Difference between revisions of "Data Discovery (DataCite)"
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| − | <p>DataCite is an organization founded in Germany to help make data more accessible and more useful; their purpose is to develop and support methods to locate, identify and cite data and other research objects. Specifically, they develop and support the standards behind persistent identifiers for data, and their members assign them. They are also known as the originators of Digital Object Identifiers (DOIs). | + | <p>[https://www.datacite.org/ DataCite] is an organization founded in Germany to help make data more accessible and more useful; their purpose is to develop and support methods to locate, identify and cite data and other research objects. Specifically, they develop and support the standards behind persistent identifiers for data, and their members assign them. They are also known as the originators of Digital Object Identifiers (DOIs). |
The DataCite Metadata Schema is a list of metadata elements chosen by DataCite for the accurate and consistent identification of a resource for citation and retrieval purposes, along with recommended use instructions. It was created by DataCite to help DOI users document resources that were being assigned DOIs. The resource that is being identified can be of any kind, but it is typically a dataset. DataCite uses the term "dataset" in its broadest sense. They mean it to include not only numerical data, but also any other research data outputs. The recommendation has three parts (termed spirals): mandatory concepts, recommended concepts and optional concepts. | The DataCite Metadata Schema is a list of metadata elements chosen by DataCite for the accurate and consistent identification of a resource for citation and retrieval purposes, along with recommended use instructions. It was created by DataCite to help DOI users document resources that were being assigned DOIs. The resource that is being identified can be of any kind, but it is typically a dataset. DataCite uses the term "dataset" in its broadest sense. They mean it to include not only numerical data, but also any other research data outputs. The recommendation has three parts (termed spirals): mandatory concepts, recommended concepts and optional concepts. | ||
| − | In the context of the terminology we use (described below), DataCite is an organization that created a set of recommendations at three levels (described in the schema description document) and an XML schema (a dialect) for implementing those recommendations. The dialect is currently being used in the DataCite search portal and in creating DOI landing pages. It can be useful to communities that are trying to improve the way they share metadata. The recommendations are useful for communities looking for expert guidance about metadata elements that are useful for data discovery. The work we are doing explores how those recommendations can be useful for communities that are already using other dialects.</p> | + | In the context of the terminology we use (described below), DataCite is an organization that created a set of recommendations at three levels (described in the schema description document) and an XML schema (a dialect) for implementing those recommendations. The dialect is currently being used in the DataCite [http://search.datacite.org/ui search portal] and in creating DOI landing pages. It can be useful to communities that are trying to improve the way they share metadata. The recommendations are useful for communities looking for expert guidance about metadata elements that are useful for data discovery. The work we are doing explores how those recommendations can be useful for communities that are already using other dialects.</p> |
<div id="DataCite3.1Mandatory"></div> | <div id="DataCite3.1Mandatory"></div> | ||
Revision as of 11:06, July 10, 2015
DataCite is an organization founded in Germany to help make data more accessible and more useful; their purpose is to develop and support methods to locate, identify and cite data and other research objects. Specifically, they develop and support the standards behind persistent identifiers for data, and their members assign them. They are also known as the originators of Digital Object Identifiers (DOIs). The DataCite Metadata Schema is a list of metadata elements chosen by DataCite for the accurate and consistent identification of a resource for citation and retrieval purposes, along with recommended use instructions. It was created by DataCite to help DOI users document resources that were being assigned DOIs. The resource that is being identified can be of any kind, but it is typically a dataset. DataCite uses the term "dataset" in its broadest sense. They mean it to include not only numerical data, but also any other research data outputs. The recommendation has three parts (termed spirals): mandatory concepts, recommended concepts and optional concepts. In the context of the terminology we use (described below), DataCite is an organization that created a set of recommendations at three levels (described in the schema description document) and an XML schema (a dialect) for implementing those recommendations. The dialect is currently being used in the DataCite search portal and in creating DOI landing pages. It can be useful to communities that are trying to improve the way they share metadata. The recommendations are useful for communities looking for expert guidance about metadata elements that are useful for data discovery. The work we are doing explores how those recommendations can be useful for communities that are already using other dialects.
xPath Note: The xPaths included in this table use several wildcards. // means any path, so //gmd:CI_ResponsibleParty indicates a gmd:CI_ResponsibleParty anywhere in an XML file. /*/ indicates a single level with several possible elements. This usually indicates one of several concrete realizations of an abstract object. For example /*/gmd:identificationInfo could be gmd:MD_Metadata/gmd:identificationInfo or gmi:MI_Metadata/gmd:identificationInfo and gmd:identificationInfo/*/gmd:descriptiveKeywords could be gmd:identificationInfo/gmd:MD_DataIdentification/gmd:descriptiveKeywords or gmd:identificationInfo/srv:SV_ServiceIdentification/gmd:descriptiveKeywords. Fit: The fit of the dialect path with the concept is estimated on a scale of 1 = excellent two-way fit, 2 = one-way fit or some other problem, 3 - extension required.
