27 May, 2005IASSIST1 e-Social Science: Sensor Grids for the Social Sciences? Rob Procter National Centre for e-Social Science

27 May, 2005IASSIST2 Overview n The e-Research vision and the Grid n e-Social Science explained n National Centre for e-Social Science n Sensor grids for the physical sciences n Sensor grids for the social sciences?

27 May, 2005IASSIST3 The e-Research Vision “[e-Research] is about global collaboration in key areas of science and the next generation of infrastructure that will enable it.” John Taylor, Director General of Research Councils, UK Office of Science and Technology “The goal of [e-Research] is to provide an integrated, high-end system of computing, data facilities, connectivity, software, services, and instruments that enables all scientists, engineers and educators to work in new ways on advanced research problems that would not otherwise be solvable.” Peter Freeman, Director, Computer & Information Science & Engineering, National Science Foundation n A globally connected, scholarly community promoting the highest quality scientific research

27 May, 2005IASSIST4 GRIDMIDDLEWAREGRIDMIDDLEWARE Visualizing Supercomputer, PC-Cluster Data Storage, Sensors, Experiments Desktop Mobile Access H.F. Hoffmann, CERN Internet This infrastructure is commonly known as the Grid Supporting resource use across administrative domains

27 May, 2005IASSIST5 Typical Views of Access Grid ETF Management MeetingSeminar SC Global WorkshopPerformance Arte-Social Science

27 May, 2005IASSIST6 e-Social Science n As social scientists become increasingly concerned with addressing complex research problems, they require (re)use of increasingly multi-level, multi- textured data resources n e-Research offers the potential to study complex social processes in new ways through improved methods and tools for data description, discovery and analysis

27 May, 2005IASSIST7 Example: ConvertGrid n Spatial correlation of recorded burglaries with house prices and indicators of social wellbeing/deprivation n Study target geography – 1998 LAD n Datasets required: –1991 Census Total pop (1991 ward) Unemployment (1991 ward) Overcrowding (1991 ward) –Neighbourhood Statistics 1998 data Population estimates (1998 ward) Recorded household burglaries (1998 Ward) –Experian 1999 supply Total population (1999 PCS) Annual average house sale value (1999 PCS) Population in MOSAIC Group A (1999 PCS) Keith Cole, University of Manchester

27 May, 2005IASSIST8 National Centre for e-Social Science n Funded by ESRC for 3 years initially n Aim is to develop and promote e-Social Science n Co-ordinating hub at Manchester n Four research nodes commissioned, up to four more to follow n Seven smaller projects commissioned, more to follow

27 May, 2005IASSIST9 NCeSS activities n Applications of e-Research: –Substantive social science research problems –Enhancing existing areas of research and methods –Encouraging innovation n Social shaping of e-Research: –Socio-technical factors in the design, uptake and use of e-Research –Implications for research practice and the character of knowledge production –Policy and socio-economic impacts

27 May, 2005IASSIST10 Nodes n Modelling and Simulation for e-social Science (MoSeS): –Generic frameworks through which grid- enabled modeling and simulation might be exploited within a wide range of social science problem domains n Mixed Media Grid: –Tools and techniques for social scientists to analyse audio-visual qualitative data and related materials collaboratively over the Grid

27 May, 2005IASSIST11 Nodes n Collaboration for Quantitative e-Social Science Statistics (CQeSS): – Developing e-science tools appropriate to quantitative e-social science n Understanding New Forms of Digital Record for e-Social Science: –Extending Grid based technologies to provide new processes and services through which social science data may be collected, collated, and distributed

27 May, 2005IASSIST12 Ÿ Joint US-Canadian project to build large undersea fiber network off west coast of US and Canada Ÿ Undersea network will connect instrumentation devices, robotic submarines, sensors, under sea cameras, etc Ÿ Distributed computing and data storage devices will be used to analyze and store data Sensor Grids for the Physical Sciences Project Neptune

27 May, 2005IASSIST13 Powering the Virtual Universe (Edinburgh, Belfast, Cambridge, Leicester, London, Manchester, RAL) Multi-wavelength showing the jet in M87: from top to bottom – Chandra X-ray, HST optical, Gemini mid-IR, VLA radio. AstroGrid will provide advanced, Grid based, federation and data mining tools to facilitate better and faster scientific output. Picture credits: “NASA / Chandra X-ray Observatory / Herman Marshall (MIT)”, “NASA/HST/Eric Perlman (UMBC), “Gemini Observatory/OSCIR”, “VLA/NSF/Eric Perlman (UMBC)/Fang Zhou, Biretta (STScI)/F Owen (NRA)”

27 May, 2005IASSIST14 Sensor Grids for the Social Sciences? n To date, the idea of instrumenting the social world to collect data about human activity has been largely limited to laboratory settings: –HCI –Practice-based teaching –Collaboration –‘Future’ homes n This has its limitations

27 May, 2005IASSIST15 Sensor Grids for the Social Sciences? n Commercial use of data about people’s activities in the real world is well established: –Purchases, financial transactions, telecoms n Healthcare beginning to exploit home-based and mobile devices for remote monitoring n Social sciences have a long tradition of recording data about people’s activities in the real world but methods have been limited in scope and power: –Surveys and questionnaires Census, BHPS, etc. –Observational studies in the field: Written notes Audio Video

27 May, 2005IASSIST16 Bringing the Environment Online

27 May, 2005IASSIST17 Sensor Grids for the Social Sciences? n The social world is increasingly digital: –Growing shift towards an e-Society (e-Business e-Medicine and e-Learning) –Rapid increase in online information and increasingly richer representations of human activities n This shift provides a fascinating opportunity for social sciences to obtain a richer picture of people’s activities and some major challenges: –What can be captured and how –How might this data be analysed and understood –How might security, privacy, confidentiality and ethical issues be addressed

27 May, 2005IASSIST18 Sensor Grids for the Social Sciences? n Digital data is generated on increasing scale as by product of everyday activities of social actors, exposing the dynamics of a wide variety of social processes –Patterns of consumption: Public and private goods and services –Patterns of communication: , bulletin boards, weblogs, chat rooms, news feeds, mobile phones, SMS –Patterns of movement of people and goods: CCTV, speed cameras, traffic monitoring, GPRS, embedded devices n ESRC plans to move from traditional survey- based methods to using administrative data

27 May, 2005IASSIST19 A Social Sciences Virtual Observatory n These new sources of data about the social world are different in character from conventional social science datasets: –Vast, dynamic, proliferating, with content and relevance changing continuously and unpredictably n Making such data sources useful for research needs tools for: –Resource description and discovery –Anonymising –Filtering –Integrating, structuring and cross linking multiple data streams –Annotating –Summarising –Sentiment detection –Visualisation –Distributed analysis n Text mining tools are beginning to meet some of these needs

27 May, 2005IASSIST20 GRIDMIDDLEWAREGRIDMIDDLEWARE

27 May, 2005IASSIST21 FINGRID: Financial INformation Grid n FINGrid is a demonstrator for analysing financial information in form of quantitative data (time series) and qualitative data (financial/political news) n FINGrid works by text mining financial news (Reuters news feed) for ‘market sentiment’ and then attempts to correlate this data with time series data of market price movements n The ultimate aim is to understand better the relationship between price movements and market sentiment Prof K Ahmad, University of Surrey

27 May, 2005IASSIST22

27 May, 2005IASSIST23 Summary n Sensor grids for social science research envisage harnessing the progressive ‘instrumentation’ of the social world n Could provide a much richer picture of social phenomena than is available through more conventional techniques n Need powerful new tools to make find, organise and make sense of this data n Need solutions to meet the security privacy, confidentiality and ethical challenges

27 May, 2005IASSIST24 Getting Involved in NCeSS n Small grant programme is open until July 31 st n Agenda Setting Workshop on Collaboration, Co-Laboratories and e- Research: Understanding and Supporting New Forms of Science and Social Science 21 st June n First International Conference on e- Social Science 22 nd -24 th June