Resurfacing Historical Scientific Data: A Case Study Involving Fruit Breeding Data

• Main Authors: Shannon L. Farrell, Lois G. Hendrickson, Kristen L. Mastel, Katherine Adina Allen, Julia A. Kelly
• Format: Article
• Language: English
• Published: University of Massachusetts Medical School, Lamar Soutter Library 2019-12-01
• Series: Journal of eScience Librarianship
• Subjects: scholarly communication; scholarly publishing; data management; analog data; scientific data; data preservation; data reuse; digital preservation; data collection
• Online Access: https://escholarship.umassmed.edu/jeslib/vol8/iss2/5

<p><strong>Objective</strong>: The objective of this paper is to illustrate the importance and complexities of working with historical analog data that exists on university campuses. Using a case study of fruit breeding data, we highlight issues and opportunities for librarians to help preserve and increase access to potentially valuable data sets.</p> <p><strong>Methods</strong>: We worked in conjunction with researchers to inventory, describe, and increase access to a large, 100-year-old data set of analog fruit breeding data. This involved creating a spreadsheet to capture metadata about each data set, identifying data sets at risk for loss, and digitizing select items for deposit in our institutional repository.</p> <p><strong>Results/Discussion</strong>: We illustrate that large amounts of data exist within biological and agricultural sciences departments and labs, and how past practices of data collection, record keeping, storage, and management have hindered data reuse. We demonstrate that librarians have a role in collaborating with researchers and providing direction in how to preserve analog data and make it available for reuse. This work may provide guidance for other science librarians pursing similar projects.</p> <p><strong>Conclusions</strong>: This case study demonstrates how science librarians can build or strengthen their role in managing and providing access to analog data by combining their data management skills with researchers’ needs to recover and reuse data.</p> <p><em>The substance of this article is based upon a panel presentation at RDAP Summit 2019.</em></p>