IMLS National Forum on Data Mining Research Using In-copyright and Limited-access Text Datasets: Discussion Paper, Forum Statements, and SWOT analyses
Author(s)
Dickson, Eleanor
Senseney, Megan
Namachchivaya, Beth
Ludäscher, Bertram
Contributor(s)
Althaus, Scott
Borgman, Christine L.
Butler, Brandon
Cormier, Marc
Cox, Krista
Downie, J. Stephen
Feeney, Patricia
Guibault, Lucie
Horstmann, Wolfram
Lynch, Clifford
Murray-Rust, Peter
Orcutt, Darby
Padilla, Thomas
Paolillo, Michelle
Piper, Andrew
Sag, Matthew
Samberg, Rachael
Shipman, Jean
Strawn, George
Uhlir, Paul F.
Waibel, Günter
Wittenberg, Kate
Worthey, Glen
Issue Date
2018-05-24
Keyword(s)
text data mining
intellectual property
copyright
data use and access
terms and conditions
research data services
Abstract
This discussion paper foregrounds discussion at “Text Mining with Limited-Access Data,” a National Forum funded by the Institute for Museum and Library Services. The forum convened twenty-five stakeholders for a day-and-a-half long meeting to explore the current landscape for text data mining using texts that are under copyright or protected by licenses, including terms of use licenses, that limit access and use. The stakeholders include librarians, researchers, legal experts, content providers, and representatives of professional organizations. Prior to the forum, project team members interviewed stakeholders to learn
more about their perspectives on research that employs use-limited text data, and to guide forum participants in drafting written statements and SWOT (Strength, Weakness, Opportunity, and Threat) analyses. This paper reports on the progress of the National Forum project, as well as synthesizes participant responses to the interviews and in their forum statements. It intends to establish a shared vocabulary and key points of consideration for the forum. Initial forum statements and SWOT analyses are included as a separate document.
Publisher
Center for Informatics Research in Science and Scholarship
Type of Resource
text
Language
en
Permalink
http://hdl.handle.net/2142/100055
Sponsor(s)/Grant Number(s)
IMLS LG-73-17-0070-17
Copyright and License Information
Creative Commons Attribution 2.0 Generic (CC BY 2.0)
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