Dataverse
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This page tracks development of a proof of concept integration of Archivematica with Dataverse.
See also
Overview
This wiki captures requirements for ingesting studies (datasets) from Dataverse into Archivematica for long-term preservation.
Workflow
Workflow diagram
Workflow diagram notes
[1] A new or updated study is one that has been published, either for the first time or as a new version, since the last API call.
[2] The json file contains citation and other study-level metadata, an entity_id field that is used to identify the study in Dataverse, version information, a list of data files with their own entity_id values, and md5 checksums for each data file.
[3] If json file has content_type of tab separated values, Archivematica issues API call for multiple file ("bundled") content download. This returns a zipped package for tsv files containing the .tab file, the original uploaded file, several other derivative formats, a DDI XML file and file citations in Endnote and RIS formats.
[4] Standard and pre-configured micro-services to include: assign UUID, verify checksums, generate checksums, extract packages, scan for viruses, clean up filenames, identify formats, validate formats, extract metadata and normalize for preservation.
[5] DC metadata parsed for the study only, not for individual data files.