Capturing and supporting contexts for scientific data sharing via the biological sciences collaboratory

Author(s):  
George Chin ◽  
Carina S. Lansing
2010 ◽  
Vol 12 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Yunqiang ZHU ◽  
Jiulin SUN ◽  
Shunbao LIAO ◽  
Yapeng YANG ◽  
Huazhong ZHU ◽  
...  

2010 ◽  
Vol 11 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Yunqiang ZHU ◽  
Min FENG ◽  
Jia SONG ◽  
Runda LIU

2020 ◽  
Vol 33 (2) ◽  
pp. 101-119
Author(s):  
Emily Hauptmann

ArgumentMost social scientists today think of data sharing as an ethical imperative essential to making social science more transparent, verifiable, and replicable. But what moved the architects of some of the U.S.’s first university-based social scientific research institutions, the University of Michigan’s Institute for Social Research (ISR), and its spin-off, the Inter-university Consortium for Political and Social Research (ICPSR), to share their data? Relying primarily on archived records, unpublished personal papers, and oral histories, I show that Angus Campbell, Warren Miller, Philip Converse, and others understood sharing data not as an ethical imperative intrinsic to social science but as a useful means to the diverse ends of financial stability, scholarly and institutional autonomy, and epistemological reproduction. I conclude that data sharing must be evaluated not only on the basis of the scientific ideals its supporters affirm, but also on the professional objectives it serves.


AI & Society ◽  
2021 ◽  
Author(s):  
Suzanne Anker

AbstractThis paper addresses three aspects of Bio Art: iconography, artificial life, and wetware. The development of models for innovation require hybrid practices which generate knowledge through epistemic experimental practices. The intersection of art and the biological sciences contain both scientific data as well as the visualization of its cultural imagination. In the Bio Art Lab at the School of Visual Arts, artists use the tools of science to make art.


2012 ◽  
Vol 522 ◽  
pp. 770-775
Author(s):  
Yu Zheng ◽  
Yan Rong Ni ◽  
Deng Zhe Ma

In order to satisfy the needs of fast and convenient customization of manufacturing scientific data sharing service, the data service customization process and its key technologies were studied. First the data resource model and the customization oriented professional data service model were studied. Then the processes of service customization, from resource registration, service definition, service parsing, to service generating, were analyzed. The parsing engine based on service parsing technology and incubator based on service generating technology was emphasized. Finally the prototype system was developed and validated by an example.


Author(s):  
Michael Wilson ◽  
Shirley Crompton ◽  
Brian Matthews ◽  
Alexey Orlov
Keyword(s):  

2021 ◽  
Author(s):  
Regina Becker ◽  
Adrian Thorogood ◽  
Jasper Bovenberg ◽  
Colin Mitchell ◽  
Alison Hall

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