This document summarizes a pilot project that integrated technical infrastructure, collaboration, and knowledge to develop e-social science. An interdisciplinary team addressed social research questions by adapting Grid technologies. The project explored crime patterns in relation to socioeconomic factors. Researchers from various disciplines collaborated with data providers and technologists. Through training and iterative development, the team shaped new computer tools to analyze datasets using the Grid. The project demonstrated how situated innovations can appropriately develop technologies for social science research through collaboration.

1. Prepared for 2010 Graduate seminarInformetrics and e-research (prof. Han Woo Park),at Yeungnam Univ. in S. Korea Situated Innovations in e-Social Science Bridgette Wessels and Max Craglia Presented by Kim KyoungEun river@ynu.ac.kr 3. May 2010

2. Introduction ▶ This chapter explores a user-led approach in the development of e-social science in which an interdisciplinary team integrated technical infrastructure, collaboration, and knowledge in the development of e-social science. ▶ In this chapter, ‘development’ refers to the work done by researchers to adapt Grid technologies to address an interdisciplinary social research problem.

3. Introduction ▶ The e-social science pilot project discussed in this chapter addressed three main dimensions of e-social science. ⑴ identification of new social research foci (focus) ⑵ adapting research processes ⑶ developing tools ⇒ The way in which these three dimensions of the project were integrated shows that the development of computer-mediated research using the Grid can develop relevant and innovative tools for the social sciences.

6. The Pilot Project ▶ The core research team : 3 urban planners with Geographical Information Systems(GIS) expertise / 2 criminologists / 2 sociologists (including the ethnographer) / 1 computer scientist (Grid Officer) ▶ The support services group : the academic White Rose Grid(WRG) consortium / the Open Geospatial Consortium(OGC) ▶ Other data source : the Census accessed through MIMAS / the Index of Multiple Deprivation 2004 -> three group of social scientists, data provider/practitioners / technology providers collaborated in exploring the possibilities of the Grid for use in the social sciences.

7. Technology and Innovation in the Project ▶ The analytical framework of the project was based on the social shaping definitions of ‘technology’ and ‘innovation’. : ‘technology’ - “set of physical object… human activities… and knowledge” : ‘innovation’ – a complex social activity, involving learning processes and the interaction and sharing of expertise among different actors in the project network.

8. Technology and Innovation in the Project ▶ Changes to practices and tools were made from action situated in the project required researchers to learn new techniques and perspectives in developing e-social science. The researchers worked with existing social science classification systems and had to combine them in new ways : ‘the methodological articulation’ The meetings and workshops enable the ‘artful integration’ of innovative technology, the Grid, with the social and material worlds of academic perspectives and methods.

9. Shaping New computer-Supported Research Tools ▶ The approach of the team was that the knowledge and practices of social science should shape the technological development. - The researchers adopted an inductive approach to: ⑴ explore the different disciplinary approaches in the study of the relationship between young people at risk of crime and the characteristics of their neighborhood, ⑵ develop the methodology and relevant tools from the needs of the social science research. The researchers made sense of the research problem through this inductive approach that led to deductive statistical modeling and systematic computer-supported data processing. The team aligned the above approach with design in use methodology.

10. Shaping New computer-Supported Research Tools ▶ The process of design and use was integrated in pilot project. - The project trajectory was : 1. Development of multi-disciplinary collaborative research and research partnership. 2. Discussion of theoretical issues to underpin the multi-disciplinary approach. 3. Training for the social scientists and technological development of the Grid. 4. Integration and analysis of the datasets. 5. Further Grid development and sharing outcomes among partners. -> Each of these phases in the trajectory is elaborated below.

11. Phase1: Developing Multi-Disciplinary Collaborative Research. ▶ The fostering of the collaborative approach consisted of a range of meetings and discussions within the core team, and between the core team and the policy and practitioners group, and with the technical expert from the OGC. (Open Geospatial Consortium) -> In the next meetings of the core team, each of the researchers discussed their disciplinary approach to the research problem, data sources, and theoretical perspectives. : urban planner / criminologist / sociologist / Grid officer

12. Phase1: Developing Multi-Disciplinary Collaborative Research ▶ The core team also had to develop a dialogue and shared understanding with the project-partners. The official ‘Kick-off meeting’ involved the core team meeting with representatives from regional policy makers, service and data providers, and technology providers. (OGC & WRG) : The focus of the kick-off meeting was to outline the project, look at the kind of data needed, and introduce everyone to the Grid. : The time and effort spent by the core team at this stage paid off by allowing each partner to see potential value in the project, rather than forcing each of them to subscribe to an assumed single shared objective.

13. Phase 2: Theoretical Frameworks ▶ In this phase of the project, the core team furthered its discussion of the research problem and conducted literature reviews focusing on environmental criminology, Grid technology, and risk factors for young people. : In particular, the sociologist were concerned to develop a theoretical framework that would inform the multi-disciplinary research and help to select datasets and research methodologies.

14. Phase 2: Theoretical Frameworks ▶ They developed research questions to aid the researchers in developing a multi-disciplinary framework. - The questions were: 1. Can we construct a reliable set of measures for community-based risk factors that allow us to measure them at ward or neighborhood level? 2. Can we create a ‘national norm’ with which to compare? 3. If so, what relationship might exist between levels of risk and levels of crime - are neighborhoods in communities with high-risk level young people also areas with high-risk factors? 4. What relationship might exist between levels of risk and levels of crime?

15. Phase 2: Theoretical Frameworks ▶ The Grid officer took part in all the meetings could learn to appreciate the social science perspective. He felt that understanding social science would help him to develop Grid-related tools and training for the social scientists. The Grid officer pointed out that access to such systems(UNIXor LINUX) requires familiarity with client applications and protocols for transferring data and communicating with remote systems, which is further complicated by the introduction of modern protocols for secure communication.

16. Phase 3: Training for the Social Scientists ▶ The core team took part in three technological and three statistical training workshops, held in the University’s computer training rooms. The researchers were given passwords and identifiers to work on the WRG. : Graphic User Interfaces(GUIs) application / X protocol / secure protocols such as secure shell client(SSH) ⇒ These procedures were new to many social scientists and required an understanding of the related concepts and practices.

17. Phase 3: Training for the Social Scientists ▶ The second half of the workshop series : learning the basis of the statistical package, SPlus, and the geographical information system (GIS) ArcView, as well as accessing various datasets in using the Grid. The researchers’ training on the Grid enabled them to open ArcView on Titania and to begin to work with the idea of a cluster system. - The core team tested the applications by developing a facility for accessing and querying census data via MIMAS

18. Phase 4: Integration and Analysis of the Datasets ▶ The analysis of data was divided into two stages: ⑴ the team analyzed individual variables of the crime and youth datasets, including aggregation at census geography level, calculation of counts, rates, and standardized rates, and identified outliers and extreme values ⑵ the researchers analyzed the key variables to identify statistically significant relationships, supported by the review of the literature on environmental criminology.

19. Phase 4: Integration and Analysis of the Datasets ▶ There are integration of the research outcomes between criminologists and urban planners and social scientist of the offence at South Yorkshire. : Given that very little data linking victims and offenders had previously been available, these are important quantitative findings, which confirm qualitative interviews with young offenders and contribute to the theoretical and policy debates in this field. : The strong link between census data and offenders, on the one hand, and offenders and victimization, on the other, made a very good case for trying to model the geographical distribution of offenders on a national basis using the census variables and to use the outcome as a relative ‘risk’ map for the victimization.

20. Phase 5: Grid Development and Sharing Outcomes among Partners ▶ After developing a model of the distribution of offenders for South Yorkshire and validating it against the observed results, the model was extended to the whole of England at SOA and then filtered through a 1 hectare-cell Grid based on the residential postcodes provided by the national postal service. The advantage of this procedure was that it reported the results of the model more accurately in relation to where people live.

21. Phase 5: Grid Development and Sharing Outcomes among Partners ※ Figure 16.3 (303P) : shows the portal the Grid Officer developed for the researchers to access the application. The researchers, having imported an ASCII file with the data, could then select the number of processors on which to operate. The portal would then schedule the operation via the Globus Middleware, based on the schema showed in Figure 16.1. ※ Figure 16.4 (305P) : By installing WMS (Web map service) on both the university’s and partners’ web servers it was possible to overlay the maps of the model results with those of the policy boundaries, and query the overlay to retrieve the attribute information as illustrated in Figure 16.4.

22. Discussion ▶ The aim of user-driven and research-led development was to appropriate the Grid in ways that relevant to social science. To explore the relationships between technology, research practice, and knowledge in producing e-social science the project adopted a collaborative approach in developing first practical use. The project shows that the interplay of research practices, on the one hand, and Grid technologies, on the other, is highly situational, and that and first use require the artful integration of different practices, communities, and technologies. The researchers collaborating with others in situated innovations contributed their disciplinary perspective as well as methodological and technological knowledge.

23. Discussion ▶ The team demonstrated that not all work requires the Grid, but identifies the context in which the Grid is beneficial for social scientists. Of central importance to the success of the project was the time and effort required to develop a shared understanding of the data. As this project shows, accessing data is more than a matter of technology - it requires the development and maintenance of a relationship of trust between provider and researcher.

24. Discussion ▶ Collaboration needs to move beyond gaining an understanding of a research problem toward integrating and developing a coherent research methodology, analysis, and representation. From a criminological point of view, further research is needed to validate the model developed for the whole country with data provided by police forces other than South Yorkshire. Further research regarding semantic interoperability should explore appropriate methods to analyze data based on the theoretical constructs of different disciplines.

25. Thank you for your attention! Presented by Kim KyoungEun river@ynu.ac.kr