Aggregate control of scientific data

Niu, Jinfang

doi:10.1080/23257962.2016.1145578

Cited by 5 publications

(6 citation statements)

References 12 publications

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“…Unlike a present-day project with a set list of tables and fields based on the capture of data from a static data set, the project details data from a moving and constantly changing data structure target. Existing metadata schemas that are used commonly in the information science field or domain-centric schemas are not appropriate for our data sets because of their uniqueness and variety, as seen in Niu’s study (2016). Thus, an in-house metadata schema is designed with 13 elements and their corresponding attributes.…”

Section: Discussionmentioning

confidence: 99%

“…The more there is demand for access to unprecedented amounts of historical scientific data, the more attention there needs to be on long-term preservation in scientific activities. With regards to the role of archivists in the data rescue processes, Niu (2016) argues that as scientific data sets are in aggregates, archivists are well suited to disentangle problems because they are good at using aggregated control of data sets at a high level and utilizing context-driven historical methodologies. Archivists and preservation librarians know the meaning and significance of historical collections, as they are the guardians who preserve them.…”

Section: Discussionmentioning

confidence: 99%

“…Dublin Core based variants, DataCite (DataCite Metadata Working Group, 2016), the Core Scientific MetaData Model for the data in experimental science (Matthews et al , 2010), the CERIF data model (EuroCRIS, 2012, etc.). However, these metadata schemas are too general to be applicable to data sets from specific areas or types and rather impede access to scientific data (Niu, 2016). Next, domain-oriented metadata schemas could be considered (e.g.…”

Section: Literature Review: the Digitization And Preservation Of Historical Climate Datamentioning

confidence: 99%

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Data rescue archive weather (DRAW)

Park

Burr

Slonosky

et al. 2018

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Purpose To rescue at-risk historical scientific data stored at the McGill Observatory, the objectives of the Data Rescue Archive Weather (DRAW) project are: to build a repository; to develop a protocol to preserve the data in weather registers; and to make the data available to research communities and the public. The paper aims to discuss these issues. Design/methodology/approach The DRAW project adopts an open archive information system compliant model as a conceptual framework for building a digital repository. The model consists of data collection, conversion, data capture, transcription, arrangement, description, data extraction, database design and repository setup. Findings A climate data repository, as the final product, is set up for digital images of registers and a database is designed for data storage. The repository provides dissemination of and access to the data for researchers, information professionals and the public. Research limitations/implications Doing a quality check is the most important aspect of rescuing historical scientific data to ensure the accuracy, reliability and consistency of data. Practical implications The DRAW project shows how the use of historical scientific data has become a key element in research analysis on scientific fields, such as climatology and environmental protection. Originality/value The historical climate data set of the McGill Observatory is by nature unique and complex for preservation and research purposes. The management of historical scientific data is a challenge to rescue and describe as a result of its heterogeneous and non-standardized form.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Literature Review: the Digitization And Preservation Of Historical Climate Datamentioning

confidence: 99%

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Data rescue archive weather (DRAW)

Park

Burr

Slonosky

et al. 2018

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“…Recently, metadata standards, including record management, have been represented as ontologies commonly addressed about knowledge graphs (Niu, 2016). Examples of using knowledge graphs in digital archives, museums and libraries include the following (Carriero et al , 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

A knowledge graph of interlinking digital records: the case of the 1997 Korean financial crisis

Kim

2023

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Purpose Despite ongoing research into archival metadata standards, digital archives are unable to effectively represent records in their appropriate contexts. This study aims to propose a knowledge graph that depicts the diverse relationships between heterogeneous digital archive entities. Design/methodology/approach This study introduces and describes a method for applying knowledge graphs to digital archives in a step-by-step manner. It examines archival metadata standards, such as Records in Context Ontology (RiC-O), for characterising digital records; explains the process of data refinement, enrichment and reconciliation with examples; and demonstrates the use of knowledge graphs constructed using semantic queries. Findings This study introduced the 97imf.kr archive as a knowledge graph, enabling meaningful exploration of relationships within the archive’s records. This approach facilitated comprehensive record descriptions about different record entities. Applying archival ontologies with general-purpose vocabularies to digital records was advised to enhance metadata coherence and semantic search. Originality/value Most digital archives serviced in Korea are limited in the proper use of archival metadata standards. The contribution of this study is to propose a practical application of knowledge graph technology for linking and exploring digital records. This study details the process of collecting raw data on archives, data preprocessing and data enrichment, and demonstrates how to build a knowledge graph connected to external data. In particular, the knowledge graph of RiC-O vocabulary, Wikidata and Schema.org vocabulary and the semantic query using it can be applied to supplement keyword search in conventional digital archives.

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“…Archivists can therefore contribute to the management of scientific data to ensure that material is available in the long term, and is trustworthy. Certainly, having noted the similarities of goals, archivists and data curators might be able to "collaborate, share expertise in knowledge organization and integrate resources" in order to protect the authenticity of scientific material [6].…”

Section: Protecting Authenticitymentioning

confidence: 99%