Some common institutional goals, with examples of associated RIF-CS encoding, are provided below:
For more information about maximising the impact of your data:
As open data is citable and reusable it brings many benefits to individuals, institutions and the broader research community. The 'openness' of data is defined by several characteristics, so describing this requires more than one element. Providing content for these elements will not only provide users with clarity around access and reuse conditions, it will also ensure the record is prominently displayed in Research Data Australia.
To highlight open data, provide content for these RIF-CS elements:
A defining characteristic of open data is that it is well described, so include as much rich information as possible in collection records to describe what the data is, how it was collected and for what purpose.
<rights> <licence type="CC-BY" rightsUri="http://creativecommons.org/licenses/by/3.0/au"></licence> <accessRights type="open"></accessRights> </rights>
<location> <address> <electronic type="url" target="directDownload"> <value>http://www.ga.gov.au/corporate_data/64739/64739_sh50-04_kml.zip</value> <title>Youanmi Map Series</title> <mediaType>application/zip/kml</mediaType> <byteSize>5 MB</byteSize> </electronic> </address> </location>
Collection records can be harvested from a data source in Research Data Australia to the Clarivate Analytics (formerly Thompson Reuters) Data Citation Index using this process. This will enable metrics for citation of data to be counted in the same way as for publications. As similar indices emerge, we will seek to ensure records in Research Data Australia are included.
To enable citation metrics for data collections, provide content for these RIF-CS elements:
If you'd like the records in your data source to be harvested to the Data Citation Index take a look at the DCI encoding notes to ensure your records are ready to be harvested and can start accruing metrics. See also 3. Linking data to related publications.
<citationInfo> <citationMetadata> <identifier type="doi">10.4225/13/50BBFCFE08A12</identifier> <title>Surface water run-off measurements in the City of Salisbury, South Australia during the period June 2012 to December 2012</title> <version>1</version> <publisher>The University of South Australia</publisher> <contributor seq="1"> <namePart type="family">Oliver</namePart> <namePart type="given">R</namePart> </contributor> <contributor seq="2"> <namePart type="family">Myers</namePart> <namePart type="given">B</namePart> </contributor> <date type="publicationDate">2013</date> </citationMetadata> </citationInfo>
While it is not possible to create a registry object (or separate RIF-CS record) to describe a publication in Research Data Australia, it is possible to provide information about a publication using the RelatedInfo element in the relevant collection record. Providing this information can bring multiple benefits including:
To link data collections to related publications, provide content for this RIF-CS element:
<relatedInfo type="publication"> <title>Preconception risk factors and SGA babies: Papilloma virus, omega 3 and fat soluble vitamin deficiencies</title> <identifier type="doi">https://doi.org/10.1016/j.earlhumdev.2011.06.002</identifier> <relation type="isCitedBy"/> </relatedInfo>
The service may enable a user to download the data being described, or it may allow a user to "do something" with the data, e.g. create a visualisation of or analyse the data. The ARDC, in consultation with the community, has developed a schema-agnostic, best practice guide for service metadata, primarily for enhancing machine-to-machine discovery. Refer to the Metadata for Services and Related Collections: Best Practice Guide for further information.
Two options exist to describe a service related to a data collection in the RDA Registry:
<relatedInfo type="service"> <title>Marine Virtual Laboratory Information System</title> <identifier type="uri">http://marvlis.aodn.org.au/marvlis</identifier> <relation type="supports"> <url>http://marvlis.aodn.org.au/marvlis/ACQ_SurfPlt/MAPWaterTemps.png</url> </relation> <notes>Data visualisation</notes> </relatedInfo>
There is widespread and growing use of structured metadata by web search engines, such as Google Dataset Search. To help the discoverability of metadata harvested into Research Data Australia, Schema.org metadata has been added to all Collection and Service records.The RIF-CS elements which are mapped to Schema.org and display in Google Dataset Search (beta) are:
If you include these elements in the RIF-CS collection records you provide to Research Data Australia, then you will maximise the discoverability and display of your records in Google Dataset Search.
(Note: this advice may change over time, as Google Dataset Search is currently in beta).
Like to know more? Refer to our mapping of RIF-CS elements to the Schema.org metadata standard used by Google Dataset Search.