scholarly journals Meaningful Data Sharing: Developing the Illinois Data Bank Metadata Framework

2018 ◽  
Vol 18 (2) ◽  
pp. 59-83 ◽  
Author(s):  
Ayla Stein ◽  
Elise Dunham
2013 ◽  
Vol 104 (2) ◽  
pp. 567a
Author(s):  
Lee Whitmore ◽  
Benjamin Woollett ◽  
Robert W. Janes ◽  
B.A. Wallace

2021 ◽  
Vol 10 (3) ◽  
Author(s):  
Hoa Q. Luong ◽  
Colleen Fallaw ◽  
Genevieve Schmitt ◽  
Susan M. Braxton ◽  
Heidi Imker

Objective: The Illinois Data Bank provides Illinois researchers with the infrastructure to publish research data publicly. During a five-year review of the Research Data Service at the University of Illinois at Urbana-Champaign, it was recognized as the most useful service offering in the unit. Internal metrics are captured and used to monitor the growth, document curation workflows, and surface technical challenges faced as we assist our researchers. Here we present examples of these curation challenges and the solutions chosen to address them. Methods: Some Illinois Data Bank metrics are collected internally by within the system, but most of the curation metrics reported here are tracked separately in a Google spreadsheet. The curator logs required information after curation is complete for each dataset. While the data is sometimes ambiguous (e.g., depending on researcher uptake of suggested actions), our curation data provide a general understanding about our data repository and have been useful in assessing our workflows and services. These metrics also help prioritize development needs for the Illinois Data Bank. Results and Conclusions: The curatorial services polish and improve the datasets, which contributes to the spirit of data reuse. Although we continue to see challenges in our processes, curation makes a positive impact on datasets. Continued development and adaptation of the technical infrastructure allows for an ever-better experience for the curators and users. These improvements have helped our repository more effectively support the data sharing process by successfully fostering depositor engagement with curators to improve datasets and facilitating easy transfer of very large files.


2010 ◽  
Vol 98 (3) ◽  
pp. 196a-197a
Author(s):  
Lee Whitmore ◽  
Benjamin Woollett ◽  
Andrew J. Miles ◽  
Robert William Janes ◽  
B.A. Wallace

Author(s):  
Helen M. Berman

The Protein Data Bank began as a grassroots effort in 1971. It has grown from a small archive containing a dozen structures to a major international resource for structural biology containing more than 40000 entries. The interplay of science, technology and attitudes about data sharing have all played a role in the growth of this resource.


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