|The Metadata Community — Supporting Innovation in Metadata Design, Implementation & Best Practices|
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Upcoming DCMI Events
» 8 April 2015: DCMI/ASIS&T Webinar: Approaches to Making Dynamic Data Citable: Recommendations of the RDA Working Group with Andreas Rauber, Department of Software Technology and Interactive Systems at the Vienna University of Technology
» 13 May 2015: DCMI/ASIS&T Webinar: From 0 to 60 on SPARQL queries in 50 minutes with Ethan Gruber, Database Developer for the American Numismatic Society
» 1-5 September 2015: DC-2015, São Paulo, Brazil (Host: UNESP (Universidade Estadual Paulista—São Paulo State University)
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ASIS&T Upcoming Events
» 6–10 November 2015: 2015 Annual Meeting
St. Louis, Missouri
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|Current | 12 January 2015 | 28 November 2014 | 24 October 2014 | 29 August 2014 | 22 July 2014 | 18 June 2014 | 14 May 2014 | 16 April 2014 | 19 March 2014|
2015-03-16, Being able to reliably and efficiently identify entire or subsets of data in large and dynamically growing or changing datasets constitutes a significant challenge for a range of research domains. In order to repeat an earlier study, to apply data from an earlier study to a new model, we need to be able to precisely identify the very subset of data used. While verbal descriptions of how the subset was created (e.g. by providing selected attribute ranges and time intervals) are hardly precise enough and do not support automated handling, keeping redundant copies of the data in question does not scale up to the big data settings encountered in many disciplines today. Furthermore, we need to be able to handle situations where new data gets added or existing data gets corrected or otherwise modified over time. Conventional approaches, such as assigning persistent identifiers to entire data sets or individual subsets or data items, are thus not sufficient. In this webinar, Andreas Rauber will review the challenges identified above and discuss solutions that are currently elaborated within the context of the working group of the Research Data Alliance (RDA) on Data Citation: Making Dynamic Data Citeable. The approach is based on versioned and time-stamped data sources, with persistent identifiers being assigned to the time-stamped queries/expressions that are used for creating the subset of data. We will further review results from the first pilots evaluating the approach. Additional information and registration available at http://dublincore.org/resources/training/#2015rauber.
2015-03-16, The Program Committee for DC-2015, to be held 1-5 September 2015 in São Paulo, Brazil, has decided to extend the deadline for submission for both the Technical and Professional Programs to 11 April 2015. The extended call can be found at http://purl.org/dcevents/dc-2015/cfp.
2015-02-23, DCMI and the DC-2015 host, São Paulo State University, are please to announce that session proposals as well as the presentation language of sessions in the Professional Program at DC-2015 may be in either Portuguese or English. Depending on the language of the session presenters, simultaneous English/Portuguese or Portuguese/English translation will be provided. Tracks in the Professional Program include special topic sessions and panels, half- and full-day tutorials, workshops, and best practice posters and demonstrations.The call for participation in both the Professional and Technical Programs remain open until 28 March 2015. The call for participation can be found at http://purl.org/dcevents/dc-2015/cfp.
The Dublin Core Metadata Initiative, or "DCMI", is an open organization supporting innovation in metadata design and best practices across the metadata ecology. DCMI's activities include work on architecture and modeling, discussions and collaborative work in DCMI Communities and DCMI Task Groups, global conferences, meetings and workshops, and educational efforts to promote widespread acceptance of metadata standards and best practices.
DCMI maintains a number of formal and informal liaisons and relationships with standards bodies and other metadata organizations.
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