• Modeling Digital Humanities Collections as Research Objects

    Author(s):
    Katrina Fenlon (see profile)
    Date:
    2019
    Subject(s):
    Collections, Digital publishing, Scholarly communication, Scholarly cyberinfrastructure, Digital archives
    Item Type:
    Article
    Tag(s):
    research objects
    Permanent URL:
    http://dx.doi.org/10.17613/jmns-kr78
    Abstract:
    Advancing digital libraries to increase the sustainability and usefulness of digital scholarship depends on identifying and developing data models capable of representing increasingly complex scholarly products. This paper considers the potential for an emergent model of scientific communication, the research objects data model, to accommodate the complexities of digital humanities collections. Digital humanities collections aggregate and enrich diverse sources of evidence and context, serving simultaneously as "publications" and dynamic, interactive platforms for research. The research objects model is an alternative to traditional formats of publication, facilitating aggregation and description of all of the inputs and outputs of a research process, ranging from datasets to papers to executable code. This model increasingly underpins research infrastructures in some scientific domains, yet its efficacy for representing humanities scholarship, and for undergirding humanities cyberinfrastructure, remains largely untested. This study offers a qualitative content analysis of digital humanities collections relying on a content/context analytical framework for characterizing collection components and their interrelationships. This study then maps those components and relationships into a research objects model to identify the model’s strengths and limitations for representing diverse digital humanities scholarship.
    Notes:
    Presented at the ACM/IEEE Joint Conference on Digital Libraries 2019. Preprint of article published in Proceedings of ACM Conference JCDL '19.
    Metadata:
    Status:
    Published
    Last Updated:
    1 month ago
    License:
    Attribution-NonCommercial-NoDerivatives
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