Announcing the final program for the 4th COMPUTATIONAL ARCHIVAL SCIENCE (CAS) WORKSHOP at the 2019 IEEE Big Data Conference in Los Angeles, on Wednesday, December 11, 2019. See: https://dcicblog.umd.edu/cas/ieee-big-data-2019-4th-cas-workshop/
Featuring 16 talks with authors from 7 countries: USA (UMD, MIT, UNC Chapel Hill, UCLA, Stanford, Indiana U., California State University Channel Islands, Fordham U., Drinker Biddle), Canada (UBC, Artefactual, Patriot One Technologiesl Systems, North Vancouver Museum and Archives), UK (King’s College London), Switzerland (Lucerne U.), Portugal (INESC-ID), The Netherlands (Dutch Digital Heritage Network), and South Africa (U.of South Africa).
- Automated Knowledge Base Construction Frameworks, Big Data, Computational Archival Science, Information Extraction, Software Architecture
- Disposition, appraisal, smart contracts, blockchain systems
- Ontologies; vocabularies; semantics; data variety; data volume; linked data
- Fake videos, trustworthiness of digital records, authenticity of videos, archival science.
- Linked Data Platform, Memento, Fedora Repository, Apache Cassandra, Digital Repositories, Distributed Database
- Computational Thinking, Digital Curation, Computational Archival Science (CAS), PII, Privacy
- Computational archival science, computer games, software development, documentation, history
- Business actors, enterprise architecture practice, information technology actors, modeling, records management capabilities
- Computational Thinking, Digital Curation, Computational Archival Science (CAS), Japanese American WWII Incarceration Camps.
- Context, auto-classification, classification, machine learning, functions
- Computational thinking, archival science
- Radio preservation, big data, Radio Preservation Task Force, archival representation, ethics of access, dynamic design
- Representations of marginalized populations, Racial implications of reproductive technology
- Building an international CAS research network
- Moving to digital archives and the AI Perspective
- An Analysis of Computational Thinking Practices in CAS
It also builds on three earlier workshops on ‘Big Humanities Data’ organized by the same chairs at the 2013-2015 conferences, and more directly on a KCL-UMD symposium held in April 2016 at the University of Maryland.
The workshop explores the conjunction (and its consequences) of emerging methods and technologies around big data with archival practice and new forms of analysis and historical, social, scientific, and cultural research engagement with archives. We aim to identify and evaluate current trends, requirements, and potential in these areas, to examine the new questions that they can provoke, and to help determine possible research agendas for the evolution of computational archival science in the coming years. At the same time, we will address the questions and concerns scholarship is raising about the interpretation of ‘big data’ and the uses to which it is put, in particular appraising the challenges of producing quality – meaning, knowledge and value – from quantity, tracing data and analytic provenance across complex ‘big data’ platforms and knowledge production ecosystems, and addressing data privacy issues.