From Acquisition to Access to Archiving - Creating Library Data Services that Provide End-to-End Support for Library Acquired Data
dc.audience | Audience::Preservation and Conservation Section | |
dc.audience | Audience::Big Data Special Interest Group | |
dc.conference.sessionType | Preservation and Conservation with Big Data SIG | |
dc.conference.venue | Megaron Athens International Conference Centre (MAICC) | |
dc.contributor.author | Kasianovitz, Kris | |
dc.contributor.author | Williamsen, Julie | |
dc.date.accessioned | 2025-09-24T09:13:38Z | |
dc.date.available | 2025-09-24T09:13:38Z | |
dc.date.issued | 2017 | |
dc.description.abstract | This case study outlines the challenges and opportunities that we are currently facing with data management of acquired datasets at the Stanford Graduate School of Business (GSB) Library and the Stanford Libraries (SUL) that impact data preservation. We will compare and contrast our current approaches for managing data in our respective environments; discuss what is working and what needs to be changed or approached in a different way. We will also discuss how we envision a library data service that seeks to employ standard approaches, like the FAIR principles, i.e. findable, accessible, interoperable, and reusable. We will identify ways to unify our approaches across our libraries so that we are not working in isolation of each other. We aim to provide considerations that will aid others facing these same data curation and preservation issues. | en |
dc.identifier.citation | Anonymous. (2015, May 11). FORCE11 Manifesto. Retrieved June 6, 2019, from FORCE11 website: https://www.force11.org/about/manifesto Association of Public and Land Grant Universities. Public Access. Retrieved March 8, 2019, from https://www.aplu.org/projects-and-initiatives/research-science-and-technology/public-access/index.html Carlson, J., & Johnston, L. (Eds.). (2015). Data information literacy: Librarians, data, and the education of a new generation of researchers. West Lafayette, Indiana: Purdue University Press. Carnegie Mellon University Libraries. (n.d.). Preparing Your Data. Retrieved May 7, 2019, from https://library.cmu.edu/kilthub/prepare-data Castiglione, J. (2008a). Environmental scanning: An essential tool for twenty-first century librarianship. Library Review; Glasgow, 57(7), 528–536. http://dx.doi.org.stanford.idm.oclc.org/10.1108/00242530810894040 CLIR. (n.d.). Data Curation. Retrieved March 11, 2019, from CLIR website: https://www.clir.org/initiatives-partnerships/data-curation/ Committee, A. R. P. and R. (n.d.). 2018 top trends in academic libraries: A review of the trends and issues affecting academic libraries in higher education. Research Planning and Review Committee, College & Research Libraries News. https://doi.org/10.5860/crln.79.6.286 Gornall, Will and Strebulaev, Ilya A., Squaring Venture Capital Valuations with Reality (April 20, 2019). Journal of Financial Economics (JFE), Forthcoming. Available at SSRN: http://dx.doi.org/10.2139/ssrn.2955455 ICPSR. (n.d.). Data Management & Curation. Retrieved April 12, 2019, from https://www.icpsr.umich.edu/icpsrweb/content/datamanagement/index.html Indiana University Network Science Institute. (n.d.). CADRE: Collaborative Archive Data Research Environment. Retrieved May 24, 2019, from Indiana University Network Science Institute website: https://iuni.iu.edu/resources/cadre Johnston, L. (2017). Curating research data. Retrieved March 11, 2019 from http://www.ala.org/acrl/sites/ala.org.acrl/files/content/publications/booksanddigitalresources/digital/9780838988596_crd_v1_OA.pdf Kellam, L. M., & Thompson, K. (Eds.). (2016). Databrarianship: The academic data librarian in theory and practice. Chicago, Illinois: Association of College and Research Libraries, a division of the American Library Association. Knight, M. (2017). What is Data Curation? Retrieved March 11, 2019 from https://www.dataversity.net/what-is-data-curation/ Libfocus. (2016). SWOT analysis for libraries - a compilation piece. Retrieved July 28, 2019, from https://www.libfocus.com/2016/11/swot-analysis-for-libraries-compilation.html National Science Board, & National Science Foundation. (2005). Long-Lived Digital Data Collections: Enabling Research and Education in the 21st Century. Retrieved March 12, 2019, from https://www.nsf.gov/geo/geo-data-policies/nsb-0540-1.pdf Open Knowledge Network. (n.d.). The Frictionless Data Field Guide. Retrieved May 21, 2019, from https://frictionlessdata.io/field-guide/ Pryor, G. (2012). Managing Research Data. London: Facet Publishing. Ray, J. M. (Ed.). (2014). Research data management: Practical strategies for information professionals. West Lafayette, Indiana: Purdue University Press. Ribeiro, C., Silva, J. R. da, Castro, J. A., Amorim, R. C., Lopes, J. C., & David, G. (2018). Research Data Management Tools and Workflows: Experimental Work at the University of Porto. IASSIST Quarterly, 42(2), 1–16. https://doi.org/10.29173/iq925 Rice, R. (2016). The data librarian’s handbook. London: Facet Publishing. Sorkin, Andrew, How Valuable is a Unicorn? Maybe Not as Much as It Claims to Be, New York Times (April 16, 2017), https://www.nytimes.com/2017/10/16/business/how-valuable-is-a-unicorn-maybe-not-as-much-as-it-claims-to-be.html Stanford Research Administration. DoResearch. Retrieved July 28, 2019, from https://doresearch.stanford.edu/research-administration Stanford Research Administration. Uniform Guidance: Concepts That Have Changed. (n.d.). Retrieved July 28, 2019, from https://doresearch.stanford.edu/research-administration/major-topics/uniform-guidance-concepts-are-changing Stanford Research Computing Center. Systems & Services Overview Retrieved May 28, 2019, from https://srcc.stanford.edu/systems-services-overview Stanford University I.T. Services. Retrieved July 28, 2019, from https://uit.stanford.edu/services SWOT analysis. (2019). Wikipedia. Retrieved from May 21, 2019 from https://en.wikipedia.org/w/index.php?title=SWOT_analysis&oldid=906110045 Tenopir, C., Talja, S., Horstmann, W., Late, E., Hughes, D., Pollock, D., Allard, S. (2017). Research Data Services in European Academic Research Libraries. LIBER Quarterly, 27(1), 23–44. https://doi.org/10.18352/lq.10180 University of Minnesota Libraries. (2015). The Supporting Documentation for Implementing the Data Repository for the University of Minnesota (DRUM): A Business Model, Functional Requirements, and Metadata Schema. Retrieved from the University of Minnesota Digital Conservancy, http://hdl.handle.net/11299/171761. University of Oregon Libraries. (n.d.). Data Management Best Practices Guide. Retrieved July 28, 2019, from https://library.uoregon.edu/research-data-management/best-practices Virginia Tech. (n.d.). Data Management & Curation. Retrieved April 12, 2019, from https://lib.vt.edu/content/lib_vt_edu/en/research-learning/research-data-management-curation.html Wilkinson, M. D., Dumontier, M., Aalbersberg, Ij. J., Appleton, G., Axton, M., Baak, A., Mons, B. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, 160018. Wilkinson, M. D., Sansone, S.-A., Schultes, E., Doorn, P., Bonino da Silva Santos, L. O., & Dumontier, M. (2018). A design framework and exemplar metrics for FAIRness. Scientific Data, 5, 180118. https://doi.org/10.1038/sdata.2018.118 Young, A. (2019, April 24). Introducing the Contractual Wheel of Data Collaboration. Retrieved May 15, 2019, from Medium website: https://medium.com/data-stewards-network/introducing-the-contractual-wheel-of-data-collaboration-ca4c55938e7a | |
dc.identifier.relatedurl | https://2019.ifla.org/ | |
dc.identifier.uri | https://repository.ifla.org/handle/20.500.14598/6634 | |
dc.language.iso | en | |
dc.rights | Attribution 4.0 International | |
dc.rights.accessRights | open access | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.subject.keyword | Data Management Lifecycle | |
dc.subject.keyword | Data Curation | |
dc.subject.keyword | Research Data | |
dc.subject.keyword | Data Services | |
dc.subject.keyword | Academic Libraries | |
dc.title | From Acquisition to Access to Archiving - Creating Library Data Services that Provide End-to-End Support for Library Acquired Data | en |
dc.type | Article | |
ifla.Unit | Section:Preservation and Conservation Section | |
ifla.Unit | Section::Big Data Special Interest Group | |
ifla.oPubId | https://library.ifla.org/id/eprint/2583/ |
Files
Original bundle
1 - 1 of 1