Social Science: Cyberinfrastructure and Supercomputing Potential and Needs

Scott Poole, Noshir Contractor, Kevin Franklin

• HASS Computational Science will be a breakthrough area in the next ten years

• Illinois—I-CHASS and NCSA—positioned to be leaders

• I-CHASS has $4 million in funded projects related to Social Sciences, including one of the first CDIs awarded to a social scientific project

NCSA Strategic Planning Presentation (April 20,2010)

Studies of 19.9 million research articles over 5 decades as recorded in the Web of Science database, and an additional 2.1 million patent records from 1975-2005 found three important facts.

1. For virtually all fields, research is increasingly done in teams

2. Teams typically produce more highly cited research than individuals do (accounting for self-citations), and this team advantage is increasing over time.

3. .Teams now produce the exceptionally high impact research, even where that distinction was once the domain of solo authors.

Sources: Wuchty, Jones, and Uzzi, 2007a, 2007b

Move to Team Science

The trend toward virtual communities was not driven by a growth in teamwork by scientists working with other co-located scientists. Using the Web of Science database to analyze the collaboration arrangements of over 4,000,000 papers over a 30 year period, they found that:

1.Team science is increasingly composed of co-authors located at different universities.

2.These “virtual communities of scholars” produce higher impact work than comparable co-located teams or solo scientists.

3.This change is true for all fields and team sizes, as well as for research done at elite universities

Source: Jones, Wuchty, Uzzi, 2008

Move to Virtual Team Science

The Hubble telescope: $2.5 billion

Source: David Lazer

CERN particle accelerator: $1 billion/year

Source: David Lazer

The Web: priceless*

Source: David Lazer

* Apologies to MasterCard

Text Mining Web crawlingWeb of Science Citation

CATPAC

UBERLINK

Digital Harvesting of Relational Metadata

CI-KNOW Analyses and Visualizations

Core Research Social Drivers for

Creating & Sustaining Communities

Business Applications

PackEdge Community of Practice (P&G)

Vodafone-Ericsson “Club” for virtual supply chain management (Vodafone)

Kraft Product Design Teams

Societal Justice Applications

Cultural & Networks AssetsIn Immigrant Communities (Rockefeller Program on Culture & Creativity)

Digital Media and Learning(MacArthur Foundation)

Entertainment Applications

World of Warcraft (NSF)

Everquest (NSF, ARI, Sony Online Entertainment)

Second Life (Linden Labs)

Science Applications

VOSS: Virtual Organizations as Socio-technical Systems (NSF)

Onco-Fertility Consortium (NIH)

CP2R: Collaboration for Preparedness,Response & Recovery (NSF)

TSEEN: Tobacco Surveillance Evaluation & Epidemiology Network (NSF, NIH, CDC)

Projects Investigating Social Drivers for Communities

SONIC

Advancing the Science of Networks in Communities

Grand Challenge: Understanding & Enabling Networks in Society

• ICT, Information, and Social Networks—interactions and inferences

• A Key Problem: Very large networks require petascale computing

• Examples:• Virtual Worlds Observatory Project• Network Science Collaborative Technology Alliance• Coupled Models of Diffusion and Individual Behavior Over

Extremely Large Social networks

Grand Challenge: Addressing Social Issues That Span National Boundaries and Multiple Cultures & Disciplines

• Challenges Include Climate Change, Economic Dislocation, Natural Disasters, Globalization, the Decay of Civil Society

• Complex problems requiring HPC

• Requires collaboration among scholars from multiple nations, funding agencies, practitioners

• ARTCA: Advanced Research and Technology Collaborative for the Americas• A new vision of engaged scholarship • Emergency Management System-Costa Rica• Alaskan Native Americans• Alliances across funders: NSF, NEH, CONICITs

• Million CPU Projects:• The Credit Crunch: An Evaluation of Alternative Policy Responses with High Performance

Computing, Krasa, Villamil, and Shorish (UIUC)• Census without Boundaries, Nedovic-Budic (UIUC) & Albrecht (NYU)

• Wendy Cho: Redistricting Studies

Bottlenecks/Issues to Achieving Objectives

• Need to Develop and Scale Up Applications Like Social Network Analysis to PetaScale levels – leverage collaborations with the world’s leading developers of network analytic methods and algorithms

• Need for Data-Intensive Computing to Handle Huge Amounts of Multimodal Data

• Need to Develop Capabilities for Simulation and Visualization

• Need to Develop Capabilities for Modeling Large Scale Longitudinal Processes—Current Methodologies Are Best Suited for Statics and Statistical Analysis

• Need to Develop Capabilities for Modeling Virtual Worlds

NCSA Strategic Planning Presentation (April 20,2010)

Cyberinfrastructure Challenges in Reaching the Objectives

• ability to handle huge multimodal datasets

• fusion of data from multiple sources (e.g. images, text, GIS)

• automated analysis of large bodies of video (HD) and audio data

• ability to compare observations and modeling

• handling of real-time data streams

• handling and analyzing complex data structures

• workflow tools to handle complex processes

• parallel analysis/data mining

• visualization tools for understanding large and/or mutliple source data

• persistent virtual worlds of massive complexity (both VR and Synthetic worlds

• collaborations among social scientists, technologists (for above technological capabilities), and translators/project managers

NCSA Strategic Planning Presentation (April 20,2010)

Summary Research in computational social science is well poised to make Research in computational social science is well poised to make

a quantum intellectual leap by facilitating collaboration that a quantum intellectual leap by facilitating collaboration that leverages recent advances in:leverages recent advances in:

Theories about the social motivations for creating, maintaining, Theories about the social motivations for creating, maintaining, dissolving and re-creating social network tiesdissolving and re-creating social network ties

Development of cyberinfrastructure/Web 2.0Development of cyberinfrastructure/Web 2.0 provide the provide the technological capability to capture relational metadata needed to technological capability to capture relational metadata needed to more effectively understand (and enable) communities.more effectively understand (and enable) communities.

Exponential random graph modeling techniques to make network Exponential random graph modeling techniques to make network recommendations grounded in social science and team science recommendations grounded in social science and team science reseachreseach

Petascale infrastructure that can meet large scale computational Petascale infrastructure that can meet large scale computational requirements of these analyses requirements of these analyses

References

• Recent ARCTA Conference in Washington DC• NSF, NEH people• Our Cultural Commonwealth (ACLS)• NSF-SBE-CISE Workshop on Cyberinfrastructure and

the Social Sciences (NSF)