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Who’S Got The Data? Interdependencies In Science And Technology Collaborations, Christine L. Borgman, Jillian C. Wallis, Matthew S. Mayernik
Who’S Got The Data? Interdependencies In Science And Technology Collaborations, Christine L. Borgman, Jillian C. Wallis, Matthew S. Mayernik
Christine L. Borgman
Science and technology always have been interdependent, but never more so than with today’s highly instrumented data collection practices. We report on a long-term study of collaboration between environmental scientists (biology, ecology, marine sciences), computer scientists, and engineering research teams as part of a five-university distributed science and technology research center devoted to embedded networked sensing. The science and technology teams go into the field with mutual interests in gathering scientific data. “Data” are constituted very differently between the research teams. What are data to the science teams may be context to the technology teams, and vice versa. Interdependencies between …
Data, Data Use, And Scientific Inquiry: Two Case Studies Of Data Practices, Laura Wynholds, Jillian Wallis, Christine Borgman, Ashley Sands, Sharon Traweek
Data, Data Use, And Scientific Inquiry: Two Case Studies Of Data Practices, Laura Wynholds, Jillian Wallis, Christine Borgman, Ashley Sands, Sharon Traweek
Christine L. Borgman
Data are proliferating far faster than they can be captured, managed, or stored. What types of data are most likely to be used and reused, by whom, and for what purposes? Answers to these questions will inform information policy and the design of digital libraries.
We report findings from semi-structured interviews and field observations to investigate characteristics of data use and reuse and how those characteristics vary within and between scientific communities. The two communities studied are researchers at the Center for Embedded Network Sensing (CENS) and users of the Sloan Digital Sky Survey (SDSS) data. The data practices of …
Unearthing The Infrastructure: Humans And Sensors In Field-Based Scientific Research, Matthew S. Mayernik, Jillian C. Wallis, Christine L. Borgman
Unearthing The Infrastructure: Humans And Sensors In Field-Based Scientific Research, Matthew S. Mayernik, Jillian C. Wallis, Christine L. Borgman
Christine L. Borgman
Distributed sensing systems for studying scientific phenomena are critical applications of information technologies. By embedding computational intelligence in the environment of study, sensing systems allow researchers to study phenomena at spatial and temporal scales that were previously impossible to achieve. We present an ethnographic study of field research practices among researchers in the Center for Embedded Networked Sensing (CENS), a National Science Foundation Science & Technology Center devoted to developing wireless sensing systems for scientific and social applications. Using the concepts of boundary objects and trading zones, we trace the processes of collaborative research around sensor technology development and adoption …
Local Or Global? Making Sense Of The Data Sharing Imperative (Keynote), Christine L. Borgman
Local Or Global? Making Sense Of The Data Sharing Imperative (Keynote), Christine L. Borgman
Christine L. Borgman
No abstract provided.
The Sensed Vs Sensing In Embedded Networked Sensing#11;Data And Data Sharing At An Ens Research Center, Christine L. Borgman
The Sensed Vs Sensing In Embedded Networked Sensing#11;Data And Data Sharing At An Ens Research Center, Christine L. Borgman
Christine L. Borgman
No abstract provided.
The Social Embeddedness Of Embedded Networked Sensing, Christine L. Borgman
The Social Embeddedness Of Embedded Networked Sensing, Christine L. Borgman
Christine L. Borgman
No abstract provided.
Scientific Data Archiving: The State Of The Art In Information, Data, And Metadata Management, Kalpana Shankar
Scientific Data Archiving: The State Of The Art In Information, Data, And Metadata Management, Kalpana Shankar
Christine L. Borgman
This white paper is the product of a one-year postdoctoral fellowship to study data archiving requirements for the Center for Embedded Networked Sensing during its first year of operation. The paper focuses on introducing current thinking on scientific data management issues and primarily on relevant standards in data description (metadata) and management for scientific archives. Appendices include a
rudimentary data dictionary for the current James Reserve database, and sample metadata crosswalks for Ecological Metadata Language (EML) and Sensor ML. This paper covers current standards, developments, and sources of datasets (where appropriate) for:
• General data management and discovery - tools …