e-Science Infrastructure for the Social Sciences

When the term „e-Science“ became popular, it frequently was referred to as “enhanced science” or “electronic science”. More telling is the definition ‘e-Science is about global collaboration in key areas of science and the next generation of infrastructure that will enable it’ (Taylor, 2001). The question arises to what extent can the social sciences profit from recent developments in e- Science infrastructure? While computing, storage and network capacities so far were sufficient to accommodate and access social science data bases, new capacities and technologies support new types of research, e.g. linking and analysing transactional or audio-visual data. Increasingly collaborative working by researchers in distributed networks is efficiently supported and new resources are available for e-learning. Whether these new developments become transformative or just helpful will very much depend on whether their full potential is recognized and creatively integrated into new research designs by theoretically innovative scientists. Progress in e-Science was very much linked to the vision of the Grid as “a software infrastructure that enables flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions and resources’ and virtually unlimited computing capacities (Foster et al. 2000). In the Social Sciences there has been considerable progress in using modern IT- technologies for multilingual access to virtual distributed research databases across Europe and beyond (e.g. NESSTAR, CESSDA – Portal), data portals for access to statistical offices and for linking access to data, literature, project, expert and other data bases (e.g. Digital Libraries, VASCODA/SOWIPORT). Whether future developments will need GRID enabling of social science databases or can be further developed using WEB 2.0 support is currently an open question. The challenges here are seamless integration and interoperability of data bases, a requirement that is also stipulated by internationalisation and trans-disciplinary research. This goes along with the need for standards and harmonisation of data and metadata. Progress powered by e- infrastructure is, among others, dependent on regulatory frameworks and human capital well trained in both, data science and research methods. It is also dependent on sufficient critical mass of the institutional infrastructure to efficiently support a dynamic research community that wants to “take the lead without catching up”.

An "All Hands" Call to the Social Science Community: Establishing a Community Framework for Complexity Modeling Using Agent Based Models and Cyberinfrastructure

To date, many communities of practice (COP) in the social sciences have been struggling with how to deal with rapidly growing bodies of information. Many CoPs across broad disciplines have turned to community frameworks for complexity modeling (CFCMs) but this strategy has been slow to be discussed let alone adopted by the social sciences communities of practice (SS-CoPs). In this paper we urge the SS-CoPs that it is timely to develop and establish a CBCF for the social sciences for two major reasons: the rapid acquisition of data and the emergence of critical cybertools which can facilitate agent-based, spatially-explicit models. The goal of this paper is not to prescribe how a CFCM might be set up but to suggest of what components it might consist and what its advantages would be. Agent based models serve the establishment of a CFCM because they allow robust and diverse inputs and are amenable to output-driven modifications. In other words, as phenomena are resolved by a SS-CoP it is possible to adjust and refine ABMs (and their predictive ability) as a recursive and collective process. Existing and emerging cybertools such as computer networks, digital data collections and advances in programming languages mean the SS-CoP must now carefully consider committing the human organization to enabling a cyberinfrastructure tool. The combination of technologies with human interfaces can allow scenarios to be incorporated through 'if' 'then' rules and provide a powerful basis for addressing the dynamics of coupled and complex social ecological systems (cSESs). The need for social scientists to be more engaged participants in the growing challenges of characterizing chaotic, self-organizing social systems and predicting emergent patterns makes the application of ABMs timely. The enabling of a SS-CoP CFCM human-cyberinfrastructure represents an unprecedented opportunity to synthesize, compare and evaluate diverse sociological phenomena as a cohesive and recursive community-driven process.Community-Based Complex Models, Mathematics, Social Sciences

Administrative Transaction Data

The value of administrative transaction data, such as financial transactions, credit card purchases, telephone calls, and retail store scanning data, to study social behaviour has long been recognised. Now new types of transactions data made possible by advances in cyber-technology have the potential to further exland social scientists’ research frontier. This chapter discusses the potential for such data to be included in the scientific infrastructure. It discusses new approaches to data dissemination, as well as the privacy and confidentiality issues raised by such data collection. It also discusses the characteristics of an optimal infrastructure to support the scientific analysis of transactions data.transactions data; administrative data; cybertechnology; privacy and confidentiality; virtual organizations

Balancing Access to Data And Privacy. A review of the issues and approaches for the future

Access to sensitive micro data should be provided using remote access data enclaves. These enclaves should be built to facilitate the productive, high-quality usage of microdata. In other words, they should support a collaborative environment that facilitates the development and exchange of knowledge about data among data producers and consumers. The experience of the physical and life sciences has shown that it is possible to develop a research community and a knowledge infrastructure around both research questions and the different types of data necessary to answer policy questions. In sum, establishing a virtual organization approach would provided the research community with the ability to move away from individual, or artisan, science, towards the more generally accepted community based approach. Enclave should include a number of features: metadata documentation capacity so that knowledge about data can be shared; capacity to add data so that the data infrastructure can be augmented; communication capacity, such as wikis, blogs and discussion groups so that knowledge about the data can be deepened and incentives for information sharing so that a community of practice can be built. The opportunity to transform micro-data based research through such a organizational infrastructure could potentially be as far-reaching as the changes that have taken place in the biological and astronomical sciences. It is, however, an open research question how such an organization should be established: whether the approach should be centralized or decentralized. Similarly, it is an open research question as to the appropriate metrics of success, and the best incentives to put in place to achieve success.Methodology for Collecting, Estimating, Organizing Microeconomic Data

Towards a cyberinfrastructure for enhanced scientific

A new generation of information and communication infrastructures, including advanced Internet computing and Grid technologies, promises to enable more direct and shared access to more widely distributed computing resources than was previously possible. Scientific and technological collaboration, consequently, is more and more coming to be seen as critically dependent upon effective access to, and sharing of digital research data, and of the information tools that facilitate data being structured for efficient storage, search, retrieval, display and higher level analysis. A recent (February 2003) report to the U.S. NSF Directorate of Computer and Information System Engineering urged that funding be provided for a major enhancement of computer and network technologies, thereby creating a cyberinfrastructure whose facilities would support and transform the conduct of scientific and engineering research. The articulation of this programmatic vision reflects a widely shared expectation that solving the technical engineering problems associated with the advanced hardware and software systems of the cyberinfrastructure will yield revolutionary payoffs by empowering individual researchers and increasing the scale, scope and flexibility of collective research enterprises. The argument of this paper, however, is that engineering breakthroughs alone will not be enough to achieve such an outcome; success in realizing the cyberinfrastructure’s potential, if it is achieved, will more likely to be the resultant of a nexus of interrelated social, legal and technical transformations. The socio-institutional elements of a new infrastructure supporting collaboration – that is to say, its supposedly “softer” parts -- are every bit as complicated as the hardware and computer software, and, indeed, may prove much harder to devise and implement. The roots of this latter class of challenges facing “e-Science” will be seen to lie in the micro- and meso-level incentive structures created by the existing legal and administrative regimes. Although a number of these same conditions and circumstances appear to be equally significant obstacles to commercial provision of Grid services in interorganizational contexts, the domain of publicly supported scientific collaboration is held to be the more hospitable environment in which to experiment with a variety of new approaches to solving these problems. The paper concludes by proposing several “solution modalities,” including some that also could be made applicable for fields of information-intensive collaboration in business and finance that must regularly transcends organizational boundaries.

Towards a cyberinfrastructure for enhanced scientific

Scientific and technological collaboration is more and more coming to be seen as critically dependent upon effective access to, and sharing of digital research data, and of the information tools that facilitate data being structured for efficient storage, search, retrieval, display and higher level analysis. A February 2003 report to the U.S. NSF Directorate of Computer and Information System Engineering urged that funding be provided for a major enhancement of computer and network technologies, thereby creating a cyberinfrastructure whose facilities would support and transform the conduct of scientific and engineering research. The argument of this paper is that engineering breakthroughs alone will not be enough to achieve such an outcome; success in realizing the cyberinfrastructure’s potential, if it is achieved, will more likely to be the resultant of a nexus of interrelated social, legal and technical transformations. The socio-institutional elements of a new infrastructure supporting collaboration that is to say, its supposedly “softer” parts -- are every bit as complicated as the hardware and computer software, and, indeed, may prove much harder to devise and implement. The roots of this latter class of challenges facing “e- Science” will be seen to lie in the micro- and meso-level incentive structures created by the existing legal and administrative regimes. Although a number of these same conditions and circumstances appear to be equally significant obstacles to commercial provision of Grid services in interorganizational contexts, the domain of publicly supported scientific collaboration is held to be the more hospitable environment in which to experiment with a variety of new approaches to solving these problems. The paper concludes by proposing several “solution modalities,” including some that also could be made applicable for fields of information-intensive collaboration in business and finance that must regularly transcends organizational boundaries.

What is Cyberinfrastructure?

Cyberinfrastructure is a word commonly used but lacking a single, precise definition. One recognizes intuitively the analogy with infrastructure, and the use of cyber to refer to thinking or computing – but what exactly is cyberinfrastructure as opposed to information technology infrastructure? Indiana University has developed one of the more widely cited definitions of cyberinfrastructure: "Cyberinfrastructure consists of computing systems, data storage systems, advanced instruments and data repositories, visualization environments, and people, all linked together by software and high performance networks to improve research productivity and enable breakthroughs not otherwise possible." A second definition, more inclusive of scholarship generally and educational activities, has also been published and is useful in describing cyberinfrastructure: "Cyberinfrastructure consists of systems, data and information management, advanced instruments, visualization environments, and people, all linked together by software and advanced networks to improve scholarly productivity and enable knowledge breakthroughs and discoveries not otherwise possible." In this paper, we describe the origin of the term cyberinfrastructure based on the history of the root word infrastructure, discuss several terms related to cyberinfrastructure, and provide several examples of cyberinfrastructure