Supporting Computational Research on Large Digital Collections
| dc.contributor.author | Ruest, Nick | |
| dc.contributor.author | Bailey, Jefferson | |
| dc.date.accessioned | 2022-12-13T13:18:39Z | |
| dc.date.available | 2022-12-13T13:18:39Z | |
| dc.date.issued | 2022-12-12 | |
| dc.description.abstract | Every year more and more scholars conduct research on terabytes and even petabytes of digital library and archive collections using computational methods such as data mining, natural language processing, and machine learning (ML), which poses many challenges for supporting research libraries. In 2020, Internet Archive Research Services and Archives Unleashed received funding to combine their tools enabling computational analysis of web and digital archives to support joint technology development, community building, and selected research projects by sponsored cohort teams. The session will feature programs that are building technologies, resources, and communities to support data-driven research, and it will review the beta platform, Archives Research Compute Hub, and discuss working with digital humanities, social and computer science researchers, and industry partners in support of large-scale digital research methods. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10315/40580 | |
| dc.language.iso | en | en_US |
| dc.rights | Attribution 4.0 International | * |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
| dc.title | Supporting Computational Research on Large Digital Collections | en_US |
| dc.type | Presentation | en_US |