Using Data Management Plans and existing NSF data centers

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Presentation transcript:

Using Data Management Plans and existing NSF data centers Break out group 5

Key Questions to be addressed Can (or should) existing NSF data centers, or other data repositories, be used in this regard? Are such data centers a necessary condition for formulating a reasonable data management plan? How can data management plans be used to attain the goals of sharable and discoverable data for all CMMI programs?

Key Questions to be addressed Can (or should) existing NSF data centers, or other data repositories, be used in this regard? There are possibilities, but currently limited Are such data centers a necessary condition for formulating a reasonable data management plan? How can data management plans be used to attain the goals of sharable and discoverable data for all CMMI programs?

NSF funded data centers: National Data Centers – Environmental Data National Oceanographic Data Center (NODC) www.nodc.noaa.gov National Climatic Data Center (NCDC) https://www.ncdc.noaa.gov/ National geophysical data center (NGDC) www.ngdc.noaa.gov/ngdc.html National Snow & Ice Data Center (NSIDC) Carbon Dioxide Information and Analysis Center http://cdiac.esd.ornl.gov/home.html Artic Data Center (new 2016) https://www.nsf.gov/news/news_summ.jsp?cntn_id=138066

NSF funded data centers: XSEDE – Extreme Science and Engineering Discovery Environment Led by University of Illinois’s National Center for Supercomputing Applications (NCSA) Members (partial listing): Center for advanced Computing – Cornell Center for Education integrating Science, Mathematics and Computing – GaTech Pervasive Technology Institute – Indiana University National Center for Atmospheric Research – Boulder National Institute for computational Sciences – Univ. Tennessee High Performance Computer Center – OSU Ohio Supercomputer Center Texas Advance Computing Center – UT-Austin

NSF funded data centers: Restricted-Access Data Centers (RDCs), also know as Census Research Data Centers https://www.nsf.gov/pubs/2015/nsf15586/nsf15586.htm Now knows as Federal Statistical Research Data Centers http://www.census.gov/fsrdc Data from: Agencies for Healthcare Research and Quality, Census Bureau, National Center for Health Statistics, Bureau of Labor Statistics

Additional NSF centers NSF Data Hubs and spokes Hubs around the country Solicitations to work in hubs Particularly concerned with “big data” issues Natural Hazards Engineering Infrastructure (NHERI) – designsafe-ci.org 13 million over 5 years Cyber infrastructure for hazards community Multi-hazard related problem Testing, field data, experimental Data cloud opportunities Private and Public data Can analyze and process within a secure computer environment

Other of Data Centers ICPSR Inter-University Consortium for Political and Social Research – University of Michigan National Historical Geographic Information System (NHGIS) – University of Minnesota Earth Data: https://earthdata.nasa.gov/ Material genome space – Material data facility – focus on large data NIST etc. Materials commons – U of Mich. (structural materials) Dept. of Energy Center at Georgia Tech.

So the current situation Can (or should) existing NSF data centers, or other data repositories, be used in this regard Not really a NSF based center for material sciences Problem with ontology and schema issues Perhaps something like EarthCube Potential with respect to the Infrastructure community But, not for all areas of infrastructure, much more in the hazards community

Key Questions to be addressed Can (or should) existing NSF data centers, or other data repositories, be used in this regard? Possibilities, but limited currently Are such data centers a necessary condition for formulating a reasonable data management plan? No, but clearly would be helpful Repository function Data preparation and processing for the community (funding) Data integration and linkage How can data management plans be used to attain the goals of sharable and discoverable data for all CMMI programs?

Key Questions to be addressed Can (or should) existing NSF data centers, or other data repositories, be used in this regard? Possibilities, but limited currently Are such data centers a necessary condition for formulating a reasonable data management plan? No, but clearly would be helpful Repository function Data preparation and processing for the community (funding) Data integration and linkage How can data management plans be used to attain the goals of sharable and discoverable data for all CMMI programs? There are many pros and cons – as a consequence we have questions for discussion tomorrow.

Questions for tomorrow Is it reasonable to ask PIs to make data public, without having the infrastructure in place to make it public? NO, but how then do we address the issue Should NSF fund approaches for facilitating the making of data public without going beyond incremental costs? Creating tools such as NIST’s schema creator – (produces XML readable) that can be conveniently downloaded; Are there similar tools that might be created in the infrastructure area and should NSF invest in the creation of these tools/technology? Do we put money/funding toward the creation of a center or set of centers? Should NSF fund the creation of distributed federated databases? Should NSF provide the funding for making data public as part of the grant as part of supplemental funding? Do any and all of these solutions cut the budget devote to research or does it have the long run consequence of stimulating research?

Questions for tomorrow How do we evaluate the DMP? Should we use criteria similar to those used for intellectual merit and broader impacts to evaluate the DMP? What level of emphasis should be place on the DMP – specific criteria for evaluation versus simply looking at compliance? Why isn’t data sharing one part of the “Broader Impacts”, and hence part of the criteria of for proposal evaluation? (i.e., for all proposals.) Should data be included as broader deliverables? Should there be a federated database registry – to facilitate access to individual databases and citation of those dataset? How do we handle confidential and/or priority data? How do we handle access to data by international “researchers”? How do we address access processes for different