Exposing Standardization and Consistency Issues in Repository Metadata Requirements for Data Deposition

Kim, Jihyun; Yakel, Elizabeth; Faniel, Ixchel M.

doi:10.5860/crl.80.6.843

Cited by 4 publications

(10 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In order to understand and judge data quality, data reusers need basic or intrinsic metadata (e.g., the identity of data creator, date of creation, and terms of use), information on the context and methods of data creation (Kim, Yakel, and Faniel 2019), and processual information (i.e., paradata)-for example, declaration of selection and exclusion decisions made during the research process (Allison 2008)-about the data creation. Koesten et al (2020) identify common features associated with the reuse potential of datasets in an extensive review of data reuse literature across several disciplines.…”

Section: Needs and Challenges In Data Reusementioning

confidence: 99%

Re-purposing Excavation Database Content as Paradata

Börjesson

Sköld²,

Friberg³

et al. 2022

KULA

View full text Add to dashboard Cite

Although data reusers request information about how research data was created and curated, this information is often non-existent or only briefly covered in data descriptions. The need for such contextual information is particularly critical in fields like archaeology, where old legacy data created during different time periods and through varying methodological framings and fieldwork documentation practices retains its value as an important information source. This article explores the presence of contextual information in archaeological data with a specific focus on data provenance and processing information, i.e., paradata. The purpose of the article is to identify and explicate types of paradata in field observation documentation. The method used is an explorative close reading of field data from an archaeological excavation enriched with geographical metadata. The analysis covers technical and epistemological challenges and opportunities in paradata identification, and discusses the possibility of using identified paradata in data descriptions and for data reliability assessments. Results show that it is possible to identify both knowledge organisation paradata (KOP) relating to data structuring and knowledge-making paradata (KMP) relating to fieldwork methods and interpretative processes. However, while the data contains many traces of the research process, there is an uneven and, in some categories, low level of structure and systematicity that complicates automated metadata and paradata identification and extraction. The results show a need to broaden the understanding of how structure and systematicity are used and how they impact research data in archaeology and in comparable field sciences. The insights into how a dataset’s KOP and KMP can be read is also a methodological contribution to data literacy research and practice development. On a repository level, the results underline the need to include paradata about dataset creation, purpose, terminology, dataset internal and external relations, and eventual data colloquialisms that require explanation to reusers.

show abstract

Section: Needs and Challenges In Data Reusementioning

confidence: 99%

Re-purposing Excavation Database Content as Paradata

Börjesson

Sköld²,

Friberg³

et al. 2022

KULA

View full text Add to dashboard Cite

show abstract

“…Finding no universally applied standard and noting that "56 unique fields were identified from the 15 example data items," the study concludes by reminding the reader that through "robust metadata, curated research data repositories will be discoverable, usable, and interoperable into the future independent of the repository platform" (p. 10). The study by Kim et al (2019) of metadata practices across 20 repositories in three academic disciplines provided the initial impetus for our present study of academic IRs. We borrow heavily from their framework and methodology, particularly, the idea that documentation-data deposit forms and attendant guidelines-"performs the dual purposes of defining a contract between depositors and repositories and gathering information about the deposited data" (p. 843).…”

Section: )mentioning

confidence: 99%

“…After using MS Excel to assign a random number to each row of the master CSV, we sorted the universe in ascending numerical order. Using the methodology from Kim et al (2019) as broad inspiration as well as some targeted elements specific to our inquiry, we developed a coding scheme. Beginning with two IRs randomly selected from the universe, we performed time trial and simplified interrater agreement testing to determine variance in code assignments.…”

Section: Aimsmentioning

confidence: 99%

“…Whereas Kim et al (2019) focused on the role of metadata in data-deposit requirements to enable reuse of data from discipline-based repositories, we sought to build upon their study by examining the role of metadata to promote data discovery in multipurpose (and multidisciplinary) academic IRs. In their analysis of data deposit requirements compiled from previous studies, Kim et al noted that "methodology" is included among the five most common data deposit metadata elements in discipline-specific repositories (p. 845).…”

Section: Figurementioning

confidence: 99%

See 1 more Smart Citation

Do Institutional Repository Deposit Guidelines Deter Data Discovery?

Nicholson¹,

Bennett²

2021

EBLIP

View full text Add to dashboard Cite

Objective – This study uses quantitative methods to determine if the metadata requirements of institutional repositories (IRs) promote data discovery. This question is addressed through an exploration of an international sample of university IRs, including an analysis of the required metadata elements for data deposit, with a particular focus on how these metadata support discovery of research data objects. Methods – The researchers worked with an international universe of 243 IRs. A codebook of 10 variables was developed to enable analysis of the eventual randomly derived sample of 40 institutions. Results – The analysis of our sample IRs revealed that most had metadata standards that offered weak support for data discovery—an unsurprising revelation in view of the fact that university IRs are meant to accommodate deposit and storage of all types of scholarly outputs, only a small percentage of which are research data objects. Most IRs seem to have adopted metadata standards based on the Dublin Core schema, while none of the IRs in our sample used the Data Documentation Initiative metadata that is better suited for deposit and discovery of research datasets. Conclusion – The study demonstrates that while data deposit can be accommodated by the existing metadata requirements of multi-purpose IRs, their metadata practices do little to prioritize data deposit or to promote data discovery. Evidence indicates that data discovery will benefit from additional metadata elements.

show abstract

“…The lack of standardization and the problem of granularity in describing data have been discussed in other studies regarding data documentation and metadata [10][11][12]. Those studies also indicated that documenting an adequate amount of proper contextual information about data would increase the potential for data reuse.…”

Section: Introductionmentioning

confidence: 99%

An analysis of data paper templates and guidelines: types of contextual information described by data journals

Kim¹

2020

Sci Ed

Self Cite

View full text Add to dashboard Cite

Purpose: Data papers are a promising genre of scholarly communication, in which research data are described, shared, and published. Rich documentation of data, including adequate contextual information, enhances the potential of data reuse. This study investigated the extent to which the components of data papers specified by journals represented the types of contextual information necessary for data reuse.Methods: A content analysis of 15 data paper templates/guidelines from 24 data journals indexed by the Web of Science was performed. A coding scheme was developed based on previous studies, consisting of four categories: general data set properties, data production information, repository information, and reuse information.Results: Only a few types of contextual information were commonly requested by the journals. Except data format information and file names, general data set properties were specified less often than other categories of contextual information. Researchers were frequently asked to provide data production information, such as information on the data collection, data producer, and related project. Repository information focused on data identifiers, while information about repository reputation and curation practices was rarely requested. Reuse information mostly involved advice on the reuse of data and terms of use.Conclusion: These findings imply that data journals should provide a more standardized set of data paper components to inform reusers of relevant contextual information in a consistent manner. Information about repository reputation and curation could also be provided by data journals to complement the repository information provided by the authors of data papers and to help researchers evaluate the reusability of data.

show abstract

Exposing Standardization and Consistency Issues in Repository Metadata Requirements for Data Deposition

Cited by 4 publications

References 11 publications

Re-purposing Excavation Database Content as Paradata

Re-purposing Excavation Database Content as Paradata

Do Institutional Repository Deposit Guidelines Deter Data Discovery?

An analysis of data paper templates and guidelines: types of contextual information described by data journals

Contact Info

Product

Resources

About