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Data Documentation Standards
Data standards are the rules by which data are described or documented. In order to share, exchange, and understand data, we must standardize the format of the data as well as document the metadata (specific information about the research data) both the descriptive meta data and the structural metadata.
- Using standards makes data more usable to more than just the project or person that created the data.
- Standards are useful for integrating data from multiple resources. If the various sources agreed upon a standard to begin with, this saves time reconciling any differences.
- When collecting new data, try to find data standards for the type of data you are collecting. Different disciplines and different kinds of data use different standards.
Resources for Data Standards
BioPortal offers an extensive repository of biomedical ontologies, including a recommender tool to help choose the best ontology for your research.
BioSharing offers a searchable database of metadata standards, markup languages, taxonomies, and other resources for biological and life sciences.
Categories for the description of Works of Art provides a conceptual framework for describing and accessing information about works of art, architecture, and other materials of culture.
Metadata information about the geographic occurrence of species and the existence of specimens in collections.
Data Documentation Initiative
DDI is an international standard for describing statistical and social science data. It contains a metadata specification, as well as a list of tools to help researchers work with DDI metadata.
Ecological Metadata language developed for the discipline of ecology.
Linked Open Vocabularies (LOV)
LOV provides a searchable repository of vocabularies and ontologies used to describe many different disciplines and domains.
Research Data Alliance Metadata Directory
The RDA Metadata Directory is a collaborative, open directory of metadata standards applicable to scientific data. Subject areas include arts and humanities, engineering, life sciences, physical sciences & mathematics, social & behavioral sciences, and general research data (multidisciplinary).
Text Encoding Initiative is a standard for representation of texts in digital form, chiefly in the humanities, social sciences and linguistics.
Visual Resources Association provides a categorical organization for the description of works of visual culture as well as the images of documentation.
The table below provides a basic description of each important element to be included in the metadata attached to your research project:
Scholarly Commons data webpage: http://www.library.illinois.edu/sc/services/data_management/documentation.html
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