Chapter 2 - Part 2

Chapter 2.Characterising the Next Generation of

MobileApplications Through a Privacy-Aware

Geographic Knowledge Discovery Process- M. Wachowicz, A. Ligtenberg, C. Renso, and S.

G¨urses

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Index2.5 The Multi-Tier Ontological Framework

2.5.1 Tier 0: The Reality Space2.5.2 Tier 1: The Positioning Space2.5.3 Tier 2: The Geographic Space2.5.3 Tier 3: The Social Space2.5.4 Tier 4: The Cognitive Space

2.6 Future Application Domains for a Privacy-Aware GKDD Process2.6.1 Transport Management: The Integration of Multimodal Choices

2.6.1.1 Tier 0: The Reality Space2.6.1.2 Tier 1: The Positioning Space2.6.1.3 Tier 2: The Geographic Space2.6.1.4 Tier 3: The Social Space

2.6.2 Spatial Planning: The Adaptation of Space to Human Behaviour2.6.2.1 Tier 0: The Reality Space2.6.2.2 Tier 1: The Positioning Space2.6.2.3 Tier 2: The Geographic Space2.6.2.4 Tier 3: The Social Space

2.6.3 Marketing: The Shift Towards Movement-Aware Marketing2.6.3.1 Tier 0: The Reality Space2.6.3.2 Tier 1: The Positioning Space2.6.3.3 Tier 2: The Geographic Space2.6.3.4 Tier 3: The Social Space

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2.5 The Multi-Tier Ontological Frame-work

• A GKDD process constructed from a multi-tier ontological perspective aims to integrate different reasoning tasks in a unified system by mapping the complex relationship be-tween movement metaphors and patterns. – This will lead to uncovering new and innovative hypothesis of distribu-

tions, patterns and structures across very large databases. – Therefore, these metaphors will not rely on similar reasoning back-

grounds but will be derived from the integration of different inference modes (i.e. abductive, inductive, and deductive).

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KnownMetaphors

Observa-tions

Context

Model

DiscoveredMetaphor

Sample

Relation

Discovery

Insight

Confront

Tier 0 : Reality SpaceA-priori Knowledge

Tier 1 : Positioning SpaceDeductive Reasoning (What, Where, When)

Tier 2 : Geographic SpaceDeductive Reasoning (How, What for)

Tier 3 : Social SpaceInductive Reasoning (What if)

Tier 4 : Cognitive SpaceCognitive Tacit KnowledgeAbductive Reasoning (Why)

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2.5.1 Tier 0: The Reality Space

• Tier 0 of the ontology represents the ‘reality space’, which recognises the existence of a known world as a four-dimen-sional continuous field in space and time. – Several known movement metaphors are currently being used, includ-

ing the movement-as-journey metaphor and the movement-as-activity

movement-as-journey• one or two journeys on a day are most common• over three quarters of all(75%) journeys are usually a single-stop tour• while combining more than three stops in a journey is very rare.

movement-as-activity• More than 50% of all out-of-home activities take more than an hour and over

30% take even more than 2h [3].

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2.5.1 Tier 0: The Reality Space

• In tier 0, it is important to establish whether there are any privacy concerns from any of the sensor carriers and the experts of an application domain.– define a level of privacy according to who are the sensor carriers from

whom data will be collected and who are the involved experts who will define the purposes of collecting these data.

– Once the stakeholders are identified in tier 0, it is also necessary to identify what their privacy requirements are, which could there be stated in terms of hierarchical levels of privacy.

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2.5.2 Tier 1: The Positioning Space

Observations• measurement values at every point in space and time, • based on some measurement scale, which may be quantitative or qualitative. • always marked by some degree of uncertainty, which depends on the type of

sensors being used for collecting the location and movement information of mobile entities, such as X,Y,Z coordinates, speed and time.

• They can be navigation sensors (e.g. GPS, INS, MEMS sensors, digital com-passes, etc.), remote sensing sensors (e.g. frame-based cameras, thermal cameras, laser scanners, etc.) and wireless technologies.

KnownMetaphors

Observa-tions

Sample



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• We do not have a trajectory representation of these points yet.

• However, it is possible to distinguish the observations ac-cording to four point representations.• Stop : A cluster of points that represent stops with a very short duration of

some minutes due to traffic light or stop signs. • Stop over : A cluster of points that represent a change of speed. For example,

a road accident. • Short stay : A cluster of points that represent stays with a short duration of

some hours due to an activity such as working, shopping or leisure. • Long stay : As cluster of points that represent stays with a long duration of

several hours that will correspond to the sensor device being switch off or be-ing at home.

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• The reasoning task consists of allowing one to infer a con-sequence from a set of point patterns. – The consequences are drawn from these point patterns down to a spe-

cific metaphor such as, for example, the movement-as-urban forms metaphor.

(1) Ring network in a concentric city: concentric pattern (2) Radial network in a lob city: radial pattern(3) Linear poly-nuclear city: linear concentric pattern(4) Concentric poly-nuclear city: circular concentric pattern (5) Linear network in a linear city: linear pattern (6) Grid city: square concentric pattern

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• In terms of privacy, – the main issue is to make sure that the granularity of data collection is

in accordance with the privacy requirements of the sensor carriers. – The domain experts can also make sure that the granularity of position-

ing data set is appropriate for the needs of the application domain and it complies with the privacy requirements of the different sensor carri-ers.

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2.5.3 Tier 2: The Geographic Space

• From the movement metaphors and representations already de-fined in the previous tier 1, a trajectory is defined in this tier as any polyline between stops, stop overs, short stays and/or long stays.

• Moreover, in this tier is where the privacy requirements of the sensor carriers need to be implemented using security con-straints. – If there are sensor carriers who want their trajectories to be unobservable or

who want to remain anonymous, then the necessary steps need to be taken here by applying different trajectory privacy-preserving methods such as cloaking and mixes.

Observa-tions

Context

Relation



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• Cloaking

• Mix

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• Currently, the main metaphor being used at this ontological level is accessibility, which can be obtained by the calcula-tion of trajectory distances (lengths).

• However, the GKDD process is entirely propositional and different movement metaphors need to be taken under consideration at this ontological level. – the metaphors of movement-as-urban form and movement-as-accessi-

bility can be used to deduce the consequences of the linear patterns,• from the trajectories based on the generalization of the trajectories • using the transportation networks such as the types of streets in an urban

area.

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• Accessibility is constrained by urban forms such as the transportation network. – the tree street patterns usually impede the movement of people on

reaching a destination. – grid street patterns facilitate the fast reaching to a particular destina-

tion.

• A GKDD process might provide the data mining query mechanism necessary to discover an anomaly in the trajec-tories

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2.5.4 Tier 3: The Social Space

• The tier 3 encompasses the model that underlies our daily trajectories and their fundamental relations with human ac-tivities. – transportation modalities (e.g. car or public transport), – commuting time or distance, – spatial distribution of jobs and housing locations, – total vehicle miles travelled, – average trip lengths and congestion on links and intersections.– from socio-economic statistics, such as income and education

of a neighbourhood.

Context

Model

Discovery



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• It is important to realize that a trajectory takes place in a social-spatial system.

• The main metaphor used at this tier level is movement-as-activity. – The spatial system and the social system are strongly intertwined and

should not be analyzed separately.

social system• consists of individuals, groups and organizations that maintain relations through

intentional (cooperative) activities,• based upon a more or less common set of rules, norms and values, and acts

within the boundaries of the institutions that are derived from it [13]

spatial system• is composed of biotic and abiotic components, processes that alter these com-

ponents and relations between them.

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• In this tier, it requires that some sort of target must already have been identified, and the task becomes one of uncover-ing ‘what if’ scenarios to explain the trajectory patterns within a social context.– For example, instead of finding the best location for a supermarket

based on the proximity of objects on the landscape, the problem be-comes about finding the best location based on the patterns of the tra-jectories of people, which in turn, suggest that the human activity on a landscape is potentially more complex and probabilistic.

• Some examples are given below: – Discover patterns that explain the occurrence of a certain activity (e.g.

shopping, recreation) – Discover the dependencies between different characteristics of activi-

ties – Discover the activities subsets and time periods with the corresponding

patterns – Detect the occurrence of an unexpected activity

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• The data miner and the domain expert need to make sure that exact rules that contain the complete data population do not breach any of the ‘group privacy’ requirements.

• there may be privacy requirements in the following form: – If the size of an identified group is less than 10% of the complete popu-

lation, then a sensor carrier wants to be unobservable, or it should not be inferred that the sensor carrier belong to this group.

– If an unexpected activity(example number 4 above) is detected, and this contains information about clearly identifiable locations, small set of trajectories or small groups of people, then this information should either not be released or only accessible to trusted parties.

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2.5.5 Tier 4: The Cognitive Space

• the goal of a geographic knowledge discovery process is to gain knowledge through abductive reasoning that can function in the absence of pre-determined hypotheses, training exam-ples or rules

• it is important to point out the difference between tacit and implicit knowledge. – implicit knowledge is something experts might know, but not wish to ex-

press – tacit knowledge is something that experts know but cannot express, it is

personal, difficult to convey, and which does not easily express itself in the formality of language.

Model

DiscoveredMetaphor

Insight



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KnownMetaphors

Observa-tions

Context

Model

DiscoveredMetaphor

Sample

Relation

Discovery

Insight

Confront






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2.6 Future Application Domains for a Privacy-Aware GKDD Process

• Three application domains have been selected to illustrate the expected innovations on applications in,– transport management– spatial planning – marketing

http://www.microlise-america.com/index.php/portfolio/transport-management-centrehttp://www.flickr.com/photos/38702466@N05/3563816815/http://webbusiness2go.com.au/location-based-marketing/

http://www.microlise-america.com/index.php/portfolio/transport-management-centre

http://www.microlise-america.com/index.php/portfolio/transport-management-centre

http://www.flickr.com/photos/38702466@N05/3563816815/

http://www.flickr.com/photos/38702466@N05/3563816815/

http://webbusiness2go.com.au/location-based-marketing/

http://webbusiness2go.com.au/location-based-marketing/

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2.6.1 Transport Management: The Integration of Multimodal Choices

• Transport or transportation refers to the movement of peo-ple and goods from one place to another.

• Transport management is aimed at solving the problems between infrastructure (e.g. transport networks) and opera-tions (e.g. road traffic control).

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KnownMetaphors

Observa-tions

Sample

Tier 0 : Reality Space• travellers and planners with multimodal information about their trajectory

behaviour.

Tier 1 : Positioning Space• Most common metaphors : movement-as-accessibility• that defines how people move from one location to another as pedestri-

ans, or taking cars, bikes or public transportation.• For a geographic knowledge discovery process, this might imply the de-

ductive search as one of the following examples: 1. Discover how a set of point patterns evolves from time t1 to time t2, in

terms of a specific mode of transportation 2. Discover an observation window (spatial and temporal extends) where

point patterns reveal a change of mode of transportation 3. Discover the rules that explain a spatial distribution of a set of point

patterns at a given time in terms of a specific mode of transportation • The domain experts need to consider if any of these discovered pat-

terns are in conflict with the privacy or security requirements of any of the sensor carriers.

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Context

Model

Relation

Discovery

Insight

Tier 2 : Geographic Space• patterns of moving people and their respective trajectories will have an

impact on understanding the relationship between modality choices and trajectory patterns.

• the knowledge of such trajectory patterns will play an important role in studying the route conditions from effects such as hazards, noise, traffic jams and visual pollution.

• This kind of information would allow the experts to check if information can be inferred from the trajectory representation that may breach the privacy requirements of any of the sensor carriers.

Tier 3 : Social Space• Some examples are given below: 1. Discover accessibility patterns that explain the occurrence of shopping

activity with its corresponding transportation modality 2. Discover the dependencies between working and leisure activities ac-

cording to a specific transportation modality 3. Detect the occurrence of an unexpected activity • the data miners and domain experts need to observe the classifications

that they infer and check to see whether the ‘category anonymisation’ requirements of the different sensor carriers are breached.

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2.6.2 Spatial Planning: The Adaptation of Space to Human Behavior

• Spatial planning is aimed to change the organisation of a geographic environment to meet the demands of society. – Demands of society continuously change as the result of change in the

society and also due to change in the geographic environment itself.– As space becomes a limited resource the geographic environment is

expected to fulfil multiple functions [54].

• In spatial planning, – location-allocation representations and methods have been developed

when positioning data sets were scarce and difficult to obtain, and models were deterministic or entirely predictable.

– In principle, mobile technologies made it possible to gather very large data sets containing movement information from mobile devices over time.

– This has opened the opportunity to deal with the location-allocation problems from a people’s perspective in spatial planning.

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KnownMetaphors

Observa-tions

Sample

Tier 0 : Reality Space• land use could become the activity metaphor based on the movement of

people, rather than the location of its features. • Knowledge of the movement of people in these types of areas is required

for the situating of shops, shop-types and checkpoints. • More over the dimensioning of pathways, gateways and emergency evac-

uation routes might benefit from additional knowledge about the spatial temporal dynamics of moving crowds.

Tier 1 : Positioning Space• The above mentioned examples of applications in spatial planning would

benefit from the gathering of positioning data of moving people on a land-scape into a trajectory data warehouse.

• This type of data neither is commonly used in the process of designing spaces nor is it commonly available.

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Context

Model

Relation

Discovery

Insight

Tier 2 : Geographic Space• The geographic discovery process needs to be essentially targeted to find-

ing linear patterns of trajectories that can be understood by a planner and designer.

• The main metaphor at this tier is movement-as-urban form. • certain land use type might enable common activities to occur close to a

specific place (e.g. housing and food shopping), as well as places with higher density development closer to transportation lines and hubs. Poor land use concentrates activities (such as jobs) far from other destinations (such as housing and shopping).

Tier 3 : Social Space• Multifunctional land use can be defined as combining various socio-eco-

nomic activities in the same area.• The challenging factor is to provide ample opportunities for recreational

activities while preserving and developing nature. • Knowledge about the patterns of movement of visitors of nature areas

and the type of activities might improve the harmonisation of multifunc-tional use of nature areas.

• Individuals may not want their leisure activities to be so clearly identifi-able.

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2.6.3 Marketing: The Shift Towards Movement-Aware Market-

ing • Currently marketing is mostly done based on customers’

profile, which, normally, is statically defined. • Traditionally, the success of marketing depends on what is

called the marketing mix of four P’s: product, price, promo-tion and placement. – This rather traditional view on marketing has been criticised, since its

main focus is on a company or marketer rather than the consumer.

• Geo-marketing implies the use of GIS to add location infor-mation into the marketing mix. – Based on spatial analysis, additional knowledge and insight might be

gained about, for example, the spatial distribution of income and de-mographic composition of districts.

• The main metaphor is movement-as-personalisation. – many people to be spammed by location-based advertisements, gen-

erated by relative dumb LBS, can be alleviated by providing more intel-ligent information based on movement behaviour.

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ing Known

Metaphors

Observa-tions

Sample

Tier 0 : Reality Space• Using LBS, marketers can pinpoint their marketing mix and enhance their

communication with potential customers based on their exact location and time.

• movement-based services (MBS) • LBS only provide the context from the users, and the environment (who is

where at time t). MBS have the potential to add to this, knowledge about what he/she did, how he/she did it and with whom.

Tier 1 : Positioning Space• LBS usually describe only the location in space, a caller id and a time

stamp. • MBS, information about the followed tracks, the movement characteris-

tics (speed, acceleration, periodicity in movements, etc.) need to be added and stored.

• MBS typically require the maintenance and storage of data to be able to infer patterns out of it.

• As data are required and requesting of the movements of individual peo-ple preserving privacy is an important requirement.

• in marketing-based application, the control of the right should be part of the decision making about what part of the reality space should be sam-pled and registered.

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ing

Context

Model

Relation

Discovery

Insight

Tier 2 : Geographic Space• marketing-related behaviour and movement behaviour. 1. the consent model is based on informing or assisting users with informa-

tion or services based on authorisation given by them. 2. users receive targeted information based on their movement behaviour,

location, time and the behaviour of others• privacy in such an application depends on which of the above location in-

formation the sensor carrier is unwilling to have analysed.

Tier 3 : Social Space• The discovery of geographic knowledge related to privacy aware market-

ing is mainly targeted to finding groups that show similar behaviour and to determine if this behaviour is interesting, given a certain marketing goal.

1. Discover the general patterns that explain the behaviour of certain groups of people given a marketing perspective.

2. Discover the dependencies between movement behaviour and the ef-fects of personalised movement-aware marketing.

3. Discover the type of information appreciated by people when they are moving at a certain time, modality and location.

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Chapter 2 - Part 2