Meghan Goodchild
Me
Meghan Goodchild’s Bio
Meghan Goodchild is the Research Data Management Librarian at Queen’s University Library and Scholars Portal of the Ontario Council of University Libraries (OCUL). At Queen’s, Meghan is the lead contact for research data management and collaborates with campus partners to improve workflows and services supporting the research data lifecycle. At Scholars Portal, Meghan provides leadership on the team supporting Borealis, the Canadian Dataverse Repository. Meghan represents Queen's and Scholars Portal on various national working groups and committees as part of the Digital Research Alliance of Canada, including the Preservation Expert Group, Curation Expert Group, and Dataverse North Working Group. She holds a Master of Information Studies (MISt) and a PhD in Music Theory from McGill University. In addition to interdisciplinary research experience, she has expertise in research data management, digital preservation, and data visualization.
MISt - McGill University
PhD in Music Theory - McGill University
MA in Music Theory - McGill University
BMus - Queen's University
Goodchild, M., & Huck, J. (In press). Building a community of Canadian Dataverse Collection Administrators: Consortial collaboration and communities of practice. In M. Y. Isuster & A. B. Rod (Eds.), Data culture in academic libraries: A practical guide to building communities, partnerships, and collaborations. Association of College & Research Libraries.
Swartz, M., Shannon, M., & Goodchild, M. (2024). Beyond the paywall: Advocacy, infrastructure, and the future of open access in Canada. In M. E. Norris and S. M. Smith (Eds.), Leading the Way: Envisioning the Future of Higher Education. Queen’s University. Retrieved from: https://ecampusontario.pressbooks.pub/futureofhighereducation/chapter/beyond-the-paywall-advocacy-infrastructure-and-the-future-of-open-access-in-canada/
Goodchild, M., Khair, S., Leahey, A., Newson, K., & Wilson, L. (2023). Research data sharing and reuse in Canada: Practice and policy. In E. Carlisle-Johnston, E. Hill & K. Thompson (Eds.), Research data management in the Canadian context: A guide for practitioners and learners. Canada. Retrieved from: https://ecampusontario.pressbooks.pub/canadardm/chapter/research-data-sharing-and-reuse-in-canada-practice-and-policy/
Donald, B., Cappello, A., Cooper, A., Goodchild, M., & Pero, R. (2023) Queen’s University Research Data Management Survey Report, 2022. Retrieved from: https://qspace.library.queensu.ca/handle/1974/31781
Goodchild, M., Rod, A. B., Khair, S., Jerabek, A., Evering, D., Stieglitz, T. Cain, L., & Harper, L. (2023, June). Better Together: Collaborating on a Community-Led Initiative to Develop a Survey of Canadian Dataverse Administrators. Paper presented at the meeting of International Association for Social Science Information Service and Technology (IASSIST) 2023, 48th Annual Conference of IASSIST, Philadelphia, USA. Retrieved from https://doi.org/10.5281/zenodo.8010797
McAdams, S., Goodchild, M., & Soden, K. (2022). A taxonomy of orchestral grouping effects derived from principles of auditory perception. Music Theory Online. https://mtosmt.org/issues/mto.22.28.3/mto.22.28.3.mcadams.html
Goodchild, M., & Hurley, G. (2019). Integrating Dataverse and Archivematica for Research Data Preservation." In M. Ras, B. Sierman & A. Puggioni (Eds.), iPRES 2019: 16th international conference on digital preservation (pp. 234-244). Retrieved from: https://osf.io/wqbvy/
Goodchild, M., & McAdams, S. (2018). Perceptual processes in orchestration. In E. Dolan & A. Rehding (Eds.), Oxford handbook of timbre (pp. 496-524). Oxford: Oxford University Press. Retrieved from: http://doi.org/10.1093/oxfordhb/9780190637224.013.10
Goodchild, M., & Zhao, J. (2017). Sustainability engineering collection assessment: A mixed-method analysis. Science & Technology Libraries, 36(2), 153-169. https://doi.org/10.1080/0194262X.2017.1298493
Goodchild, M. (2017). Digital music libraries: Librarian perspectives and the challenges ahead. CAML Review 45 (2/3), 32–57. https://doi.org/10.25071/1708-6701.40305
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