Abstract
This chapter examines current and emerging trends, practices, and technological methods relating to polar research data management. The authors discuss metadata standards, data architecture, semantics, interoperability, dissemination, knowledge mobilization, and organizational policy with respect to how they apply in the context of contemporary issues such as FAIR data principles (i.e., findability, accessibility, interoperability, and reusability), automated metadata harvesting, and data science interests such as data visualization. The chapter begins with a brief history of the beginnings of polar research data management as motivated primarily by domain specific informational needs, followed by description of the progressive changes and emerging criteria that have iteratively shaped disparate ad hoc repositories, propelling them toward the current state of data management that challenges many legacy systems. The Polar Data Catalogue is used as a working example throughout this chapter to illustrate the needs, impacts, challenges, and solutions relating to modern polar research data management. Five specific technical topics are discussed in this chapter. First, metadata standards: The ISO 19115 schema is examined, including its congruence to emerging trends like the schema.org vocabulary, as well as its limitations and future challenges. Second, data architecture: The modelling, representation, and storage of metadata and data are considered with respect to the traditional relational model versus recent NoSQL technologies, particularly from the perspective of their suitability for supporting the requirements discussed in the other sections. Third, semantics and interoperability: The FAIR data principles are discussed with a particular focus on semantics and interoperability, including challenges in implementing schema.org capabilities, search engine optimization, and participation in federated search initiatives with other organizations and partners. Fourth, dissemination and knowledge mobilization: The modernization of data availability and means of data acquisition are explored, with consideration for the growing interest and impact of data science. The emergence of REST APIs and their consumption to support automated harvest for activities such as real-time data visualization are examined as working examples. Fifth, organizational policy: The interplay between organizational policies and technical implementations is examined from the perspective of reciprocal impacts. The chapter concludes with our impressions of what challenges remain to be addressed and what others might arise in the future for polar research data management.
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Acknowledgements
The authors acknowledge financial support from the following organizations and programs: Amundsen Science, Université Laval; CFI-Cyberinfrastructure (Canadian Consortium for Arctic Data Interoperability), University of Calgary; Institutional Support (Canadian Consortium for Arctic Data Interoperability), University of Waterloo; Northern Contaminants Program/Crown-Indigenous Relations and Northern Affairs Canada; Nunavut General Monitoring Plan/Crown-Indigenous Relations and Northern Affairs Canada; and Polar Knowledge Canada/Canadian High Arctic Research Station.
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Vey, G., Van Wychen, W., Verhey, C., Pulsifer, P., LeDrew, E. (2024). Polar Research Data Management: Understanding Technical Implementation and Policy Decisions in the Era of FAIR Data. In: Acadia, S. (eds) Library and Information Sciences in Arctic and Northern Studies. Springer Polar Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-54715-7_8
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