Details on the Launch of the AIC FARM Initiative
(Future of Archives and Records Management)
The Advanced Information Collaboratory (AIC) is proud to launch a new Artificial Intelligence / Machine Learning / Computational Archival Science Initiative which will explore the Future of Archives and Records Management (FARM) through recently funded “seed” Grants and Collaborations.
Details include:
- AI:
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- GRANTS:
- IMLS:
- PROJECT:
- Title: Piloting CT-LASER+: Piloting an Online National Collaborative Network for Integrating Computational Thinking into Library and Archival Education and Practice
- Funding: IMLS Laura Bush 21st Century Librarian (LB21)
- Link: https://www.imls.gov/sites/default/files//grants/re-246334-ols-20/proposals/re-246334-ols-20-full-proposal.pdf
- Dates: 9/01/2020 – 8/30/2022
- Funds: $299,996
- Team: PI: Marciano — co-PI:s Jansen, Piety, Underwood — Collaborators: Conrad, Williams, Kurtz, et al. – 17 partners total
- TOPICS: PII, Metadata extraction using NLP, Entity Resolution, Knowledge Representation (semantic model for representing the information extracted to a Graph Database, Spatial and Temporal Analytics, and Ontologies)
- PARTNERS:
- Densho [Computational Thinking to Unlock the Japanese American WWII Camp Experience]
- Maryland State Archives (MA) [CT-LoS: Computational Treatments to re-member the Legacy of Slavery – “Reasserting Erased Memory” [SAA Research Forum Aug. 5, 2020 — https://ai-collaboratory.net/2020/08/05/establishing-a-research-agenda-for-interdisciplinary-cas/]
- Spelman College
- Puerto Rican Spring
- PROJECT:
- IMLS:
- COLLABORATIONS:
- AURA Network [Archives in the UK/Republic of Ireland & AI]:
- SUMMARY: The overall aim of the network is to apply Artificial Intelligence to archives in order to identify sensitive materials, open up non-confidential records and facilitate the sophisticated organization, analysis and processing of cultural materials. Make digital archives more accessible, produce new knowledge and engage with wider audiences.
- LINK: https://www.aura-network.net/
- PI: Dr. Lise Jaillant, Loughborough U., UK
- ACTIVITIES: Invited to contribute to Workshops #2 and #3:
- #2: AI and Archives: Current Challenges and Prospects of Born-digital archives [Jan. 28-29, 2021]
- #3: Artificial Intelligence and Archives: What comes next? [Mar. 16, 2021]
- AURA Network [Archives in the UK/Republic of Ireland & AI]:
- GRANTS:
- ML:
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- GRANTS:
- ML-FDR:
- PROJECT:
- Title: Machine Learning Strategies for FDR Presidential Library Collections — towards metadata extraction [See: CLIR/AERI July 6, 2020: https://ai-collaboratory.net/projects/ml-fdr/]
- Funding: pending
- Dates: Feb. 1, 2021 – Sep. 30, 2022
- Funds: $409K
- PROJECT:
- ML-GOV:
- PROJECT:
- Title: Metadata Extraction Using NLP for Government Records (in preparation)
- Funding: in preparation
- Funds: $300K
- TOPICS:
- e-records capture, categorization, and management
- auto-categorization of e-mail
- Freedom of Information Act (FOIA) review
- linking facts about people with confidence, and
- open data analysis.
- PROJECT:
- ML-FDR:
- COLLABORATIONS:
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- ESAGRA (Ensuring Scholarly Access to Government Records and Archives)
- SUMMARY: To explore ways that emerging technologies could improve digital access to National Archives records. Virginia Tech will collaborate with the National Archives and other universities to understand the opportunity for using artificial intelligence to search digital records. The funding will be used for a two-day workshop for Virginia Tech librarians, archivists, humanities faculty researchers, and experts in fields such as machine learning and document analysis to help assure access to governments records at the National Archives.
- LINK: https://mellon.org/grants/grants-database/grants/virginia-polytechnic-institute-and-state-university/1910-07229/
- PI: Bill Ingram, University Libraries, Virginia Tech
- FUNDS: Mellon Foundation (Public Knowledge) on 2/22/2020 for $44K
- ACTIVITIES: Spring 2021
- LEADING (LIS Education And Data Science Integrated Network Group)
- SUMMARY: LEADING will prepare a diverse, nation-wide cohort of 50 LIS doctoral students and early career librarians for data science endeavors. LEADING’s model includes community hubs (Montana State University Library, University of California San Diego, and OCLC), along with 14 member nodes, serving as mentoring sites. LEADING Fellows, community hubs, and member nodes ultimately will form a network that will advance and catalyze data science throughout our national digital infrastructure.
- LINK: https://www.imls.gov/sites/default/files//grants/re-246450-ols-20/proposals/re-246450-ols-20-full-proposal.pdf
- PI: Jane Greenberg, Drexel U.
- FUNDING: IMLS Laura Bush 21st Century Librarian (LB21)
- DATES: Nov. 2020 – Oct. 2023
- FUNDS: $887K
- TEAM: AIC: Marciano (board), Jansen (mentor)
- ESAGRA (Ensuring Scholarly Access to Government Records and Archives)
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- GRANTS:
- CAS:
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- GRANTS:
- ARL:
- PROJECT:
- Title: UMD-ARL Alliance for Additive Manufacturing Science
- Funding: Army Research Lab
- Dates: 9/07/2020 – 9/06/2025
- Funds: $22.8M ($2.075M for Marciano team — Task #13: ARL AM Digital Curation and Data Management)
- PI: Dr. Ji-Cheng (JC) Zhao, Chair Department of Materials Sciences and Engineering, UMD
- Co-PIs: Marciano, Underwood — Collaborators: Jansen, Conrad
- TOPICS: Digital Curation, Data Management, Data Mining, Development of a Digital Asset Management System for AM
- PROJECT:
- NSF Convergence:
- PROJECT:
- Title: NSF: Convergence: RAISE: WIN: a Window Into Neuroregulation
- Funding: NSF BCS (Division Behavioral and Cognitive Sciences)
- Dates: 8/22/2019 – 7/31/2022
- Funds: $1M
- PI: Andrea Chiba — co-PI: Todd Coleman — Collaborators: Marciano, Jansen et al.
- SUMMARY: Classroom learning is impacted by a child’s ability to appropriately self-regulate and adjust their state for the task at hand. Self-regulation relies on an individual’s ability to fluidly maintain balance between the sympathetic and parasympathetic nervous system. The primary nerve involved in signaling between systems is the vagus nerve. Best practices for conducting continuous collection of simultaneous behavioral and physiological data from multiple children in a natural classroom setting will be addressed as will analysis of the resultant data from both dynamical systems and information theory perspectives.
- PROJECT:
- NPS:
- PROJECT:
- Title: National Park Service: Developing a Digital Asset Management System for the Archival Holdings of the Mary McLeod Bethune Council House National Historic Site
- Funding: US DOI National Park Service
- Dates: 9/06/2019 – 12/31/2022
- Funds: $516,800
- PI: Marciano — co-PI: Jansen — Collaborators: Conrad, Williams
- SUMMARY: Create a Digital Asset Management System (DAMS) to better preserve and manage the current and future digital assets of the Mary McLeod Bethune Council House National Historic Site. The archival holdings of the site represent the institutional holdings of the National Council for Negro Women and their efforts to create a National Archive for Black Women’s History. The organization was fundamental to the civil rights efforts of the twentieth century and the holdings are an invaluable resource documenting the accomplishments of black women throughout the nineteenth and twentieth century.
- PROJECT:
- ARL:
- COLLABORATIONS:
- DCIP: Digital Curation for Information Professionals certificate program
- UMD iSchool
- PI: Marciano – Collaborator: Conrad
- Dates: Jan. 2021 – Aug. 2021
- DAS: Digital Archives Specialist curriculum and certificate program
- Society of American Archivists (SAA)
- Class: Enhancing Digital Access: Computational Strategies for Digital Research and Reference Service course.
- PI: Marciano – Collaborator: Conrad
- Dates: Summer 2021
- DCIP: Digital Curation for Information Professionals certificate program
- GRANTS: