This comparative study uses ethnographic, interview, and content data analysis to provide a situated social and organizational comparison of three scientific projects with distinct approaches to developing cyberinfrastructures and achieving data interoperability. The three projects are GEON (, a geosciences project using a national distributed storage broker to create data sharing across multiple disciplines through developing shared ontologies; LTER (, a long-term ecological program using metadata standards to federate data across a single discipline; and Ocean Informatics, an oceanographic team building community and designing a local metadata standard to bridge key data collections to a national standard.

Intellectual Need: As new scientific cyberinfrastructures emerge, a central question is how to share data across multiple distributed organizational and social contexts. There have been many suggestions for technical fixes for this pressing concern (particularly important since some of today's great political questions, such as preserving biodiversity and developing a sustainable relationship with the environment pivot on the ability to federate data across organizational and disciplinary contexts). However, there has been little study - and no comparative study - of the organizational and social dimensions of differing interoperability strategies. The working hypothesis for this project, drawing on research in the field of social informatics over the past fifteen years, is that creation of a common shared data infrastructure entails complex negotiations involving the relative institutional weight of the different actors (institutions have a range of motives for subscribing or not to interoperability strategies), the nature of their disciplinary organization (in particular reward structures; openness to interdisciplinary work; history of use of large datasets) and the nature of their domain work (degree of commitment to long-term data storage and re-use; decay rate of data over time; need to draw on large federate datasets). This study will develop grounded understandings of the organizational complexity in producing shared scientific cyberinfrastructure and the costs and benefits of three interoperability approaches: metadata standards, ontologies, and community-driven approaches.

Broader Impact: The development of scientific cyberinfrastructure is vital for this country's future economic prosperity and for its ability to respond to key policy issues with scientific and technical dimensions. Cyberinfrastructure is a large-scale contemporary investment; this study will help inform the decisions that today are determining future structural outcomes. At the level of science policy, the project will facilitate understandings of the organizational and social dimensions in building shared infrastructure. The research will produce a policy white paper on data communities and scientific cyberinfrastructure and suggest guidelines for the ongoing formative evaluation of infrastructure development activities. As these new communication tools develop, there is a need for educational programs to sensitize domain scientists, computer scientists and science policy workers to social and organizational issues. The project will produce, as a centerpiece to a Masters level program in cyberinfrastructure, a graduate course about its development, as well as a secondary school lesson module for use in an educational partnership. A 'Cyberinfrastructure Page' website, modeled on 'Inquiry Page' (, will incorporate the course and module and allow this project to share results first with the partner communities and then across communities. This will provide the kernel of a resource site for researchers and practitioners in the emergent field of scientific cyberinfrastructure, to share findings and best practices and to engage in collective problem solving.

This project is supported by an award from the FY 2004 NSF-wide competition on Human and Social Dynamics (HSD). Coordinated management of the HSD competition and the portfolio of HSD awards involves all NSF directorates and offices.

National Science Foundation (NSF)
Division of Social and Economic Sciences (SES)
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Mark L. Weiss
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Santa Clara University
Santa Clara
United States
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