Research data and metadata curation as institutional issues

Mayernik, Matthew S.

doi:10.1002/asi.23425

Cited by 61 publications

(61 citation statements)

References 94 publications

(97 reference statements)

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“…data sets) and relationships (e.g. citation relationships) in various ways (Mayernik, et al, ). An additional challenge in characterizing relationships is that different uses of relationship information might require different levels of description about the entities at either end of the relationships.…”

Section: Discussionmentioning

confidence: 99%

“…The information in these systems comes from a combination of existing metadata databases and newly created metadata. The resources are represented via the Semantic Web data model using multiple ontologies (Mayernik, et al, ). In the Semantic Web, ontologies are used to define entity types (classes), and the relationships between them (properties).…”

Section: Investigations Into Linkingmentioning

confidence: 99%

“…In our project, no single ontology supported our project needs. We thus combined components from a couple of different ontologies and created custom ontology extensions as necessary to fill gaps (Mayernik, et al, ).…”

Section: Investigations Into Linkingmentioning

confidence: 99%

“…Each cell further breaks down the work requirements into "technical" and "institutional" work. As I discussed in a prior paper (Mayernik, 2016), scholarly resource curation encompasses far more than just technical work. Institutional factors like community norms and expectations, the availability of intermediaries to support curation work, standards development and adoption, and individual routines all play important roles in determining the success of curation efforts.…”

Section: Looking Forward and Backward In Timementioning

confidence: 99%

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Scholarly resource linking: Building out a “relationship life cycle”

Mayernik

2018

Proc. Assoc. Info. Sci. Tech.

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Scholarly resources, including publications, software, data sets, and instruments, are created in an iterative and interrelated fashion. Managing the relationships that exist among and between such resources is a central requirement for information systems. Practically, however, many scholarly resources exist online as discrete entities, divorced from other resources to which they are intimately related. A robust system for linking scholarly resources in a broad and sustainable fashion will have to navigate a set of complex and interrelated requirements. This paper presents results and insights from three different projects that focused on supporting more robust linkages among scholarly resources. The discussion details key technical and institutional challenges looking forward and backward in time across what might be considered to be a “relationship life cycle”: identifying, validating, characterizing, and preserving relationships. The goal of the paper is to help guide new research initiatives and operational services focused on integrating relationship information into the scholarly record.

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Section: Discussionmentioning

confidence: 99%

Section: Investigations Into Linkingmentioning

confidence: 99%

Section: Investigations Into Linkingmentioning

confidence: 99%

Section: Looking Forward and Backward In Timementioning

confidence: 99%

See 2 more Smart Citations

Scholarly resource linking: Building out a “relationship life cycle”

Mayernik

2018

Proc. Assoc. Info. Sci. Tech.

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“…A center has a welldefined mission to support research efforts whose size, duration, equipment, and technical specificity are beyond the scope of a single research enterprise. National data or science centers are formal organizations that institutionalize the management and creation of research data (Mayernik, 2015). National data centers were originally conceived as serving particular designated user communities.…”

Section: Introductionmentioning

confidence: 99%

Scientific Knowledge Mobilization: Co-evolution of Data Products and Designated Communities

Baker

Duerr²,

Parsons

2016

IJDC

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Digital data are accumulating rapidly, yet issues relating to data production remain unexamined. Data sharing efforts in particular are nascent, disunited and incomplete. We investigate the development of data products tailored for diverse communities with differing knowledge bases. We explore not the technical aspects of how, why, or where data are made available, but rather the socio-scientific aspects influencing what data products are created and made available for use. These products differ from compact data summaries often published in journals. We report on development by a national data center of two data collections describing the changing polar environment. One collection characterizes sea ice products derived from satellite remote sensing data and development unfolds over three decades. The second collection characterizes the Greenland Ice Sheet melt where development of an initial collection of data products over a period of several months was informed by insights gained from earlier experience. In documenting the generation of these two collections, a data product development cycle supported by a data product team is identified as key to mobilizing scientific knowledge. The collections reveal a co-evolution of data products and designated communities where community interest may be triggered by events such as environmental disturbance and new modes of communication. These examples of data product development in practice illustrate knowledge mobilization in the earth sciences; the collections create a bridge between data producers and a growing number of audiences interested in making evidence-based decisions.

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Digital data archives as knowledge infrastructures: Mediating data sharing and reuse

Borgman

Scharnhorst

Golshan

2019

Asso for Info Science & Tech

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Digital archives are the preferred means for open access to research data. They play essential roles in knowledge infrastructures -robust networks of people, artifacts, and institutions -but little is known about how they mediate information exchange between stakeholders. We open the "black box" of data archives by studying DANS, the Data Archiving and Networked Services institute of The Netherlands, which manages 50+ years of data from the social sciences, humanities, and other domains. Our interviews, weblogs, ethnography, and document analyses reveal that a few large contributors provide a steady flow of content, but most are academic researchers who submit datasets infrequently and often restrict access to their files. Consumers are a diverse group that overlaps minimally with contributors. Archivists devote about half their time to aiding contributors with curation processes and half to assisting consumers. Given the diversity and infrequency of usage, human assistance in curation and search remains essential. DANS' knowledge infrastructure encompasses public and private stakeholders who contribute, consume, harvest, and serve their data -many of whom did not exist at the time the DANS collections originated -reinforcing the need for continuous investment in digital data archives as their communities, technologies, and services evolve.

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Research data and metadata curation as institutional issues

Cited by 61 publications

References 94 publications

Scholarly resource linking: Building out a “relationship life cycle”

Scholarly resource linking: Building out a “relationship life cycle”

Scientific Knowledge Mobilization: Co-evolution of Data Products and Designated Communities

Digital data archives as knowledge infrastructures: Mediating data sharing and reuse

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