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6th COMPUTATIONAL ARCHIVAL SCIENCE (CAS) WORKSHOP

6th COMPUTATIONAL ARCHIVAL SCIENCE (CAS) WORKSHOP

6th COMPUTATIONAL ARCHIVAL SCIENCE (CAS) WORKSHOP

See: https://ai-collaboratory.net/cas/cas-workshops/2021-6th-cas-workshop [ai-collaboratory.net]

Dec 15-18 (workshop date TBD), 2021, Atlanta, Orlando FL (now held virtually)

 

COMPUTATIONAL ARCHIVAL SCIENCE: digital records in the age of big data

PART OF: IEEE Big Data 2021 -- http://bigdataieee.org/BigData2021/ [bigdataieee.org]

All papers accepted for the workshop will be included in the Conference Proceedings published by the IEEE Computer Society Press. In addition to standard papers, the workshop (and the call for papers) will incorporate a student poster session for PhD and Master’s level students.

 

IMPORTANT DATES:

 

Oct. 22, 2021: Electronic submission of workshop papers

Nov. 1, 2010: Notification of paper acceptance

Nov. 15, 2020: Camera-ready of accepted papers

Dec. 15-18 (TBD): Workshop

INTRODUCTION TO WORKSHOP [See: CAS Portal [ai-collaboratory.net] for previous submissions]:

The large-scale digitization of analogue archives, the emerging diverse forms of born-digital archive, and the new ways in which researchers across disciplines (as well as the public)wish to engage with archival material, are resulting in disruptions to transitional archival theories and practices. Increasing quantities of ‘big archival data’ present challenges for the practitioners and researchers who work with archival material, but also offer enhanced possibilities for scholarship, through the application both of computational methods and tools to the archival problem space and of archival methods and tools to computational problems such as trusted computing, as well as, more fundamentally, through the integration of computational thinking with archival thinking.

RESEARCH TOPICS COVERED:

Topics covered by the workshop include, but are not restricted to, the following:

  • Application of analytics to archival material, including AI, ML, text-mining, data-mining, sentiment analysis, network analysis.
  • Analytics in support of archival processing, including e-discovery, identification of personal information, appraisal, arrangement and description.
  • Scalable services for archives, including identification, preservation, metadata generation, integrity checking, normalization, reconciliation, linked data, entity extraction, anonymization and reduction.
  • New forms of archives, including Web, social media, audiovisual archives, and blockchain.
  • Cyber-infrastructures for archive-based research and for development and hosting of collections
  • Big data and archival theory and practice
  • Digital curation and preservation
  • Crowd-sourcing and archives
  • Big data and the construction of memory and identity
  • Specific big data technologies (e.g. NoSQL databases) and their applications
  • Corpora and reference collections of big archival data
  • Linked data and archives
  • Big data and provenance
  • Constructing big data research objects from archives
  • Legal and ethical issues in big data archives

 

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