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Research, Scholarly, and Creative Achievements

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Papers in refereed journals

    1. [1]Ingram, W.A. et al. 2024. Building datasets to support information extraction and structure parsing from electronic theses and dissertations. International Journal on Digital Libraries. (May 2024). DOI:https://doi.org/10.1007/s00799-024-00395-4.
    2. [2]Li, L. et al. 2020. Teaching Natural Language Processing through Big Data Text Summarization with Problem-Based Learning. Data and Information Management. 4, 1 (Mar. 2020), 18–43. DOI:https://doi.org/10.2478/dim-2020-0003.
    3. [3]Ingram, W.A. et al. 2019. Summarizing ETDs with deep learning. Cadernos BAD. 1, (2019), 46–52. DOI:https://doi.org/10.48798/cadernosbad.2014.
    4. [4]Fallaw, C. et al. 2016. Overly Honest Data Repository Development. The Code4Lib Journal. 34 (2016).
    5. [5]Habing, T. et al. 2009. Developments in Digital Preservation at the University of Illinois: The Hub and Spoke Architecture for Supporting Repository Interoperability and Emerging Preservation Standards. Library Trends. 57, 3 (May 2009), 556–579. DOI:https://doi.org/10.1353/lib.0.0052.

Papers in refereed conference proceedings

    1. [1]Ingram, W.A. et al. 2023. AI and Public Archives: Collaborative Leadership for Responsible Adoption. Proceedings of the 23rd ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL 2023) (Jun. 2023), 323–324.
    2. [2]Chekuri, S. et al. 2023. Integrated Digital Library System for Long Documents and their Elements. Proceedings of the 23rd ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL 2023) (Jun. 2023), 13–24.
    3. [3]Choudhury, M.H. et al. 2023. MetaEnhance: Metadata Quality Improvement for Electronic Theses and Dissertations of University Libraries. Proceedings of the 23rd ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL 2023) (Jun. 2023), 61–65.
    4. [4]Ingram, W. et al. 2023. Maximizing Equitable Reach and Accessibility of ETDs. Proceedings of the 23rd ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL 2023) (Jun. 2023), 256–257.
    5. [5]Ahuja, A. et al. 2023. A New Annotation Method and Dataset for Layout Analysis of Long Documents. Companion Proceedings of the ACM Web Conference 2023 (WWW ’23 Companion) (Apr. 2023), 834–842.
    6. [6]Banerjee, B. et al. 2022. Applications of Data Analysis on Scholarly Long Documents. 2022 IEEE International Conference on Big Data (Big Data) (Dec. 2022), 2473–2481.
    7. [7]Salsabil, L. et al. 2022. A Study of Computational Reproducibility Using URLs Linking to Open Access Datasets and Software. Companion Proceedings of the Web Conference 2022 (WWW ’22 Companion) (Apr. 2022), 5.

Papers presented at professional meetings

    1. [1]Ingram, W.A. et al. 2022. Electronic Theses and Dissertations: A Research Corpus of Scholarly Big Data. GL24 — Twenty-Fourth International Conference on Grey Literature, GreyNet International.
    2. [2]Ahuja, A. et al. 2022. Analyzing and Navigating ETDs Using Topic Models. 25th International Symposium on Electronic Theses and Dissertations.
    3. [3]Banerjee, B. et al. 2021. Applications of Mining ETDs. 24th International Symposium on Electronic Theses and Dissertations.
    4. [4]Chen, Y. and Ingram, W.A. 2021. Why and How We Went Serverless, and How You Can Too. CNI: Coalition for Networked Information Spring 2021 Membership Meeting.
    5. [5]Ingram, W.A. 2020. Mining ETDs for Trends in Graduate Research. CNI: Coalition for Networked Information Fall 2020 Membership Meeting.
    6. [6]Ingram, W.A. 2019. Bringing Computational Access to Book-length Documents Via an ETD Pilot. CNI: Coalition for Networked Information Fall 2019 Membership Meeting.

Workshop facilitation

    1. [1]Ingram, W.A. and others 2022. Leading the Future of AI and Public Archives: Toward a Shared AI Ethics Framework. Virtual workshop organized by Virginia Tech, Smithsonian, Library of Congress, and NARA.
    2. [2]Ingram, W.A. and others 2022. Leading the Future of AI and Public Archives. Virtual workshop organized by Virginia Tech, Smithsonian, Library of Congress, and NARA.
    3. [3]Ingram, W.A. 2021. Ensuring Scholarly Access to Government Archives and Records. Five-day virtual workshop organized by Virginia Tech and NARA, sponsored by the Andrew W. Mellon Foundation.

Conference tutorials

    1. [1]Ingram, W.A. and Fox, E.A. 2020. Preparing Code and Data for Computational Reproducibility. Half-day tutorial at ACM/IEEE Joint Conference on Digital Libraries (JCDL 2020).
    2. [2]Fox, E.A. and Ingram, W.A. 2020. Introduction to Digital Libraries. Half-day tutorial at ACM/IEEE Joint Conference on Digital Libraries (JCDL 2020).
    3. [3]Ingram, W.A. and Fox, E.A. 2019. Preparing Code and Data for Computational Reproducibility: A Hands-On Workshop. 22nd International Symposium on Electronic Theses and Dissertations (ETD 2019).

Other papers and reports

    1. [1]Ingram, W.A. and Johnson, S.A. 2021. Ensuring Scholarly Access to Government Archives and Records. Virginia Tech.
    2. [2]Aromando, J. et al. 2020. Classification and Extraction of Information from ETD Documents. Virginia Tech.
    3. [3]Ahuja, N. et al. 2018. Big Data Text Summarization: Using Deep Learning to Summarize Theses and Dissertations. Virginia Tech.