BIG DATA TO SMART CITY:RECOMMENDATIONS TO COR

Brazil International Laboratory 2017Price School of Public Policy

University of Southern California

Photo: Claude Mazé

Submitted to Centro de Operações do Rio (COR) on June 2, 2017

Authored by:Alexander Yee, Andrea Avila, Fazrin Rahman,

Gabriel Armsted, Jennifer Roglà, Leigh Adamo,

Martha De La Torre, Max Sherman, Nicholas Ryu,

Radin Rahimzadeh, Rui Zhang, and Suhail Alrashidi.

Acknowledgements:We would like to thank COR for providing us with

their time and resources. Roger that.

A special thanks to Mr. Pedro Seixas and Dr.

Antonio Bento for coordinating our visits and

faciliting the creation of this report.

Muito obrigada(o)!

Since a landslide tragedy in 2010, the city of Rio de Janeiro, Brazil, has been heavily using information and communication technology to bring the government closer to the citizens under the umbrella of its Smart City Plan. It has enabled solutions that are helping the city to become more inclusive and to provide a better quality of life.

The basis for the development of the Smart City Plan for Rio de Janeiro was the expansion of the local government’s telecommunications network, which has intensified the presence of the government throughout the city, along with a digital inclusion program, an important indicator that tracks the population’s access to new technologies particularly in disadvantaged communities across the city.

Among the smart services offered by the municipal government are the monitoring and operation of the city’s operations center, Centro de Operações or COR, which enhances integration between agencies and utilities, supporting the local government’s decision-making processes.

EXECUTIVE SUMMARY

EXEC SUMMARY

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A giant wall monitor is broken into a grid showing status graphs, meteorological reports and live video feeds from traffic and CCTV. Photograph: David Levene

COR has an opportunity to build upon its intial successes and establish itself as an innovative and indispensible agency for the city.

Background

COR brings together 30 of the municipality’s departments along with private suppliers in a single monitoring room. Here they track real-time conditions in the city, and coordinate responses to emergencies and disruptions. Other cities have similar projects – Madrid has one control room for police, fire and ambulance services – but none are as big or broadly operational as that of Rio.

Information is shared real-time between city staff from various departments – from transportation to sanitation, health to emergency services – as well as with the private contractors that own the transit lines, do road work, and collect trash. For example, staff from RioÁguas - the City entity tasked with preventing floods - monitor the level of the rivers; the CET-Rio traffic agency keeps tabs on vehicle flow via the video wall, changing traffic lights if necessary and calling field agents to manage accidents as soon as they happen. Upstairs is a room for journalists, who can access much of the same information – effectively acting as COR’s megaphone, and helping crowdsource information back to COR’s systems (Frey, 2014).

COR serves as the city’s nerve center, applying analytical models to more effectively anticipate and coordinate emergency responses.

COR’s social media outlets also provide frequent updates on weather and traffic, as well as recommended alternative routes around the city on days of special events including concerts, soccer matches and festivals.

SWOT ANALYSIS

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‘SWOT’ Analysis of COR

Strengths

The strength of COR is its ability to integrate many departments involved in Rio’s daily management; and to manage crisis and emergency situations. COR’s ability to manage crisis and emergency situations is a globally recognized strength. COR also provides and exchanges information with the public through the media and social networks. The public reaps great value from these services, and has the opportunity to contribute to the improving these services by submitting crowdsourced information (Harrison et al., 2012). These strengths allow COR to be a cutting edge organization with the potential to drive innovation.

Weaknesses

Current statistics from COR’s Facebook and Twitter page illustrate a potential weakness in terms of COR’s social media outreach. Rio de Janeiro has a population of almost 6.5 million people in the city of Rio de Janeiro (IBGE, 2010), while there are 290,566 Facebook followers. Their page is still new, created in 2015, and has been accessed approximately 4,000 times to date, revealing the need to continue expanding COR’s social media outreach.

Equitable delivery and access to services in low income communities is a weakness that requires special attention due to the proliferation of informal housing developments in the City of Rio de Janeiro. These neighborhoods have long occupied an ambiguous grey zone in Rio de Janeiro, at once not own the land they built their homes upon, and yet also openly tolerated, as they were

officially “illegal,” since residents often do not own the land they built their homes upon, and yet the communities are also openly tolerated, as they provided affordable housing options for the urban poor (Penglase, 2009). This is imperative because 23-34% of the city’s population (around 1.5 million) lives in vulnerable low-income communities, most of which are located on slopes which become hazardous in intense rain (Catalytic Communities, n.d.).

Opportunities

An opportunity for COR to enhance its capacity to serve the people of Rio is to mobilize universities partnerships to improve service delivery. Cooperative university links could help develop a data science workforce that will help COR innovate its services in the future. These links strongly rely on both informal personal networks and formal organisational structures (Turpin et al., 1996). The implementation of a cooperative university-government link could increase COR’s working capacity that will enhance service delivery and would be aligned with Rio’s long-term strategic plan to become a smart city model, that invests in innovation and efficiency for a sustainable, inclusive and resilient urban administration.

COR now needs to develop a Post-Olympic mission that will equitably serve the citizens of Rio de Janeiro in COR’s day to day functions. According to the Stanford Innovation Review, a good mission statement is about the what, not the how (Starr, 2012). This would be an excellent opportunity for COR because the organization can reconsider its mission statement and rebrand itself as it enhances its social media outreach.

Threats

Threats that will impede the progress of COR are directly related to having a small staff, which could lead to systemic failures for COR. A small critical emergency response team could lead to productivity loss due to the intense amount of mental capcity such work demands. This could adversely impact the effectiveness of COR’s information communication technology systems in a time of crisis, disaster, and risk management. Additionally, Kahn (1990, 2010) describes engagement as the harnessing of people’s selves to their work, such that they fully invest their physical, cognitive, and emotional resources in their work roles. Ensuring employees are engaged and fully attentive to their tasks will be an ongoing challenge for the small direct COR team.

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COR’s ample strengths can be built upon when addressing the weaknesses, opportunities, and threats considered here. In particular, COR’s wide experience with partnerhsip building with other City agencies as well as private companies can be leveraged and expanded. The next section will consider who are COR’s current stakeholders, who are their potential partners, followed by our vision for this report. We will then consider three main areas for our COR recommendations: smart data capacity, indicators, and communication to stakeholders.

SWOT ANALYSIS

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PEOPLE & PARTNERS

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PEOPLE & PARTNERS

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PEOPLE AND PARTNERS

COR’s general categories of partnerships are laid out in the above figure. When considering their current partnerships, consistent engagement, communication, and performance measurement of internal and external stakeholders will help maintain support, advocacy, and mutually beneficial partnerships.

Yet COR has an opportunity to increase their number of external stakeholders by fostering meaningful partnerships and pushing forward collaborative efforts. Additionally, COR can work towards measuring the productivity of their internal partnerships, and evaluate the overall processes of COR to identify opportunities and develop best partnership practices.

VISION FOR RECOMMENDATIONS

To identify and strategically focus how city management in Rio de Janeiro,

specifically Centro de Operações Rio (COR), can use big data to promote

resilience and smarter city growth consistent with COR’s mission.

Most of the data out there is unstructured and it is only with artificial intelligence and ana-lytics that that data can be turned into mean-ingful data or smart data that can be used for proactive policy-making, rather than reactive policy making. Multiple layers of intelligence can be built into the big data that is collected to process, analyze, store, interpret and improve the data and effectively make the data point to nuanced patterns and information that is very useful (Shumpeter, 2011).

The exciting potential to make use of big data is highlighted in its participatory possibility that gives not only policymakers a voice, but also allows for citizens to contribute data that highlights their urgent needs to their repre-sentatives. Better resource allocation, mitiga-tion and/or response to issues allow for more resilient cities, cost-effective policy practice, and most importantly, higher quality of life for constituents. That is, a smart city should be able to actively generate smart ideas in an open environment through fostering open data that will directly involving citizens in the co-creation process of public policies or services (Bakici et. al, 2013). In order to create an optimal open source portal that would make smart data available, there are two requirements: 1. Data collected must be aggregated measure for equi-ty and 2. The scope of the data must extend in scale over a longer time horizon.

RecommendationsRequire partners to collect more variables re-lated to the same data points Ex. Populations in the same area who experience a shock differently because they live at different points in elevation.Facilitate partnerships with universities to create guideline for data sharingRecommend partnerships with data science startups to help organize, store, visualize dataCreate PENSA 2.0 within COR to facilitate data flows andanalysis. The team will continue to include: 1) Strategic planning 2) Data analysis 3) Research 4) Public policy development forecasting

From Big Data to Smart Data

The Case for Rio’s Open Source Portal

Initiatives achieved towards building a smart city democratize the policy making process and shift the old world order where policy makers influenced the data that would be collected to a new paradigm where the data allows for the formulation of robust policy questions. Howev-er, with this new shift in paradigm comes new challenges to address.

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SMART DATA & OPEN SOURCE

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Data equity

Big data has similar issues to existing data. Large data sets aggregate data points that lead to obscure models that make broad assump-tions and forecasts (Shumpeter, 2011). As mentioned, smart data, data that is disaggregat-ed, has the potential to describes the distinct experiences of diverse populations, especially with relationship to providing better policy solutions for city-wide resiliency. Having sound and disaggregated data available to be properly analyzed by data scientists, academics and pol-icy makers, allows policymakers to focus in on certain groups, devising policies and allocating resources to meet their needs (Citiscope, 2017). The more that policymakers can understand about the lived experience of citizens of varying sex, age, disability status and location (to name a few), the more they can do to ensure the vulnerable are not left behind and tailor policy solutions for particular demographics (Citi-scope, 2017). To tackle the issue of data equity, COR is positioned to create a set of standard-ized indicators that can be shared across agen-cies partnering with COR to forecast long-term risk what affect this risk would on populations even accounting for differences among those who live in the same neighborhood. Collecting disaggregated data will also lend to better re-source allocation and cost savings for the city.

An example that allows for optimal resource allocation is demonstrated in the case of cities that are prone to natural disasters. This data will allow for pre-and-post disaster evaluation that will encourage adequate and immediate funding once more precise social and monetary costs are determined. This pre/post evaluation will also encourage investment and implemen-tation of mitigation and adaptation methods to reduce future risk and high costs. In the case of Mexico and the World Bank, a Disaster Assess-ment Committee (DAC) was created before a disaster struck which consisted of sectorial

federal and local institutions. Each subcom-mittee has a maximum of 20 working days to complete fieldwork, to document and photo-graph damage using GIS devices, and to itemize reconstruction needs and the related costs. When the full damage assessment is being completed, a timely report is sent to the appro-priate governing and a viable request for fund-ing is created, allowing for the government to forecast an optimal financial strategy per fiscal year (Global Facility for Disaster Reduction and Recovery, 2014).

Data.Rio Scope

In order for the data collected by the city of Rio de Janeiro to become meaningful, COR needs to not only standardize the method in which partnering agencies collect data but also re-quire that the data be collected over longer time horizons per agency. In partnership with Data.Rio, COR can advocate for the better organiz-ing and streaming of multi-agency data and also, work with the agency to apply machine learning and visualization tools through part-nerships with Universities to produce acces-sible and easy to understand analysis to the public. In order to create the best open source portal, COR has the opportunity to facilitate the growth and scale of data.rio. It would be to the advantage of the city, as well as private part-ners and citizens for this expansion that would also create transparency, expose data vari-ability, enable for better simulation and help partnering public and private sector partners to segment populations and thus to customize more meaningful actions and policies for them. In order to facilitate the expansion of Data.Rio, it is critical that data is: 1) Complete: All public data is made available. Public data is not sub-ject to limitations, 2) Primary: Data is as col-lected at the source, with the highest possible level of granularity, not in aggregate or modi-fied forms. 3) Timely: Data is made available as quickly as necessary to preserve the value of

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Models for Success: Funding Structure & Po-litical Capacity Building

The smart city open data portal will be success-ful if two key components of its structure are met: funding and political capacity building. In the era of public-private partnerships, it is possible to identify strategic collaborations that would render many positive external returns to the city and the stakeholders involved. Even more crucial is achieving buy-in from bureau-cratic champions of innovation within the city government itself build political capacity and move smart city initiative forward in a timely fashion.

Funding Structure The funding structure that is recommended is one that will allow for multi-sector deci-sion-making and drive public policy solutions and projects that target resiliency goals, benefit a diverse public and motivate capital to contin-ue funding such projects (Plastrik and Wylde, 2001). The model is inspired by the corpo-rate-civic investment fund that was established by New York City in the early two thousands. With adequate and sustained funding, COR will become not only a big data

of the data. 4) Accessible: Data is available to the widest range of users for the widest range of purposes. 5) Machine processable: Data is reasonably structured to allow automated processing. 6) Non-discriminatory: Data is avail-able to anyone, with no requirement of regis-tration. 7) Non-proprietary: Data is available in a format over which no entity has exclusive control. 8) License-free: Data is not subject to any copyright, patent, trademark or trade secret regulation. Reasonable privacy, securi-ty and privilege restrictions may be allowed (Smart City Open City Guide, 2017). In the case of Singapore (identified as a leader in smart city initiatives), over 100 apps have been developed through integration of government data. Private sector application developers have utilized data from the Land Transport Authority to create apps that inform motorists about car park avail-ability and road pricing. Community groups have created apps for topics that add value to the public by informing citizens of options and warning them of potential encounters (e.g. clean public toilet locations and street cats). Lastly, a collaboration between People’s Associ-ation and Civil defense force that alerts first re-sponders to perform CPR before the ambulance arrives (Singapore Public Data, 2017).

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facilitator between its partners but also a big data service provider by contributing to the cleaning and analytical reports after process-ing the data. The funding model takes shape as sector experts are identified and invited to pool their capital to a city fund. These sector experts will choose high potential civic proj-ects that target resiliency goals. The internal analytics team that resembles the prior or-ganization of PENSA, will create metrics to gauge the effectiveness of the selected projects through measurements of the projects such as: cost-benefit analysis, level of citizen satis-faction and relative changes to resilience. As the number of projects grow, the relationship between private capital, public problem-solvers and [smart] big data city government capacity will solidify and persist to fund further proj-ects. The increasing number of projects would then encourage partnerships with sister cities to share best practices and initiatives to coordi-nate data sharing and city to city projects. The last value add in this structure is the availabili-ty for the city of Rio to monetize its data which allows for yet another stream of return of investment to both COR and the city of Rio by providing tailored analysis to agencies.

Political Capacity Building

Although external partners are critical to col-lecting meaningful data, implementing useful public policy projects and ensuring sustainable funding, building relationships within city government is crucial to scaling an innovative government agency in a smart city context that is gradually evolving. The model of capacity building that is recommended is to: 1) identify visionary bureaucrats, 2) create a feedback loop, 3) optimize city government operations and 4) ultimately scale COR. Due to limited city funds, it is important to identify other bureau-crats across local government to champion the necessity for COR across the government. The creation of a feedback loop that allows for em-ployees across the government to consistently ask questions about the work of COR and its impact, is crucial for the growth of COR. This feedback loop creates better coordination and communication across the government and as a positive externality, optimizes the operational methodology both with in COR and between COR and other departments, highlighting the viability of COR. Lastly, with the positive con-tribution of COR to the government space, COR will be encouraged and assisted in its team and capacity expansion.

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Recommendation

Increase COR’s strategic partnerships and measure the success of the agency by imple-menting Scorecards to evaluate performance in terms of ‘value provided to stakeholders’ and further identify best practices. We recommend that COR facilitate partner-ships with data science start-ups and Academic Institutions to sustain operational integration, actionable intelligence and, social participa-tion.

Stakeholder Analysis

The Operation Center in Rio de Janeiro is essential to providing Rio with information about situations and proposing quick solutions to minimize inconvenience and save lives. In order to make this mission possible and sustain its current and future operation, COR must en-sure the needs and criteria of its stakeholders are met (Bryson, 2011). This analysis follows Bryson’s (2011) Basic Analysis Technique by, further developing a vision for what exactly COR is planning to accomplish, identifying the current and potential stakeholders of the agency, and communicating the specific vision with them. It is also important to consider the criteria each stakeholder may use to assess COR’s value and evaluate the organization’s performance internally against that criteria. By sharing expected outcomes and strategic goals with stakeholders during the planning phase, COR can showcase a clear vision of what they are working to accomplish and what collaborative initiatives will enable COR to achieve its mission. COR will have more sup-port and trust from its stakeholders if there is an increased clarity of the agency’s purpose. In addition, characterization of the stakeholder’s

role within the strategic plan will promote the idea of a mutually beneficial a partnership. The Stakeholder table lists COR’s current Inter-nal and External Stakeholders and their level of awareness of COR’s value. The chart also includes each stakeholder’s sphere of influence and role within COR’s strategic plan.

The influence that COR’s Stakeholders have on the agency is further broken down by using the “Power vs. Interest Grid”, which helps visu-alize the various levels of interest and power among stakeholders. Further to the right, we find stakeholders with both direct and indi-rect power over COR’s initiatives, and higher up, we find stakeholders with more interest in the success of COR (Ackerman, 2011, p. 183). In-creasing the number of valuable partnerships and ‘Players’ within COR is achieved by foster-ing relationships, improving communication and increasing engagement opportunities. By sustaining valuable partnerships and main-taining Stakeholder interest, COR will increase the number of financial investments received, improve overall funding mechanisms, boost visibility, and strengthen its operation.

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Value of External StakeholdersAdditional resources (financial, research, content knowledge/expertise)Improved funding mechanisms will provide COR with the tools needed to implement the ‘Smart City’ recommendations put forth by The Inter-American Development Bank (De Lancer Julnes, 2006). Improved Stakeholder communication will help reiterate COR’s mission and confirm Stakehold-er’s understanding of COR’s purpose. Individual and agency partners are far more likely to advo-cate on behalf of COR to potential investors/partners, community leaders, and citizens.Value of Internal StakeholdersThe value of COR’s Internal Stakeholders can be measured and increased through the utilization of Balanced Scorecards. Scorecards can also measure COR’s success by evaluating the entire in-ternal process, and providing the agency with a better understanding of which areas are success-ful and which areas need improvement. By measuring the productivity and performance of COR’s Internal Stakeholders, COR has the abil-ity to utilize these results to implement and achieve its goals more effectively. This creates further opportunities for the growth and development of COR’s staff which is important to address based on the limited number of staff members due to budget constraints.

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Potential Academic & Data Science Partnerships Case Study: University-Government Partner-ships in Support of State Reform- Lessons from the Caribbean

While working towards the implementation of University-Government partnerships, it would be helpful to examine the multi-party partnership between the Universidad Autonoma de Santo Domingo, two Government Institutions within the Dominican Republic, and Utah State Univer-sity in the Unites States. This mutually beneficial partnership was initiated to support government reform efforts in the Dominican Republic and for Utah State University to position itself as a “cre-ator and dissemination of knowledge” (De Lancer Julnes, 2006). Although the multi-party partner-ship initially faced several challenges, such as, the lack of internal capacity of the Universidad Autonoma de Santo Domingo, external politics, and economic concerns (De Lancer Julnes, 2006). However, the ‘Lessons from the Caribbean’ case study displays the value of new partnerships and different perspectives, which in this case, stimu-lating the City’s development agenda (2006).

Implementation

In terms of partnering with outside universities or other research institutions, we recommend COR pursue three options in order to minimize the amount of resources needed to develop these relationships while still maximizing po-tential benefits. 1. Focus on partners with resources who have already expressed interest in working with COR.Based on our site visits, it is clear that COR’s technology is not only one-of-a-kind in Brazil, but in the entire world. As we heard, a number of research institutions and universities have been ready and excited about collaborations with COR. COR should ask about the sort of funding structure those partners envision, to understand if they partner is willing to con-tribute resources, human or material, to these collaborations. Typically these institutions will already have some funding ready for joint projects, or outside researchers seeking a rela-tionship at the very least will not expect COR to provide them with any additional funding, and only limited staff time. This means that COR can capitalize on research possibilities with just a small investment of staff time (Rogla, 2017).

2. Focus on trilateral relationships between COR, Brazilian universities, and a foreign university.This option allows COR to have a local uni-versity partner, but still capitalize on funding possibilities and additional levels of expertise from researchers at foreign universities. If COR has not already been approached by local universities seeking to carry out collaborative projects, they should consider reaching out to the international relations unit of a local univer-sity, letting that unit know that COR would like to partner both with the university but also

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capitalize on one of the applicable internation-al partnerships the university already has in the areas of planning, policy, or other types of public administration and/or transportation. For example, FGV-EASP has an International Relations Office, and already partners with the University of Southern California Price School of Public Policy, which provides joint project possibilities with local participation and thus increased sustainability, combined with the additional funding and expertise of a foreign university (Rogla, 2017).

3. Focus on international intergovernmental initiatives related to COR’s mission.

The United Nations Office for Disaster Risk Re-duction (UNISDR), in partnership with the Eu-ropean Commission, IBM, AECOM and others, came out with a new Disaster Resilience Score-card for Cities tool in May 2017 (UNISDR 2017). Rio de Janeiro is one of the participants in the UNISDR Making Cities Resilient program, and is most likely one of the few cities that has enough data to complete this very comprehen-sive new scorecard tool. The City could apply to move to ‘Role Model’ status, which may provide notoriety that will raise the profile of the City to increase the number and quality of partnerships in the future. The City could addi-tionally reach out to the agency asking if there are any other pilot initiatives or tests that COR could participate in on behalf of Rio de Janeiro. Participation in pilot programs may come with additional resources in the form of technical assistance or funding that could help COR move forward on its goals, especially in terms of prediction or creating simulations.

Typically these relationships begin with sim-ple talks about collaboration probabilities and goals of each side for the partnership. Then partner organizations sign a memorandum of understanding (MOU) that lays out more details of collaboration, including more tech-nical aspects such as any intellectual property concerns. Typically the legal arms of each or-ganization get involved, but only to ensure the language in the agreements is accurate, and you can request identical agreements be signed in multiple languages. If it is a foreign university, their international office will also typically help facilitate these agreements and/or the collabo-ration overall. Once you have an initial MOU in place, the groundwork is laid for the part-nership, and sometimes partners choose to sign project-specific agreements as collaborations move forward. While an initial MOU is not always necessary, the more complex the proj-ect is, it is a best practice to put an agreement into place to ensure projects are completed and completed in the way desired by both partners (Rogla, 2017).

Value of Performance Management

Case Study: United Nations Office for Disaster Risk Reduction

Balanced Scorecards are a set of detailed level assessment tools that allow local governments to monitor and review progress and challenges. The Scorecard examples provided for COR are based on the UNISR Scorecards implemented to measure the ‘Ten Essentials for Making Cit-ies resilient’. In this specific case, Scorecards measured and displayed the risk scenarios for each of the identified city hazards and prompts agencies to understand its “most probable” and “most severe” areas of concern (UNISR, 2017). Scorecards also measure city responses to each risk scenario (pre and post) to measure and improve its efficiency.

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COR’s performance has many complex compo-nents that should be measured by implement-ing balance score cards within the agency and City to establish a culture of using data to shape strategic goals and track progress against them in the short and long-term. When looking for indicators of success, we are, essentially judging the value that an agency provides its partners and the population it serves (Weiss, 1972). The indicators of success should directly connect to the goals of the agency and further provide measurable feedback as to whether or not those goals are being obtained within the proposed timeline (Carnochan, Samples, Myers, & Aus-tin, 2004).

One way COR can enhance its measurement of success is by implementing Balanced Score-cards which will assess the agency’s perfor-mance within the categories of ‘Objectives, Measurements, Targets, and Initiatives’ (Ka-plan, 2001). When the evaluation is completed (every six months), the scores act as a distilla-tion of key performance patterns and identify the root causes of challenges which will provide COR with an understanding of which areas the agency is succeeding and which areas need the most improvement. Balanced Scorecards can provide COR with clarity and direction that is achieved by breaking down each category into specific areas of focus. The Scorecard evalua-tion scores will then be incorporated into the next phase of COR’s strategic plan.

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Objectives: one Scorecard should include:

“Citizens Perspective”, which would provide citizen feedback on the agency’s initiatives and en-sure citizen’s feel that their opinions are valuable to the City and their concerns are acted upon. Scorecards will be evaluated to measure citizen satisfaction, determine the needs of citizens that are not currently being met, and correct actions. Below are samples of ‘Citizen Engagement’ Scorecards that can be implemented and posted as an interactive link on COR’s website and social media outlets to promote engagement and participation in evaluation efforts.

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Measurements:

An additional Scorecard should include the “Learning & Development Perspective” to measure the skills, resources, and productivity of COR employees and Agency Representatives in order to improve performance, create value and progress towards resilience. Below are examples of ‘Inter-nal Process’ Scorecards that can be shared with employees to promote engagement, incentivized participation and improve communication efforts. Furthermore, COR can track its scores every six months to increase employee satisfaction and productivity.

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Targets:

The “Internal Perspective of Mission” Scorecard should be included as communicating a succinct list of agency objectives and goals to internal employees is crucial for the team to excel beyond citizen/agency expectations. By targeting the diverse skill set of COR’s employees, the agency can prevent mission stretch and/or mission drift when new partners are introduced.

Initiatives:

It is crucial to include a Scorecard that measures the “Financial Perspective & Trust” of COR’s stakeholders. This allows COR to determine if its efforts are creating value for its stakeholders so the agency can attract additional sources of funding and establish ways to gain trust.

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RecommendationsWork with academic specialists to develop the following indices:• Hazard Vulnerability Index• Resilience Index• Smart City Index

Introduction

We recommend that COR work with academic specialists to develop three indices: a hazard vulnerability index, a resilience index, and a smart city index. An index is a type of composite measure that summarizes and ordinally ranks data (Babbie 2016). Indices are difficult to develop, and require a robust theoretical basis and sound methodological approach in order to be both accurate and instructive. An index is an aggregating tool that is best used to answer focused questions. One index focusing on quality of life in a favela may require very different data than another index focusing on quality of life in the city center. Consequently, before undertaking any index development endeavor, it is crucial to determine precisely what the indices are meant to capture, and which measures are appropriate for the chosen location and scale, for example, how they might differ in formal and informal contexts. In short, indices are complicated and highly sensitive instruments, and require expertise and careful guidance. Such expertise can be solicited through dedicated in-house researchers (see PENSA 2.0 recommendation), and/or through partnerships with the academic sector. Academic partners are particularly valuable because they can be engaged without need for significant additional resources from COR, while still providing needed capacity for research and program development. Lastly, academic partners should guide the interpretation of the indices and public policy experts should be engaged to

INDICATORS

INDICATORS

suggest policy based on the results.

Although indices are complicated and time-consuming to construct, the value to be gained from the development and maintenance of indices more than offsets these challenges. There are many reasons that COR should commit to developing these three indices.

Value of Indicators

COR’s Value: Well-constructed indices can help COR quantify its added value to the Mayor’s Office, other agencies, potential donors, and most importantly, the citizens. The indices we have proposed are tailored to help COR quantify its value through savings, efficiency, and prevented loses.

Comparative Advantage: Indices are a project that logically belongs at COR because of COR’s comparative advantage as a data aggregator. Indices are a tool for data aggregation, and require lots of data. With data from over thirty agencies and partners, COR is the best positioned entity in the city to undertake this task, and should move to act on this strategic position.

Performance Evaluation: COR can use the balanced index scores from a variety of areas as a performance evaluation tool to monitor whether COR is making progress toward its mission goals, and identify potential for greater internal efficiencies. Additionally, these indices can produce “scorecards” for the city or for neighborhoods within the city that will that allow for transparent monitoring.

Implement RioResiliente Strategy: The indices are the best application of the resilience indicators identified as flagship project of the Rio Strategic Plan 2017-2020 and RioResiliente Strategy, the latter of which COR is tasked with implementing. These indices are critical

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for monitoring success in implementation and ensuring that a robust dialogue is opened about appropriate metrics. The three indices we have proposed are also tailored specifically to the goals in the RioResiliente Strategy, and model how COR might track progress towards the Strategy’s goals. Each indicator has been mapped onto a specific goal from the Strategy, which can been seen in full in Appendix XX.

Inform Actions: One of the most important purposes of the indices is to evaluate and compile data in a way that is useful for crafting data-driven policy. While it is important to note that policy should not be “blindly” drawn from data, nonetheless, data is crucial for policymakers not only in determining the best future actions, but also evaluating the effectiveness of past actions.

Increases Equity: Like most major cities, Rio de Janeiro must address the inequitable access to and distribution of city services. Although there is broad awareness that certain neighborhoods are better served in general than others, specific deficiencies in specific services may more difficult to capture. Each of the sub-indices allows for a multi-dimensional approach to monitoring these differences.

Our Process

In order to develop the three indices, we began by reviewing academic and professional sources (such as the 100 Resilient Cities report) that allowed us to structure and measure the indicators identified by COR. We also reviewed the RioResiliente Strategy and identified the most applicable goals and subgoals of the six overarching RioResiliente Strategy goals to be incorporated within the indices. By doing so, COR can understand how measured indicators can help COR achieve RioResiliente Strategy goals. Lastly, the indicators within the Smart City Index were adapted to reflect realistic

INDICATORS

measurements based off of COR’s assets and capabilities identified within the Inter-American Development Bank (IDB) Rio Smart City case study. The site visits to CICC, Rio Aguas and other public offices and stations also allowed us to receive feedback that would allow us to expand our indices.

After conducting our research and finishing the site visits, we then began to formulate suggestions for specific indicator measurements and an index aggregation strategy for each of the indices. We also considered what other types of categorical and measurable information relevant for each indicator. For example, the ideal unit of analysis was inputted as a category so that the indices could be adaptable for different spatial scales whether that was at the city or neighborhood level. Other relevant information was identifying the source as justification for the use of each indicator and how indicators would align with different goals or capabilities outlined within the strategic documents produced by public entities.

Limitations

Although the indices produced here reflect a long process of research and adaptation to Rio’s context, it is also important to point out the limitations of these indices, and of any indices that may be built through partnerships in the future. First, because we did not have access a full menu of data that COR aggregates, our capacity to comprehensively map our indices onto COR’s existing data was limited. This can affect certain aspects of the indices such as the units of analysis as well as relevance to different RioResiliente goals.

Second, there may be overlap of certain indicators between indices and sub-indices. Overlap of indices that are highly correlated is called multicollinearity, and causes problems

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when weighting indicators and prevents accurate results. Although every effort has been taken to eliminate multicollinearity with each sub-index, it could become an issue when aggregating the three indices together as the potential for overlapping variables would increase. This issue must be addressed by future academic partners before further adaptation of the indices proposed below.

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The third issue is closely related to the second. COR must ensure that any indices developed in the future are aggregated using methodology from academic or other research partners, with a theoretically sound basis that encompasses appropriate variables, scoring mechanisms, and relevance to specific goals. This is to ensure that the final scores produced by these new and/or combined indices are meaningful and accurate.

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How to Build an Index

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Scale. Consider the scale of the measurement. These measurements could be specific populations, neighborhoods, or cities. This is important because the scale will inform the variables and measure-

ments that could capture specifically-desired information. For example, Cutter et al. chose to evaluate a region comprised of eight states in the U.S.A that is under the management of a federal disaster management agency known as FEMA.

Building an Index is a complicated and technical endeavor. The following steps outline a basic overview on how an index is constructed. Additionally, we use the Disaster Resilience Index as an index example. It was created and applied by authors including Susan Cutter, a leading author in the field of resilience.

Theory. An index needs a theorical basis to determine what should go into it. This can be an existing theory from an academic source or developed anew. Cutter et al., chose the “Disaster

Resilience of Place (DROP)” theoretical model, but different models may be adopted according to need. For any theoretical basis, it important that the theory or idea can be empirically tested.

Variables. Choose appropriate variables, tak-ing note of the data’s consistency of measurement and the data quality. You may need to balance variables from academic research or the available

data. Between the two, variables from the chosen prescribed theory should be prioritized.

Clean. “Clean” the data and address any of missing values. There are four methods to clean the data: (1) Standardize the data to avoid problems that occur when mixing measurement units. (2) Check to make sure no

two indicators are strongly correlated, thus ensuring the integrity of the weighting system. (3) Perform an item analysis to check whether each of the items included in a composite measure makes an indepen-dent contribution. (4) Normalize measurements so that variables are on a similar measurement scale. The Min-Max rescaling method can be used.

Weights. Use a theoretical basis to determine the weights of each indicator and sub-index. Typically items should be weighted equally, unless the literature recommends otherwise. Some theories should require

participatory feedback to gauge the weights of different measures. For example, social justice theories might require a participatory process to assign weights based on differing community perceptions of priorities.

Score. Create the index score. One can simply add up the sum of the indicators or sub-indices. In our example, the authors needed to first average the sub-index scores to account for an inequal number of variables across the

sub-indices. Once the average score was determine, the scores were added together to create a final Disaster Resilience Score.

Resilience Index

The resilience index is designed to meet two of the needs identified by COR: how to use the disaster-related and mobility-related data and how to achieve city resilience objectives related to RioResiliente Strategy goals. Seven sub-indices were constructed to capture the experiences of citizens living in both formal and informal communities. Furthermore, the vulnerability to disasters varies due to geographical locations which implies that resilience improvement solutions must be customized accordingly.

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The city’s ability to predict and react to disasters does not only come from advanced techniques and comprehensive infrastructure, but also from the public’s’ ability to access information and therefore make necessary preparations. Thus, it is important to build a comprehensive evaluation system integrating the various aspects within the context of Rio de Janeiro. Given the that the city needs to recognize that different communities have different resilience capabilities to cope with different types of disasters, communities should have customized resilience improvement plans.

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See Appendix 1 for full table.

MobilityWe can demonstrate how the rest of the index would be built out using the mobility indicator as an example. The mobility indicator can help COR track the performances of the transportation systems in Rio de Janiero. This indicator targets both the short-term goals of disaster management (see the Saturation of Road Infrastructure sub-index in Appendix XXX) and the long-term goals of sustainability. The 12 variables within the mobility indicator help construct a performance evaluation system and a focus on transportation planning based on the perspectives of infrastructure, city operation, and transport usage sectors.

In the short-run, public safety stresses the need for a necessary communication channel of transportation information when disaster strikes. By evaluating the effectiveness and efficiency of the information platforms that include physical information boards and smartphone applications, COR can be more aware of where the resources should be distributed to expand its ability to inform people of transit options.

Reachability is also important on rainy days as it directly affects the connectivity of the Rio transportation system, intermodal integration,

and the modal split of transportation options. Unexpected road obstacles can change people’s choice to choose transportation modes and routes. For example, a larger metro station can accommodate more people as an intermediary transfer option between different transportation modes over a longer period of time. However, the availability of these alternative modes can vary amongst communities due to the transit access that was allocated by resource distribution and planning agencies.

In the long-run, the measurements contribute to sustainable transportation and land-use planning in Rio de Janeiro. According to a research study on a comparative evaluation of mobility in several Brazilian cities: Belém, Curitiba, Goiânia, Juazeiro do Norte, Uberlândia and Itajubá, data availability and data quality were the two major factors affecting mobility within the cities. Benchmarking a well-structured and detailed mobility evaluation system that has been tested in the context of Brazil would be a valuable source for the further enhancement of Rio’s mobility evaluation system.

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Long-term policy making such as vehicle emission control relies on the analysis of emission variables (listed in the Saturation of Road Infrastructure part in Appendix 3). One important concept to note is the “sponge city” concept implemented in two series of pilot cities in China. This concept stresses the flexibility of road infrastructure to permeate, absorb and recycle water, which combines the rainfall treatment system with the road system.

Hazard Vulnerability Index

The Hazard Vulnerability Index is an index that is partially derived from the overarching Resilience Index. It was made as a separate section to better clarify 11 sub-indices that specifically focus on Rio de Janeiro’s vulnerabilities to disasters. These are namely the 11 chronic stresses and shocks identified in the RioResiliente Strategy as opposed to the overall resilience of city operations and the citizens of Rio de Janeiro. The indices specific to each shock will enable COR and the city to generate a more detailed resilience plan to distribute disaster management resources.

See Appendix 3 for full table.

Intense Rain

An applied example of the Hazard Vulnerability Index is Intense Rain, which showcases how sub-indicators from the Hazard Vulnerability index are constructed and explained. In the case of Intense Rain, sub-indicators range from Landslide Vulnerability to Community Perception. The aforementioned sub-indicators utilize different measurements that either have a positive or negative effect on resilience within the city of Rio de Janeiro. Furthermore, the measured sub-indicators had extrapolated data from data portal sources such as AlertaRio, Data.Rio, and GeoRio, city case studies, and/or other academic sources.

Smart City Index

While the previous two indices are more focused on measuring Rio de Janeiro’s resilience capacity and quantifying COR’s added value to external stakeholders, the Smart City Index was created as a way to internally evaluate COR’s key functions and performance while also offering insight and recommendations into how COR can become a more effective agency.

The Smart City index includes seven different sub-indices based on an academic literature review of six different sources. The subindices thematically revolve around COR’s technological and partnership capacities. Furthermore, the seven sub-indices encompass 46 different measurable variables but the same units of analysis as the other two indices.

The Smart City Index is also helpful because it also show COR how to further enhance its own capabilities. These include prevention measures and actions that will prevent further accidents and disasters, overall operational efficiency, and/or increasing its ability to

INDICATORS

predict when and where certain accidents or disasters will occur. While the Smart Cities Index does not list as many variables that can be adapted for COR’s prediction capabilities, this is something COR can further study and utilize academic professionals for to develop more relevant indicators for COR.

Lastly, the Smart City Index can help suggest actions that can help COR achieve some of the RioResilinte goals (such as the Execution Simulations for Crisis Response) while also referencing COR’s assets and capabilities based on the informational sections of IDB Rio Smart City case study (RioResiliente Strategy).

Safety and Security

An applied example of the Smart City Index is the Safety and Security indicator. Through nine different variables, the Safety and Security indicator can measure the “Decrease in Evacuation Time” sub-indicator. So when a flood disaster happens, COR can track how quickly it was able to evacuate potential victims from formal and informal neighborhoods to appropriately designated safety areas using the “Decrease in Evacuation Time” variable. Over time, COR can review and compare their response time records to evaluate if there were improvements in their performance.

By reviewing sub-indicators, COR can learn how to improve upon its smart city services related to evacuation time and network congestion incidents. Specifically, COR can reduce the time needed for disaster-related evacuations as well as predict where and when network congestion incidents will occur thus reducing the amount of potential future network congestions events.

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Intense Rain Sub-index

Safety and Security Sub-index

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INDICATORS

Mobility Sub-index

Case Studies

Resilience by Neighborhood LevelDurban, South Africa

In 2006, the eThekwini Municipality developed the Municipal Climate and Protection Programme incorporating both an assessment of climate change and development of response strategies at the local level. Created after heavy torrential rains that devastated the region’s emergency response resources, the municipality’s Environmental Planning and Climate Protection Department encouraged three sectors for development: health, water, and disaster emergency. The Programme, was one of the first to addressed climate change while also adopting a culturally competent approach. Building on social equity gains post-apartheid, the Programme specifically addressed the unique impacts of climate change on informal housing arrangements. It created job opportunities for those living in informal housing through the Green Roof Top Project, where rooftop gardens serve to conserve energy within buildings and creates jobs in agriculture. Additionally, the eThekwini Municipality allowed different neighborhoods within Durban to adopt their own customized climate response plans to improve Programme outcomes. Given the RioResiliente goal to create jobs, a similar strategy could be employed in Rio de Janeiro. This could also be an opportunity to move Rio’s data collection - and potentially strategic plans - down to the neighborhood level, which will allow for more equity in the implementation and outcomes of the city’s resilience initiatives.

Lessons from the Durban case show that support from local political leadership for climate adaptation planning is essential. This increases the opportunity for public and private cooperation to further new adaptation strategies, the City’s development objectives, and available funding and skills (ICLEI, 2012). Durban’s “learning by doing” approach was supported by robust monitoring, evaluation and defensible research. The research partnerships between the three sectors of health, water, and disaster management were essential in order to roll-out pilot tested strategies (ICLEI, 2012). Finally, a lack of social cohesion is a substantial barrier to effectively engage communities around climate change, thus the municipal government needed to consider responses at the neighborhood level in order to address the many intersectional realities that impact different communities (Roberts, 2010). Their experiences illustrate the need for resilience indicators to separately capture social and community resilience, as done in the Resilience Index

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Durban

Source: ICLEI, 2012

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Case Studies

Mobility ResilienceMumbai, India

The Brihanmumbi Municipal Corporation (BMC) implemented a plan in 2016 to improve its rail-way systems by elevating and improving the structure in conjunction with the Station Area Traffic Improvement Scheme. The plan is to improve 20 railways and create high station platforms to deal with potential flood waters that would disrupt mobility services. Car, taxi, and foot traffic will also be addressed in various stages. Like Rio, Mumbai has heavy foot traffic and is prone to vehicle bottlenecks that impede emergency services to its nearly 18 million citizens.

Mumbai is also a disaster-prone city. It has been hit by a number of monsoons, and regular-ly faces challenges when citizens evacuate the city or head to emergency centers. Transpor-tation problems have arisen mainly due to the uncontrolled expansion of urban sprawl and improper land use, meanwhile employment is still concentrated in the city center which leads to a job-housing imbalance. Informal settlements have appeared along Mumbai’s roads, highways, and railways, causing accidents, poor infrastructure, and unsustainable living en-vironments (Cheshmehzangi & Thomas, 2016). Overcrowding and road congestion due to these communities would also be alleviated by raising the train tracks and expanding the railways. Rio de Janeiro could also consider elevating its BTS lines, light rail lines, or other roadways that could be used for emergencies to deal with the congestion pressures coming from large informal housing and labor sectors, increasing urban sprawl, and intense rain. It is also an important lesson to control the private vehicle ownership to reduce the emission.

Mumbai

Source: Rediff.com

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Case Studies

Disaster ResilienceManila, Philippines

Due to a combination of a growing population, degradation of resources, and climate change, Manila is increasingly vulnerable to extreme flooding events and typhoons (Roberts 2011). Ma-nila’s municipal government has initiated several disaster reduction programs relevant to Rio de Janeiro. For example, effective community-based measures were implemented to educate, train, and provide residents in vulnerable areas with real-time, localized disaster risk information. This helped residents prepare for imminent disasters in an expeditious manner. Moreover, the City of Manila gave citizens a checklist of actions, needed supplies, and communications and contingen-cy templates to build resilience and disaster preparedness on the community level. This format, could help COR implement more effective evacuation planning.

Manila has also adapted a System Dynamics Model (SD) to better quantify its resilience, which allowed them to be proactive at making policy. SD modeling platforms allow for a system to be built virtually in terms of stocks, flows, input information and feedback loops (Gotangco et al., 2016). It analyzes the interactions between diverse data inputs and outcomes, which improves the prediction of upcoming hazards and their effects. This approach helped Manila track its resilience efforts, and could help COR track and predict emergency responses as well. For example, in the context of flood resilience, COR can use the system to track economic losses from flooding and potential savings due to adaptive measures. In these times of scarce public funding, COR could even predict economic losses in the event of a disaster to demonstrate the importance of fortifying its service delivery and community outreach efforts.

Manila

Source: Rotary International

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Case Studies

Smart CitiesKuala Lumpur, Malaysia

Kuala Lumpur has composed a system to enhance its use of information communication technol-ogy and e-governance to create a comprehensive plan that will improve overall city functionality as a burgeoning smart city (Lau et al., 2014). The Economic Transportation Program was created by the city in 2014 and was divided into nine different Entry Point Projects (EPP); EPP 1, 2, and 4 specifically push forward smart city indicators. EPP 1 and 2 emphasize the need for recruiting technology firms and experts that will instigate smart technology innovation and distribution, which are smart city indicators that could incentivize new technological projects and increase the hardware and software capacity of a city. EPP 4 focuses on the need for integrating new informa-tion technologies into public transit systems, which can be measured by smart city indicators that monitor traffic accidents and can divert users to alternative routes while also incentivizing poten-tial pedestrians and car-users to utilize public transit systems.

The overall EPP plan models a multi-phase strategy to acquire and incentivize startups that can enhance the technological capacity for this emerging smart city, recruit interna-tional and domestic technology experts and firms that will incentivize smart city innova-tion, and increase technological hardware such as sensors and software systems such as Wifi networks. Kuala Lumpur’s projects speak to COR’s vision of enhancing Rio de Janei-ro’s smart city capabilities. Such projects could allow COR to increase its smart city de-velopment projects as well as expand its digital monitoring efforts throughout the city.

Kuala Lumpur

Source: Lau et al., 2014

Once COR is able to develop, implement and measure the different indicators, it is important to create strategies to communicate this content with citizens and potential partners. In order to do so, we recommend:

1. Identification of different levels of user access to facilitate data cleaning

2. Target potential start-ups to develop Application Programming Interface (APIs

3. Solidify social media outreach and measure its success by using social media indicators

4. Use social media platforms to analyze citizen priorities and match scorecard results to citizens’ perceptions

5. Dissemination of scorecards

Value Added to COR We see that these recommendations add value to COR’s key functions by:

Time saved

A) Integration of social media platforms. This can be done by posting content on one site which will then be automatically populated on the other sites• “Automating social sharing” or cross-

referencing all existing social media will not only save time when posting data but it will also ensure that the information is reaching all followers through the different platforms (Vahl, 2015). Doing so will allow the agency to ensure that the shared information reaches a larger target audience through the multiple platforms as not every Facebook follower has a Twitter account and vice versa, and same goes with other social media platforms.

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B) Facilitation of information dispersion during times of crisis• Connecting social media sites, saves time

when posting messages as a post in one platform should automatically post to another. This would save time in trying to make a post for every site, especially during times of crisis when agencies want to send out information as quickly as possible.

• “With the click of a button, a picture, video, or message can become viral as it is sent to 10, 50, 100, or a thousand people” (Thackeray et al., 2008).

Low cost outreach

A) Social media tools provide a free platform to directly communicate with citizens• “Tapping the spirit of the Free Open

Source Software (FOSS) movement” opens up an opportunity for receiving “input and innovation” allowing the public and partners to do some work giving them power and opportunities for innovation that also helps COR in receiving more personalized information from the public (Linders, 2012).

B) It also allows for the purchase of promotional ads for short periods of time if necessary (Facebook, 2017)

Increase citizens participation and trusts

A) Social media has been used by different government agencies to increase transparency by bringing information to citizens in their preferred platform

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B) The ability to bring government content via mass distribution enables new forms ofcitizen participation, therefore enhancing “social consciousness and citizen engagement” (Bonson et al., 2012)

Improve data received

A) New technologies have prompted citizens to become more involved in the “co-production of knowledge and information”, extending their role from only users to partners (Linders, 2012)• Keeping the public engaged with relevant

information will help bring in more public interaction that can allow COR to receive more personalized information/data. The public can share COR’s posts taking part in the “promotional strategy” and also participate in the sharing of information or asking questions that will help the agency improve its content for the future as well as increase “viral marketing” (Thackeray et al., 2008).

B) This production of knowledge and exchange of information adds value to COR’s data pool

New partnerships

A) This new wave of information creates new opportunities to develop partnerships with Rio’s agencies as well as international financial institutions, such as the World Bank or the International Development Bank, to develop innovative ways to consume the data created.

Engagement Plan

We advise the following engagement plan to begin implementing the recommendations. In addition, we believe it is important to distinguish between the different audiences that have access and receive the data produced by COR. For this reason, we have divided the plan between developers (e.g: Google, Waze) as

administrators (Public agencies within COR) and users (citizens of Rio).

Developers & Administrators

A) Data cleaning • Understanding who receives data: As

COR sends out data it needs to clean out different parts depending on who receives it. As a result, it needs to dedicate more staff time to this task. Creating a standard procedure of who receives the data, it would allow COR to set a specific number of staff dedicated for this task. This number would only change in cases of emergency.

B) APIs• The vasts amount of data that COR

receives and the opportunity to receive more via social media to create the perfect opportunity to seek partnerships with small start-ups. The partnership will allow for the creation of an Application Programming Interface (API). This API can later be used for the creation of a mobile application that can aggregate some of the services individual agencies within COR already provide.

• This application can be used to target different populations and create individualized content that Cariocas can use in their daily lives.

Users (Increasing PR & sending out relevant information)

With a population of almost 6.5 million people in the city of Rio de Janeiro (IBGE, 2010), distributing specific data information to the public is not an easy task. COR has been doing a great job of creating social media platforms that engage Cariocas and help distribute relevant information. However, there is still some room for improvement as current platforms only cover 12% of the population.

This percentage does not take into consideration that some of the followers may not be part of the Rio population. We believe COR could implement the following steps to continue to engage and increase their citizen audience:

A) Implementation of a social media campaign• European organizations are learning about

the opportunities digital sources and social media are presenting, though they may still rely on print media (working with journalists) as a primary source of media, they recognize that social media and other online forms of communication will be taking over the “leading position” in communicating information to the public (Verhoeven et al., 2012). It is for this reason, that emphasis on a campaign that aims to increase the number of followers is more than important than ever.

• Examples to increase followers include: usage of television and radio, “COR Bacano” campaign that engages school age children by allowing school visits into the center, and partner with local Carioca celebrities that can re-Tweet and/or share COR’s content.

• Another way to promote COR’s content is through the usage of other existing social media pages: The inclusion of social media links in the description section of the media pages, listing social platforms in cover photo descriptions, sharing of content from one social media site to another, and automating social sharing from one platform to another are some ways of using social media platforms as promotional tools (Vahl, 2015).

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Social Media Indicators

One of the most important components of our report is the application of indicators that can allow COR to measure implementation outcomes. We are recommending the usage of the Social Media Metrics for Federal Governments (Herman, 2013). Although designed for federal governments, they can be used with local governments by picking individual or a set of indicators depending on what COR wants to measure.

BreadthProvides information on traffic and content usage:• Community SizeWhat it measures: Measures account popularity. It takes into consideration other measures in order to not only rely on number of followersHow to measure: Number of fans, followers, subscribers and unique individuals that have seen the page’s content• Community GrowthWhat it measures: Account popularity How to measure: Difference between current number of fans from previous month or year

(Image retrieved from http://bloggersclick.com/grow-facebook-followers-earn-money-facebook-page/)

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DepthLooks into the time, outcome and context of a visit. Number of desired actions that users complete • ConversionsWhat it measures: Volume of desired actions How to measure: Analytics programs• ViewingWhat it measures: How often and for how long videos are viewed How to measure: Minutes watched and number of views on YouTube analytics tools

Direct EngagementMeasures how much followers or general visitors use the content on social media sites.• Engagement VolumeWhat it measures: An agency’s engagement with the public through metrics on its dimensions and frequency.How to measure: Native analytics programs collect and report for each social media tool, such as Twitter analytics, Facebook insights, and YouTube analytics.• Engagement ResponsivenessWhat it measures: Success rate of an agency for its responsiveness on social media.How to measure it: Collecting data at the end of the each day or at the end of a specific event.

LoyaltyIt measures visitor loyalty and returns Return CommunityWhat it measures: How many current members return to see content How to measure: Google analytics allows for the creation of a custom segment specific produced content

Customer ExperienceIt measures what it is being said about programs, events or any other relevant content that can aid in the improvement of practices and service delivering. Due to issues of privacy, data collected should not be identifiable. • SentimentWhat it measures: What is being shared about programs and value trends How to measure: There are a number of free analytic available, but it is important to ensure that the program ensure users’ privacy• IndicatorsWhat it measures: Provides information on social programs provided by the agency How to measure: Tools used to measured sentiment can also be used for indicators • Survey FeedbackWhat it measures:Results of citizen satisfaction on agency’s social community via surveys How to measure: Survey software. Recommended to survey during targeted campaigns in order to invest the public into the program

CampaignsPerformance reports of specific programs and tactics with the use of the five metric categories mentioned above.What it measures: Provides an organized breakdown of the performance of both short and long-term projects or programs.How to measure: Through the combination of chosen metrics based on the what the desired end result.

Strategic OutcomesReports on the direct impact to strategic organization priorities by social media strategy performances.

What it measures: Extensive breakdown linking the impact of the mission to social performance metrics.How to measure: Narrative explanation of a combination of metrics, campaigns, and organizational goals.

Based on this list, we have also included a list of social media indicators for smart cities. Some of these indicators take into consideration the different characteristics of Rio’s diverse population. Please find them in the appendix section.

Scorecard

As mentioned in the performance management section, scorecards are an integral tool to measure COR’s implemented strategies and analyse their effectiveness. The scores received can also be used to compare the citizens’ perceptions of the state of COR. This can be accomplished by providing surveys via social media that can be tailored to the neighborhood level.

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Short-Term Recommendations

Phase 1 (6 Months)

Smart Data & Open Source• Require partners to collect more dynamic

data to reflect neighborhood information• Recommend use of data science startups

to help organize data and output through visualization tools

Indicators• Identify academic or research partners to

help develop new recommended indicators and indices

Communication• Identify the different levels of user access

to facilitate data cleaning• Target potential start-ups to develop

APIs. Possibility of consolidating mobile applications with the different agencies within COR

Phase 2 (1st Year)

Smart Data & Open Source• Advise data.rio to release frequent output

of reports to highlight value of COR and sustain conversation and funding

• Create PENSA 2.0 within COR to facilitate data flows and analysis.The team will continue to include: 1) Strategic planning 2) Data analysis 3) Research 4) Public policy development forecasting

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Indicators• Identify existing data sources for indicators

and check robustness of current indicators through triangulation with external data sources like NASA

Communication• Solidify social media outreach via publicity

campaign. Measure its success through social media indicators

• Implementing Balanced Scorecards to measure performance

Long-Term Recommendations Phase 3 (2nd Year)

Smart Data & Open Source• Create a Damage Assessment Committee

(DAC) to improve damage and loss assessment procedures that will help strengthen the country’s response capacity (quantify the cost-savings of COR’s work)

Indicators• Determine new data sources/priorities

via: Relationship to RioResiliente Plan and/or COR mission, focus groups with stakeholders especially citizens and guidance from academic literature

Communication• Utilize social media platforms to strengthen

citizen participation in COR initiatives and crowdsource information for real-time personalized response in times of natural disaster

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IMPLEMENTATION STRATEGY

SMART DATA & OPEN SOURCE

INDICATORS

COMMUNICATION

Phase 4 (Beyond)

Indicators• Institutionalized data transparent and

scale data at a neighborhood level for more targeted data sets

• Adopt a disaster risk reduction mindset versus a disaster relief mindset

Communication• Empower and provide the tools for

community institutions to become active partners in resilience efforts throughout Rio - including the areas of water management, sanitation and disaster relief

• Build upon WhatsApp’s popularity

IMPLEMENTATION

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Sub-Index Variable / Indicator How Measured Disaster Related

Expected Effect on Resilience

Justification Additional Cities Where Used

Recommended Unit of Analysis

RioResiliente Goal Additional Notes on Application to RJ Context

Community

Migration Net migration Yes Negative Adapted from Cutter et al. 2010 Southeast Region, USA City

Native Born Population Percentage population locally born still residing there Yes Positive Adapted from Cutter et al. 2010 Southeast Region,

USA CityThis capitalized on the wealth of institutional knowledge and history within both formal and informal communities by families that can facilitate coping with emergencies.

Civic Participation Percentage voter participation in the last city election Yes Positive Adapted from Cutter et al. 2010 Southeast Region, USA Neighborhood 6.G

Community Faith Number of religious followers per 1000 population Yes Positive Adapted from Cutter et al. 2010 Southeast Region, USA Neighborhood This also may relate to the number of local churches, which are often

safe houses during intense rains.

Civic Involvement Number of civic organizations per 1000 population Yes Positive Adapted from Cutter et al. 2010 Southeast Region, USA Neighborhood

Advocacy Number of social advocacy organizations per 1000 population Yes Positive Adapted from Cutter et al. 2010 Southeast Region,

USA Neighborhood

Innovation Percentage population employed in creative class occupations Yes Positive Cutter et al. 2010 Southeast Region,

USA Neighborhood 5.D This should capture the innovation strengths of neighborhood citizens that may increase problem-solving capacities during emergencies.

Homeless Population Number of individuals living on the street Yes Negative RioResiliente Strategy Neighborhood 6.F

Social

Access to FoodPercentage of land-area within 0.5 km of at least 1 vegetable market or supermarket selling fresh food and vegetables

Yes Positive Adapted from CRI 2017 Los Angeles, USA Neighborhood This attempts to capture food deserts, in particular access to fresh foods.

Malnourishment Percentage of malnourished children under five as a percentage of all citizens under five Yes Negative Adapted from CRI 2017 Neighborhood

Educational Equity Ratio of the pct. population with college education to the pct. population with no high school diploma Yes Negative Cutter et al. 2010 Southeast Region,

USA Neighborhood

Age Percentage non-elderly population Yes Positive Cutter et al. 2010 Southeast Region, USA Neighborhood

Transportation Access Percentage population with a vehicle Yes Positive Cutter et al. 2010 Southeast Region, USA Neighborhood

Communication Capacity Percentage population with a telephone Yes Positive Cutter et al. 2010 Southeast Region, USA Neighborhood

Language Competency Percentage population who do not speak Portuguese as a second language Yes Positive Adapted from Cutter et al. 2010 Southeast Region,

USA Neighborhood

Special Needs Percentage population without a sensory, physical, or mental disability Yes Positive Cutter et al. 2010 Southeast Region,

USA Neighborhood This measure will reveal physical accessibility issues by neighborhood.

Health Insurance Coverage Percentage population with health insurance coverage Yes Positive Cutter et al. 2010 Southeast Region,

USA Neighborhood 6.D

Infant Care Percentage of newborns seeing the doctor within 7 days after discharge from the hospital No Positive RioResiliente Strategy Neighborhood 6.D

While this is emphasized in the RioResiliente Strategy for underserved communities, breaking it down by neighborhood will allow for better metrics to determine if socioeconomic status is indeed the main predictor.

Medication Access Percentage of land-area within 0.5 km of at least 1 pharmacy Yes Positive Adapted from CRI 2017 Los Angeles, USA Neighborhood

Vaccination Rate Percentage of age appropriate vaccination rate No Positive RioResiliente Strategy Neighborhood 6.E

While this is emphasized in the RioResiliente Strategy for underserved communities, breaking it down by neighborhood will allow for better metrics to determine if socioeconomic status is indeed the main predictor.

Prenatal Care Percentage of prenatal consultations started in the rest trimester of pregnancy No Positive RioResiliente Strategy Neighborhood 6.E

While this is emphasized in the RioResiliente Strategy for underserved communities, breaking it down by neighborhood will allow for better metrics to determine if socioeconomic status is indeed the main predictor.

Primary School Enrollment Percentage of youth enrolled in primary schools No Positive RioResiliente Strategy Neighborhood 6.E

While this is emphasized in the RioResiliente Strategy for underserved communities, breaking it down by neighborhood will allow for better metrics to determine if socioeconomic status is indeed the main predictor.

Documentation Percentage of people with complete personal documentation No Positive RioResiliente Strategy Neighborhood 6.E

While this is emphasized in the RioResiliente Strategy for underserved communities, breaking it down by neighborhood will allow for better metrics to determine if socioeconomic status is indeed the main predictor.

Institutional

Population Covered by a Metropolitan Disaster Management Plan

Percentage of the population covered by a disaster recovery plan Yes Positive Cutter et al. 2010 Southeast Region,

USA Neighborhood 2.A Adapted to the RioResiliente goal.

Housing Insurance Coverage Percentage of formal and informal housing units covered by housing insurance policies Yes Positive Adapted from Cutter et al. 2010 Southeast Region,

USA NeighborhoodAttempts to capture insurance needs within low-income communities by ensuring the percentages capture all housing units, rather than just formal ones.

Municipal Services Percentage of municipal expenditures for fire, police, and emergency medical Yes Positive Cutter et al. 2010 Southeast Region,

USA City

Political Fragmentation Number of political parties receiving votes in the last election Yes Negative Adapted from Cutter et al. 2010 Southeast Region,

USA Neighborhood

Previous Disaster Experience Number of past disaster declarations Yes Positive Cutter et al. 2010 Southeast Region, USA Neighborhood

Resilience Education - Schools Percentage of schools incorporating resilience into their curriculums Yes Positive Adapted from Cutter et al. 2010 Southeast Region,

USA Neighborhood 6.A

Resilience Education - MOOCs Number of students enrolled Yes Positive RioResiliente Strategy City 6.B

AlertaRio SMS Coverage Percentage of the population who have opted in to the AlertaRio SMS Yes Positive Adapted from Cutter et al. 2010 Southeast Region,

USA Neighborhood

AlertaRio Resilient Communities Participation

Number of community leaders participating in the Resilient Communities Program Yes Positive Adapted from Cutter et al. 2010 Southeast Region,

USA Neighborhood 2.D Adapted to the RioResiliente goal.

Participation Rates in Citizen Science

Percentage of citizens participating in the RJ Citizen Science initiative Yes Positive Adapted from Cutter et al. 2010 Southeast Region,

USA City Adapted to the RioResiliente goal.

Participation Rates in River Guards

Percentage of citizens participating in the RioAguas River Guards initiative Yes Positive Adapted from Cutter et al. 2010 Southeast Region,

USA City Adapted based on site visit with RioAguas.

Sub-Index Variable / Indicator How Measured Disaster Related

Expected Effect on Resilience

Justification Additional Cities Where Used

Recommended Unit of Analysis

RioResiliente Goal Additional Notes on Application to RJ Context

Infrastructure

Housing Types Percentage housing units that are formal Yes Positive Adapted from Cutter et al. 2010 Southeast Region, USA Neighborhood 4.E Adapted to better capture the experiences of the large informal housing

population in Rio.

Housing Age Average age of formal and informal housing units Yes Negative Adapted from Cutter et al. 2010 Southeast Region, USA Neighborhood 4.E Adapted to better capture the experiences of the large informal housing

population in Rio.Shelter Capacity - Vacant Housing Percentage vacant units Yes Positive Adapted from Cutter et al. 2010 Southeast Region,

USA Neighborhood Adapted to better capture the experiences of the large informal housing population in Rio.

Shelter Capacity - Vacant Hotels Number of hotels/motels per square km Yes Positive Adapted from Cutter et al. 2010 Southeast Region, USA Neighborhood Adapted to better capture the experiences of the large informal housing

population in Rio.

Medical Capacity Number of hospital beds per 1000 population Yes Positive Adapted from Cutter et al. 2010 Southeast Region, USA Neighborhood Adapted to the neighborhood level.

Evacuation Potential - Access Principal arterial miles per square km Yes Positive Adapted from Cutter et al. 2010 Southeast Region, USA Neighborhood

Evacuation Potential - Safe House Number of public schools per square km Yes Positive Adapted from Cutter et al. 2010 Southeast Region,

USA Neighborhood

Electricity - Access Percentage of city population with authorized electrical service No Positive Adapted from CRI 2017 Los Angeles, USA Neighborhood Adapted to better capture the experiences of the large informal housing

population in Rio.Energy - Consumption kW per day per person No Negative RioResiliente Strategy Neighborhood 4.C

Energy - Investment in Efficiency Total annual public investment (BRL) in energy use efficiency No Positive RioResiliente Strategy City 4.C

Energy (Solar) - Municipal Access Total kW installed in municipal buildings No Positive RioResiliente Strategy City 4.B

Energy (Solar) - Decentralization Amount of mWh produced by decentralized solar energy Yes Positive RioResiliente Strategy Neighborhood 4.B

Energy (Solar) - Investment Total annual public investment (BRL) in solar energy No Positive RioResiliente Strategy City 4.BEnergy (Solar) - Use Metrics tons of GHG offset by solar use No Positive RioResiliente Strategy City 4.B

Street Lighting - Type Percentage of existing luminaires substituted for LED technology No Positive RioResiliente Strategy Neighborhood 3.A

Street Lighting - Access Number of street lights per sq km No Positive RioResiliente Strategy Neighborhood 4.E

Water - Access Percentage of households with authorized access to clean water No Positive Adapted from CRI 2017 Los Angeles, USA Neighborhood

Water - Consumption Liters per day per person No Negative RioResiliente Strategy Neighborhood 4.C, 5.A

Water - Investment in Efficiency Total annual public investment (BRL) in water use efficiency No Positive RioResiliente Strategy City 4.C, 5.A

Water - Drinking Quality Micrograms of pollutants per liter in drinking water No Negative RioResiliente Strategy Neighborhood 4.D

Water - Water Body Quality Micrograms of pollutants per liter in other water bodies No Negative RioResiliente Strategy / RioAguas

data point City 4.D, 4.F

Sanitation - AccessPercentage of population covered by the sewage disposal system with treatment in the basins of Guanabara, Sepetiba, and Jacarepagua

No Positive RioResiliente Strategy Neighborhood 4.D, 4.E

Contamination Risk Percentage of land-area within 0.5 km of a contamination risk No Negative San Francisco Community

Resilience Indicator System San Francisco, USA Neighborhood

Reduction of Waste Diverted tons per sq. km. No Positive RioResiliente Strategy Neighborhood 5.APavement Percentage of paved streets/pedestrian walkways No Positive RioResiliente Strategy Neighborhood 4.E

Green Roofs Percentage of roofs converted to gardens/green spaces No Positive ICLEI, 2012 Durban, South Africa Neighborhood 3.B

Economic

Employment (Formal) Percentage employed in the formal labor sector Yes Positive Adapted from Cutter et al. 2010 Southeast Region, USA Neighborhood More indicators are included in this sub-index to better capture the

informal labor market in Rio.

Employment (Formal) - Women Percentage female labor force participation in the formal sector Yes Positive Cutter et al. 2010 Southeast Region,

USA Neighborhood More indicators are included in this sub-index to better capture the informal labor market in Rio.

Employment (Informal) Share of employment in the informal sector No Negative Site visits / ILO 2013 Brazilian national statistic Neighborhood Brazil is already recording these measurements, and RJ sees a

considerable amount of informal labor market activity (see: ILO, 2013)Employment (Informal) - Outside Informal Sector

Share of informal employment outside the informal sector No Negative Site visits / ILO 2013 Brazilian national

statistic Neighborhood Brazil is already recording these measurements, and RJ sees a considerable amount of informal labor market activity (see: ILO, 2013)

Employment (Informal) - Women Share of women in employment in the informal sector and informal employment No Negative Site visits / ILO 2013 Brazilian national

statistic Neighborhood Brazil is already recording these measurements, and RJ sees a considerable amount of informal labor market activity (see: ILO, 2013)

Single Sector Employment Dependence

Percentage population not employed in farming, fishing, forestry, and extractive industries (both formal and informal employment)

Yes Positive Cutter et al. 2010 Southeast Region, USA Neighborhood

This captures the large dependence of Rio on the petroleum industry, and attempts to account for the informal labor market related to these industries.

Jobs Created Number of jobs created per month (formal and informal sectors) No Positive RioResiliente Strategy Neighborhood 5.A Adapted to better capture the experiences of the large informal labor

market in Rio.

Housing Capital Percentage homeownership Yes Positive Cutter et al. 2010 Southeast Region, USA Neighborhood Adapted to better capture the experiences of the large informal housing

population in Rio.

Income and Equality GINI Coefficient Yes Positive Cutter et al. 2010 Southeast Region, USA Neighborhood

It may be difficult to measure the GINI coefficient on a neighborhood level, but other measures of inequality are acceptable, such as share of total annual income by income bracket.

Business Size Ratio of large to small businesses (including in the formal and informal economy) Yes Positive Adapted from Cutter et al. 2010 Southeast Region,

USA Neighborhood By including the informal economy in this metric, you better capture the experiences of Rio citizens.

Health Access Number of physicians per 1000 population Yes Positive Adapted from Cutter et al. 2010 Southeast Region, USA Neighborhood

You should consider here any alternative sources of medical care that are not captured by simple physical registration records, i.e. informal clinics, community midwives, or other types of community healers citizens may go to.

Reuse of Solid Waste Volume of solid waste reintroduced in the production chain in metric tons No Positive RioResiliente Strategy Neighborhood 5.B

Participation in Rio + B Number of companies involved in Rio +B. No Positive RioResiliente Strategy Neighborhood 5.C

Sub-Index Variable / Indicator How Measured Disaster Related

Expected Effect on Resilience

Justification Additional Cities Where Used

Recommended Unit of Analysis

RioResiliente Goal Additional Notes on Application to RJ Context

Mobility

Informability - AwarenessPeople's awareness of how easy it is to get information necessary for the journey as measured via an ordinal scale in a survey/scorecard

Yes Positive Adapted from da Silva, 2015; Nicolas et al., 2003; Litman, 2017 Sheffield, UK Neighborhood 3.C

There can be an investigation of people's awareness of the communication channels, for example, how they hear about the smartphone app/Facebook page/other social media pages, how they evaluate the information channels, etc., to better distribute resources that promote these communication channels.

Informability - Boards Density of transit information boards per neighborhood Yes Positive Adapted from da Silva et al, 2015;

Nicolas et al., 2003; Litman, 2017 Sheffield, UK Neighborhood 3.C

Informability - Apps Number of transportation apps for smartphones Yes Positive Adapted from da Silva et al, 2015; Nicolas et al., 2003; Litman, 2017 Sheffield, UK Neighborhood 3.C

Informability - Updating Frequency transportation apps are updated for smartphones Yes Positive Adapted from da Silva et al, 2015;

Nicolas et al., 2003; Litman, 2017 Sheffield, UK Neighborhood 3.C

Reliability Punctuality rate of all transit types Yes Positive da Silva et al, 2015; Nicolas et al. 2003 Sheffield, UK Neighborhood 3.C Rio could also do statistical analysis on buffer time, for example, counting

how many delays occur in 5 min, 10 min, 30 min, and 1 hour time-period.

Reachability - Stations Time required to get to the destination (in real time or time as perceived by users) Yes Negative

Adapted from da Silva et al, 2015; Nicolas et al. 2003; Wells & Raad, 2007

Haia, Netherlands Neighborhood 3.C Original destination (OD) and route information can be obtained from map apps on people's phones.

Reachability - Waiting Waiting time perceived by users Yes NegativeAdapted from da Silva et al, 2015; Nicolas et al. 2003; Wells & Raad, 2007

Haia, Netherlands Neighborhood 3.C

Reachability - Transfers Transfer times per person Yes NegativeAdapted from da Silva et al, 2015; Nicolas et al. 2003; Wells & Raad, 2007

Haia, Netherlands Neighborhood 3.C

Availability Variety of transportation modes to allow enough alternatives Yes Positive

Adapted from da Silva et al, 2015; Nicolas et al. 2003; Wells & Raad, 2007

Los Angeles, USA; Curitiba Neighborhood 3.C

Low-income communities usually have fewer transportation mode alternatives, so the neighborhood level allows a clearer picture about who in the city has access.

Transport Usage - Trips Number of trips per inhabitant per time period Yes PositiveAdapted from da Silva et al, 2015; Nicolas et al. 2003; Wells & Raad, 2007

Los Angeles; Curitiba, Brazil Neighborhood 3.C Could instead be measured in kilometrage.

Transport Usage - People/Trip Number of people transported per trip Yes PositiveAdapted from da Silva et al, 2015; Nicolas et al. 2003; Wells & Raad, 2007

Los Angeles; Curitiba, Brazil Neighborhood 3.C

Transport Usage - People/Time Number of people transported in a certain amount of time Yes Positive

Adapted from da Silva et al, 2015; Nicolas et al. 2003; Wells & Raad, 2007

Los Angeles; Curitiba, Brazil Neighborhood 3.C

Modal Split Proportion of travelers using public transportation in a given time period Yes Positive

Adapted from da Silva et al, 2015; Mobility and Exposure Indicators Guidebook

Los Angeles; Curitiba, Brazil City 3.C

Intermodal Integration - Number Number of intermodal connectors Yes PositiveAdapted from da Silva et al, 2015; Mobility and Exposure Indicators Guidebook

Los Angeles; Curitiba, Brazil City 3.C

As low-income communities have limited access to public transport especially rail services, they might use bus services or other modes to reach the nearest rail station. In this case, it's important to measure the intermodal connectivity/integration to evaluate the equity between neighborhoods.

Intermodal Integration - Capacity Capacity of intermodal connectors Yes PositiveAdapted from da Silva et al, 2015; Mobility and Exposure Indicators Guidebook

Los Angeles; Curitiba, Brazil City 3.C

As low-income communities have limited access to public transport especially rail services, they might use bus services or other modes to reach the nearest rail station. In this case, it's important to measure the intermodal connectivity/integration to evaluate the equity between neighborhoods.

Congestion - Bottlenecks Number and length of bottlenecks Yes NegativeAdapted from da Silva et al, 2015; Mobility and Exposure Indicators Guidebook

Los Angeles; Curitiba, Brazil Neighborhood 3.C

Congestion - Speed Average speed of road vehicles Yes NegativeAdapted from da Silva et al, 2015; Mobility and Exposure Indicators Guidebook

Los Angeles; Curitiba, Brazil Neighborhood 3.C

Delay Total daily/monthly/yearly delay time, delay time = actual trip time - planning trip time Yes Negative

Adapted from da Silva et al, 2015; Mobility and Exposure Indicators Guidebook

Los Angeles; Curitiba, Brazil Neighborhood 3.C

Traffic Volume Number of vehicles across all modes Yes PositiveAdapted from da Silva et al, 2015; Mobility and Exposure Indicators Guidebook

Los Angeles; Curitiba, Brazil Neighborhood 3.C

Transit Accessibility - Vehicle Volume Number of public transport vehicles Yes Positive

Adapted from da Silva et al, 2015; Mobility and Exposure Indicators Guidebook

Los Angeles; Curitiba, Brazil Neighborhood 3.C This metric helps identify the equity of communications regarding access

to public transport.

Transit Accessibility - Length Length of public transport networks in meters Yes PositiveAdapted from da Silva et al, 2015; Mobility and Exposure Indicators Guidebook

Los Angeles; Curitiba, Brazil Neighborhood 3.C

Sub-Index Variable / Indicator How Measured Disaster Related

Expected Effect on Resilience

Justification Additional Cities Where Used

Recommended Unit of Analysis

RioResiliente Goal Additional Notes on Application to RJ Context

Mobility

Transit Accessibility - Density Density of public transport stations per neighborhood Yes Positive

Adapted from da Silva et al, 2015; Nicolas et al., 2003; Litman, 2017; CRI 2017

Los Angeles; Curitiba, Brazil Neighborhood 3.C

Transit Accessibility - Access Area/population coverage per station Yes PositiveAdapted from da Silva et al, 2015; Nicolas et al., 2003; Litman, 2017; CRI 2017

Los Angeles; Curitiba, Brazil Neighborhood 3.C

Affordability People's perception of transit pricing Yes NegativeAdapted from da Silva et al, 2015; Nicolas et al., 2003; Litman, 2017; CRI 2017

Los Angeles; Curitiba, Brazil Neighborhood 3.C

Hazard

Landslide Vulnerability See subindex Yes Negative RioResiliente Strategy Neighborhood See subindex

Flood Vulnerability See subindex Yes NegativeRioResiliente Strategy / San Francisco Community Resilience Indicator System

San Francisco, USA Neighborhood See subindex

Strong Winds See subindex Yes Negative RioResiliente Strategy Neighborhood See subindex

Heat Vulnerability See subindex Yes NegativeRioResiliente Strategy / San Francisco Community Resilience Indicator System

San Francisco, USA Neighborhood See subindex

Sea Level Rise See subindex Yes Negative RioResiliente Strategy Neighborhood See subindexEpidemics and Pandemics See subindex Yes Negative RioResiliente Strategy Neighborhood See subindexDroughts See subindex Yes Negative RioResiliente Strategy Neighborhood See subindexTraffic See subindex Yes Negative RioResiliente Strategy Neighborhood See subindexAccidents with Urban Infrastructure See subindex Yes Negative RioResiliente Strategy Neighborhood See subindex

Agglomeration of People w/ Impact in Normalcy See subindex Yes Negative RioResiliente Strategy Neighborhood See subindex

Criminal Acts in Urban Spaces See subindex Yes Negative RioResiliente Strategy Neighborhood See subindexSanitation See subindex Yes Positive RioResiliente Strategy Neighborhood See subindex

Sub-Index Variable / Indicator How MeasuredExpected Effect on Resilience

JustificationUse for Prevention,Efficiency, and/or

Predictions

Recommended Unit of Analysis

RioResiliente Goal / Section of IDB

ReportAdditional Notes on Application to RJ Context

Technology Innovation

Current Project Opportunities Number of current COR programs and partnerships Positive ISO/IEC, 2015 Prediction/ Prevention Block Operations Center Challenge is the ability for data sharing between different entities(dependent on COR partnership agreements).

New Project Opportunities Number of future COR programs and partnerships Positive ISO/IEC, 2015 Prediction Block Operations Center Challenge is the ability for data sharing between different entities(dependent on COR partnership agreements).

Share of Knowledge-Intensive Enterprises

Proportion of high-tech enterprises/companies (both within the formal and informal gig economy) Positive ISO/IEC, 2015 Efficiency City Operations Center

Keeping track of high-tech enterprises can help the city identify private sectors that they can collaborate with, especially for reducing their workload regarding data cleaning and analysis

TechnologyInfrastructure

Access to Real-Time Information Percentage of traffic lights connected to real-time traffic management system Positive Cohen, 2014 Efficiency City 3C /

Monitoring and Control

In addition to increasing the efficiency of traffic management, network-connected infrastructure can also be helpful for the efficient maintenance and monitoring of the city infrastructure

Wifi Coverage - Normal Days Number of Wifi hotspots per sq.km. (comparing the formal and informal neighborhood) on normal days Positive Cohen, 2014 Prevention Block Monitoring and Control

Having the information on Wifi coverage within the city can help inform COR of the infrastructure capacity they could use for monitoring and prevention on a normal day

Wifi Coverage - Post-Disaster Number of Wifi hotspots per sq.km. (comparing the formal and informal neighborhood) post-disaster Positive Cohen, 2014 Prevention Block Monitoring and Control

Having the information on Wifi coverage within the city can help inform COR of the infrastructure capacity they could deploy during and after a disaster strikes

Sensor Coverage Number of infrastructure components with installed sensors Positive Cohen, 2014 Prevention Block 3C

In addition to increasing monitoring capacity, network-connected infrastructure can also be helpful for the efficient maintenance and monitoring of the city infrastructure

Share of Network Infrastructure in Total Investment

Amount of urban infrastructure investments in BRL (for both formal and informal neighborhood) Positive ISO/IEC, 2015 Prevention Block Monitoring and Control

Up to COR to define both 'urban' and 'infrastructure' such as which of their investments are contributing towards 'smart city' infrastructures and in which part of the city

Recovery TimesAverage time used for recovering from telecommunication congestion per resident Positive ISO/IEC, 2015 Efficiency Neighborhood Operations Center Rio should build a recovery time measurement instrument

Governance

Percentage of Open Government Information

Refer to the percentage of the government unclassified documents open on public networks (citizen, journalist, communities)

Positive ISO/IEC, 2015 Prediction City Smart Services Encouraging an open data infrastructure within the City will increase transparency

Government Sector Electronic Devices

Number of electronic devices used in public sector(computers, cell phones, etc...) Positive Batagan, 2011 Efficiency City Monitoring and Control

Operations CenterGovernment Sector Internet Connectivity

Percentage of government institutions with Internet connectivity Positive Batagan, 2011 Efficiency City Monitoring and Control

Operations Center Data integration will require an Internet-connected infrastructure for the city

System Construction Number of new systems, hardware being constructed/added to COR's capabilities Positive Hara et al., 2016 Prevention City Operations Center

Field SystemsThis variable will allow COR to justify the added value of new investment on infrastructure

System Cost Performance Operation cost of ICT systems Positive Hara et al., 2016 Efficiency Neighborhood Monitoring and ControlOperations Center

Knowing the BRL spent for operation and maintenance of the ICT system can help COR identify the best use of resources, especially if they can compare it to another identical system in another city such as Madrid

Safety and Security

City Video Surveillance Penetration Number of video cameras per capita Positive ISO/IEC, 2015 Prevention Block Field Systems Video camera locations (diffuse or concentrated in different parts of Rio)

City Video Surveillance Penetration Number of video cameras per informal community Positive ISO/IEC, 2015 Prevention Block Field Systems Video camera locations (diffuse or concentrated in different informal communities)

Accident RatioRatio of all kinds of accidents predicted by ICT measures in a period of time including aspects such as victims, damaged projects, etc.

Positive Hara et al., 2016 Prediction Block3C / Operations CenterField Systems

Knowing the ratio of incidents COR prevents, COR can better quantify how much it has saved the city in terms of recovery and relief operations

ICT Penetration for Disaster Prevention - Formal

Number of sensing terminals in disaster-prone areas per formal community Positive Hara et al., 2016 Prediction Neighborhood Operations Center This variable will allow COR to justify the prevention measurement taken

for the vulnerable communityICT Penetration for Disaster Prevention - Informal

Number of sensing terminals in disaster-prone areas in informal community Positive ISO/IEC, 2015 Prevention/Prediction Neighborhood Operations Center This variable will allow COR to justify the prevention measurement taken

for the vulnerable community

Disaster Alert Publication Rate The publication rate of timely alerts for natural disasters (storms, flooding, etc…) Positive ISO/IEC, 2015 Efficiency Neighborhood 2C / Smart Services

Operations CenterPublication rate can inform COR of the efficiency and accuracy of the current system

Decrease in Evacuation Time Time saved with using COR (hours, minutes. etc...) especially in dense informal neighborhoods Positive Hara et al., 2016 Prediction/Efficiency Block 2C / Smart Services Depends on different disaster types and steps needed to evacuate people

to safety during disaster events

Information Distribution Post-Disaster - Congestion Prevention

Preventable incidents of network congestion (via satellite phones or wifi network antenna) Positive GSMA, 2013 Efficiency Block 2C / Smart Services

COR must review if it is capable of alternative communication methods. It should predict/determine network congestion areas and plan/deploy network congestion solutions accordingly

Information Distribution Post-Disaster - Incident Communication

Post-disaster Incidents communicated via email/internet versus phone call to public Positive GSMA, 2013 Prevention City 2C / Smart Services

User Capacity

Smartphone Penetration Percentage of residents with smartphone access Positive Cohen, 2014 Prevention/ Efficiency Neighborhood Smart Services COR has to know their outreach capacity, especially the smartphone where most engagement happens

Cell Phone Connections - City Number of cell phone connections per 100,000 people Positive Cohen, 2014 Prevention/ Efficiency City Smart ServicesMonitoring and Control

In addition to the smartphone user, knowing the overall number of people with mobile phones is also important as one of the main outlets of COR messaging is through SMS

Cell Phone Connections - Informal Number of cell phone connections per 100,000 people in informal neighborhoods Positive Cohen, 2014 Prevention/ Efficiency Neighborhood Smart Services

Monitoring and Control

Knowing the number of people with mobile phones in informal neighborhood is important because most of the people living there do not necessarily have access to data even if they have a smartphone

Number of Users Percentage of users inputting information into COR Positive Cohen, 2014 Efficiency Neighborhood Monitoring and ControlOperations Center

Number of users inputting information can inform COR of the level of engagement and number of active users

Online Civic Engagement How often residents send crowdsourced information to COR via civic apps Positive ISO/IEC, 2015 Efficiency Neighborhood Smart Services Number of users inputting information can inform COR of the level of

engagement and how active users are within the platform

Public Convenience and Comfort

Satisfaction Level Public satisfaction level with COR network-based services from a 1-5 scale (1 is low satisfaction) Positive ISO/IEC, 2015 Efficiency City Smart Services

Operations CenterOne way for COR to evaluate the performance of their network-based service is by using a rating system

Convenience of Government Services

Public rating of the convenience of public services from a 1-5 scale (1 is low satisfaction) Positive ISO/IEC, 2015 Efficiency City Smart Services

Operations CenterThe City can use a rating system to gain insight on the quality of their service delivery

Convenience of Smart Traffic Information Administration and Service

Public rating of the convenience of obtaining traffic information via smart terminals from a 1-5 scale (1 is low satisfaction)

Positive ISO/IEC, 2015 Efficiency City Smart ServicesOperations Center

Sub-Index Variable / Indicator How MeasuredExpected Effect on Resilience

JustificationUse for Prevention,Efficiency, and/or

Predictions

Recommended Unit of Analysis

RioResiliente Goal / Section of IDB

ReportAdditional Notes on Application to RJ Context

Social Media

Breadth - Community Size Number of social media followers per platform Positive Herman, 2013 Prevention / Efficiency Neighborhood Smart ServicesOperations Center

If possible, all social media indicators should be measured on a neighborhood level if any sort of geolocation information is available through the platform. In terms of Community Size, examples from some platforms include: Facebook fans - number of people who like your page, or number of unique people who have seen any conect associated with the page). Twitter followers - number of accounts subscribed to your Twitter feed.

Breadth - Community Growth Difference between the number of current users from users in the previous months per platform Positive Herman, 2013 Prevention / Efficiency Neighborhood Smart Services

Operations CenterNeed to also potentially adjust for higher number of followers after an emergency

Depth - Conversions Number of desired actions/click-throughs Positive Herman, 2013 Efficiency Neighborhood Smart ServicesOperations Center

Depth - Views As measured in number of unique number of views Positive Herman, 2013 Efficiency Neighborhood Smart ServicesOperations Center

Depth - Minutes Watched Measured in number of minutes watched Positive Herman, 2013 Efficiency Neighborhood Smart ServicesOperations Center

Need to consider which city zones have low access internet access, which will affect streaming ability and speeds that may reduce the minutes watched in some communities

Engagement Responsiveness - Questioned Answered

Measured by the number of questions answered through social media Positive Herman, 2013 Efficiency Neighborhood Smart Services

Operations CenterEngagement Responsiveness - Response Time

Average time it takes for the City to respond to a social media request Negative Herman, 2013 Efficiency Neighborhood Smart Services

Operations CenterEngagement Volume - Total Mentions

Number of total mentions, likes and comments per platforms Positive Herman, 2013 Efficiency Neighborhood Smart Services

Operations CenterEngagement Volume - Unique Mentions Number of unique mentions per platform Positive Herman, 2013 Efficiency Neighborhood Smart Services

Operations Center

Loyalty - Regular Visitors Percentage of users who have multiple visits Positive Herman, 2013 Efficiency Neighborhood Smart ServicesOperations Center

Customer Experience - Sentiment Percentage of positive comments about specific content as determined by a textual analysis of positive, negative or neutral comments

Positive Herman, 2013 Efficiency Neighborhood Smart ServicesOperations Center

Customer Experience - Top Keywords

Percentage of positive comments about your overall social media content as determined by a textual analysis of positive, negative or neutral comments

Positive Herman, 2013 Efficiency Neighborhood Smart ServicesOperations Center

Customer Experience - Top Hashtags

Percentage of positive hashtags about your overall social media content as determined by a textual analysis of positive, negative or neutral comments

Positive Herman, 2013 Efficiency Neighborhood Smart ServicesOperations Center

Feedback - Satisfaction As measured through a survey on the social media platform from a 1-5 scale (1 is low satisfaction) Positive Herman, 2013 Efficiency Neighborhood Smart Services

Operations Center

Feedback - Diversity of Users

The number of demographic categories represented amongst users, as measured through nominal categories users can fill in capturing demographic data such as ethnicity, age, socioeconomic status, etc.

Positive Herman, 2013 Efficiency Neighborhood Smart ServicesOperations Center

It would be beneficial to ask for participants Codigo de Enderecamento Postal (CEP) to determine their location

Sub-Index Variable / Indicator How MeasuredExpected Effect on Resilience

Justification Additional Cities Where Used

Recommended Unit of Analysis RioResiliente Goal Additional Notes on Application to RJ Context

Intense Rains

Landslide Vulnerability Percentage of area in landslide susceptibility map high risk zone based on soil tests Negative RioResiliente Strategy /

GeoRio data point Neighborhood

This is data already captured by GeoRio, but by reducing the unit of analysis, it will better show which portions of a single neighborhood are vulnerable to landslides, rather than the city overall, to better prioritize resilience efforts and focus on communities which have a high percentage of vulnerable land.

Flood Vulnerability Percentage of the land‐area in the 100‐year storm floodplain Negative

RioResiliente Strategy / San Francisco Community Resilience Indicator System

San Francisco, USA Neighborhood

This will better show which portions of a single neighborhood are vulnerable to flooding, rather than the city overall, to better prioritize resilience efforts and focus on communities which have a high chance of flooding.

Impervious Surfaces Percentage of surfaces that are impervious in terms of area Negative

San Francisco Community Resilience Indicator System

San Francisco, USA Block 3.B

Impervious surfaces increase the possibility of and volume of flooding, which is a critical metric to have on even the neighborhood block level, given that impervious surfaces combined with steep slopes will exacerbate the effects of floodings. For example, a house at the bottom of a steep slope is vulnerable to a higher volume of flooding than the top of the slope.

Precipitation Centimeters Negative AlertaRio data point BlockHumidity Percentage Negative AlertaRio data point BlockTemperature Degrees in Celsius Negative AlertaRio data point BlockAtmospheric Pressure hPa Negative AlertaRio data point BlockWind Direction Degrees Negative AlertaRio data point BlockWind Speed Km/hour Negative AlertaRio data point BlockRiver Levels Centimeters Negative RioAguas data point Neighborhood

Geological Studies Availability of geological risk assessment maps Positive Site Visits NeighborhoodThis is to deal with potential fissures within mountains and hills that would not be captured by soil tests but still can still lead to landslides.

Floodplain Population Number of people living in the floodplain (population/sq.km.) Negative Adapted from Tucci, 2002 Neighborhood

This attempts to capture not just the area of land affected but also the number of people living in that area. Given low-income and informal neighborhoods are more densely packed, this will better capture how many individuals are affected.

Landslide Zone Population Number of people living in landslide zone (population/sq.km.) Negative Adapted from Tucci, 2002 Neighborhood

This attempts to capture not just the area of land affected but also the number of people living in that area. Given low-income and informal neighborhoods are more densely packed, this will better capture how many individuals are affected.

Flood Frequency Number of flood incidents per year Negative Tucci, 2002 Curitiba, Brazil Neighborhood

Community Perception Percentage of community residents who identify "intense rains" as an important issue Positive Jamieson, 2016 Neighborhood

When individuals believe the specific vulnerability is a problem for their community, they are more likely to take steps to prepare for its effects including supporting policy and institutional resilience efforts.

Saturation of Road Infrastructure

Greenhouse Gas Emission - Total

Citywide GHG emissions level (tons of GHG produced in a certain period) Negative Zhu et al, 2015 Beijing, China City 3.C

Beijing bans high-emission vehicles in the anti-haze movement; Rio can adjust the standard to judge whether the vehicle emission is high enough to ban

Greenhouse Gas Emission - Vehicles

Percentage of high-emission vehicles among all metropolitan vehicles Negative Zhu et al, 2015 Beijing, China City

Vehicle Emissions Impact - Air Quality

Hourly pollutant concentrations at a single point. Pollutants analysed include ozone, nitrogen oxides, sulphur dioxide, carbon monoxide and particulates.

Negative Wang et al, 2014 Beijing, China Neighborhood 3.C

Vehicle Emissions Impact - Visibility How far in meters people can see in the air Positive Wang et al, 2014 Beijing, China Neighborhood 3.C

Beijing uses how many meters can be seen to measure air quality; however, Rio usually has heavy smog which can affect the visibility test result (smog versus haze)

Vehicle Emissions Impact - Noise Density of vehicles in the measured area Negative Zannin, et al 2002 Curitiba, Brazil Neighborhood 3.C

Traffic Security - Fatalities Traffic accident fatalities (across all transportation modes) Negative

Beijing Public Security Traffic Management Yearbook 2009

Beijing, China Neighborhood 3.C Pedestrian fatality and injury rate can be considered together with walkability for transportation planning

Traffic Security - Injuries Traffic accident injury rate (across all transportation modes) Negative

Beijing Public Security Traffic Management Yearbook 2009

Beijing, China Neighborhood 3.C Pedestrian fatality and injury rate can be considered together with walkability for transportation planning

Walkability - Length Pedestrian density in terms of walkway length (how many meters of walkways in a 400m. radius circle) Positive Kansas City Walkability

Plan Kansas City, USA Neighborhood 3.C

Pedestrian fatality and injury rate can be considered together with walkability for transportation planning. In Rio's context, the measurement could also include pedestrian width, connectivity between intersections, and quality of pavements.

Walkability - Population Ratio of population with access to diverse-use places like groceries Positive Rattan et al, 2012 Halton, Canada Neighborhood 3.C Pedestrian fatality and injury rate can be considered together with

walkability for transportation planning

Road Infrastructure Quality Percentage of well-maintained road segments Positive Adapted from Burningham and Stankevich, 2005 Lima, Peru Neighborhood 3.C Rio could also track the time and efficiency of the road

maintenance projectsRoad Infrastructure Quality - Construction Projects Number of road construction/maintenance projects Positive Adapted from Burningham

and Stankevich, 2005 Lima, Peru Neighborhood 3.C Rio could also track the time and efficiency of the road maintenance projects

Permeability of Road Infrastructure

Amount of rainfall diverted from estuarine systems in liters of water per sq.m. of road Positive

Adapted from The Embassy of the Kingdom of Netherlands, 2016

Beijing, China Neighborhood

This captures the ability of road infrastructure to react to heavy rains (permeate/absorb/recycle rainwater), and is related to the concept of a "sponge city" which was implemented in two series of pilot cities in China. The key is to combine the rainfall treatment system with the road system. What's most important to Rio is to incorporate the idea of becoming a "sponge city" in order to have infrastructure systems that are able to react to sudden rains and floods.

Sub-Index Variable / Indicator How MeasuredExpected Effect on Resilience

Justification Additional Cities Where Used

Recommended Unit of Analysis RioResiliente Goal Additional Notes on Application to RJ Context

Saturation of Road Infrastructure

Commuting Time Average commuting time per person/transport mode/trip Negative RioResiliente Strategy Rome, Italy Neighborhood 3.C Rio can use this metric to track the efficiency of different modes for

further transportation planning resource distribution.

Economic LossTotal economic loss caused by maintenance, repair, and construction of transportation systems to prevent and react to natural disasters

Negative RioResiliente Strategy Beijing, China City 3.C In the context of Rio, economic loss can be calculated by temporal episodes or disaster type.

Community Perception People's satisfaction with the whole transportation system Positive Vita, & Marolda, 2008;

Jamieson, 2016

EU RISER Program (Roadside Infrastructure for Safer Roads)

Neighborhood 3.C

When individuals believe the specific vulnerability is a problem for their community, they are more likely to take steps to prepare for its effects including supporting policy and institutional resilience efforts.

Additional Shocks and Stresses*Strong Winds To be determined RioResiliente Strategy

Heat Vulnerability To be determined RioResiliente StrategySea Level Rise To be determined RioResiliente Strategy

Epidemics and Pandemics To be determined RioResiliente StrategyDroughts To be determined RioResiliente Strategy

Accidents with Urban Infrastructure To be determined RioResiliente StrategyAgglomeration of People with Impact on

Normalcy To be determined RioResiliente Strategy

Criminal Acts in Urban Spaces To be determined RioResiliente StrategySanitation To be determined RioResiliente Strategy

* The same process should be carried out in concert with academic partners for the additional nine shocks and chronic stresses identified in the RioResiliente Strategy.