Dataverse

From Archivematica
Jump to navigation Jump to search

Main Page > Documentation > Requirements > Dataverse

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

  • The proposed workflow consists of issuing API calls to Dataverse, receiving content (data files and metadata) for ingest into Archivematica, preparing Archivematica Archival Information Packages (AIPs) and placing them in archival storage, and updating the Dataverse study with the AIP UUIDs.
  • Analysis is based on Dataverse tests using https://apitest.dataverse.org/ and https://dataverse-demo.iq.harvard.edu/, online documentation at http://guides.dataverse.org/en/latest/api/index.html and discussions with Dataverse developers and users.
  • Proposed integration is for Archivematica 1.5 and higher and Dataverse 4.x.

Workflow diagram

Dataverse - Archivematica workflow 1.png

Workflow diagram notes

[1] "Ingest script" refers to an automation tool designed to automate ingest into Archivematica for bulk processing. An existing automation tool would be modified to accomplish the tasks described in the workflow.

[2] 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.

[3] 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.

[4] 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.

[5] The METS file will consist of a dmdSec containing the DC elements extracted from the json file, and a fileSec and structMap indicating the relationships between the files in the transfer (eg. original uploaded data file, derivative files generated for tabular data, metadata/citation files). This will allow Archivematica to apply appropriate preservation micro-services to different filetypes and provide an accurate representation of the study in the AIP METS file (step 1.9).

[6] Archivematica ingests all content returned from Dataverse, including the json file, plus the METS file generated in step 1.6.

[7] Standard and pre-configured micro-services 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.

Transfer METS file

When the ingest script retrieves content from Dataverse, it generates a METS file to allow Archivematica to understand the contents of the transfer and the relationships between its various data and metadata files.

Sample transfer METS file

Original Dataverse study retrieved through API call:

  • dataset.json (a JSON file generated by Dataverse consisting of study-level metadata and information about data files)
  • Study_info.pdf (a non-tabular data file)
  • A zipped bundle consisting of the following:
    • YVR_weather_data.sav (an SPSS SAV file uploaded by the researcher)
    • YVR_weather_data.tab (a TAB file generated from the SPSS SAV file by Dataverse)
    • YVR weather_data.RData (an R file generated from the SPSS SAV file by Dataverse)
    • YVR_weather_data-ddi.xml, YVR_weather_datacitation-endnote.xml, and YVR_weather_datacitation-ris.ris (three metadata files generated for the TAB file by Dataverse)


Resulting transfer METS file

  • The fileSec in the METS file consists of three file groups, USE="original" (the PDF and SAV files); USE="derivative" (the TAB and R files); and USE="metadata" (the JSON file and the three metadata files from the zipped bundle).
  • All of the files unpacked from the Dataverse bundle have a GROUPID attribute to indicate the relationship between them. If the transfer had consisted of more than one bundle, each set of unpacked files would have its own GROUPID.
  • Three dmdSecs have been generated:
    • dmdSec_1, consisting of a small number of study-level DDI terms
    • dmdSec_2, consisting of an mdRef to the JSON file
    • dmdSec_3, consisting of an mdRef to the DDI XML file
  • In the structMap, dmdSec_1 and dmdSec_2 are linked to the study as a whole, while dmdSec_3 is linked to the TAB file. The endnote and ris files have not been made into dmdSecs because they contain small subsets of metadata which are already captured in dmdSec_1 and the DDI xml file.


METS1G.png
METS2G.png
METS3G.png


Metadata sources for METS file


METS element Information source Notes
ddi:titl json: citation/typeName: "title", value: [value]
ddi:IDNo json: authority, identifier json example: "authority": "10.5072/FK2/", "identifier": "0MOPJM"
ddi:IDNo agency attribute json: protocol json example: "protocol": "doi"
ddi:AuthEntity json: citation/typeName: "authorName"
ddi:distrbtr Config setting in ingest tool
ddi:version date attribute json: "releaseTime"
ddi:version type attribute json: "versionState"
ddi:version json: "versionNumber", "versionMinorNumber"
ddi:restrctn json: "termsOfUse"
fileGrp USE="original" json: datafile Each non-tabular data file is listed as a datafile in the files section. Each TAB file derived by Dataverse for uploaded tabular file formats is also listed as a datafile, with the original file uploaded by the researcher indicated by "originalFileFormat".
fileGrp USE="derivative" All files that are included in a bundle, except for the original file and the metadata files (see below).
fileGrp USE="metadata" Any files with .json or .ris extension, any -ddi.xml files and -endnote.xml files
CHECKSUM json: datafile/"md5": [value]
CHECKSUMTYPE json: datafile/"md5"
GROUPID Generated by ingest tool. Each file unpacked from a bundle is given the same group id.



AIP METS file

Basic METS file structure

The Archival Information Package (AIP) METS file will follow the basic structure for a standard Archivematica AIP METS file described at METS. A new fileGrp USE="derivative" will be added to indicate TAB, RData and other derivatives generated by Dataverse for uploaded tabular data format files.

dmdSecs in AIP METS file

The dmdSecs in the transfer METS file will be copied over to the AIP METS file.

Additions to PREMIS for derivative files

In the PREMIS Object entity, relationships between original and derivative tabular format files from Dataverse will be described using PREMIS relationship semantic units. PREMIS normalization and creation Events will be added to indicate the derivative file was generated from the original file, and a Dataverse Agent will be added to indicate the Events were carried out by Dataverse prior to ingest, rather than by Archivematica.

Example:

Original SPSS SAV file 

 
<premis:relationship>
  <premis:relationshipType>derivation</premis:relationshipType>
    <premis:relationshipSubType>is source of</premis:relationshipSubType>
  <premis:relatedObjectIdentification>                  
    <premis:relatedObjectIdentifierType>UUID</premis:relatedObjectIdentifierType>
  <premis:relatedObjectIdentifierValue>[TAB file UUID]</premis:relatedObjectIdentifierValue>
<premis:relationship>
...
<premis:eventIdentifier>
  <premis:eventIdentifierType>UUID</premis:eventIdentifierType>
  <premis:eventIdentifierValue>[Event UUID assigned by Archivematica]</premis:eventIdentifierValue>
</premis:eventIdentifier>
<premis:eventType>derivation</premis:eventType>
<premis:eventDateTime>2015-08-21</premis:eventDateTime>
<premis:linkingAgentIdentifier>
  <premis:linkingAgentIdentifierType>URI</premis:linkingAgentIdentifierType>
  <premis:linkingAgentIdentifierValue>http://dataverse.scholarsportal.info/dvn/</premis:linkingAgentIdentifierValue>
</premis:linkingAgentIdentifier>
...
<premis:agentIdentifier>
  <premis:agentIdentifierType>URI</premis:agentIdentifierType>
  <premis:agentIdentifierValue>http://dataverse.scholarsportal.info/dvn/</premis:agentIdentifierValue>
</premis:agentIdentifier>
<premis:agentName>SP Dataverse Network</premis:agentName>
<premis:agentType>organization</premis:agentType>

Derivative TAB file 

 
<premis:relationship>
  <premis:relationshipType>derivation</premis:relationshipType>
    <premis:relationshipSubType>has source</premis:relationshipSubType>
  <premis:relatedObjectIdentification>                  
    <premis:relatedObjectIdentifierType>UUID</premis:relatedObjectIdentifierType>
  <premis:relatedObjectIdentifierValue>[SPSS SAV file UUID]</premis:relatedObjectIdentifierValue>
<premis:relationship>

Fixity check for checksums received from Dataverse

<premis:eventIdentifier>
  <premis:eventIdentifierType>UUID</premis:eventIdentifierType>
  <premis:eventIdentifierValue>[Event UUID assigned by Archivematica]</premis:eventIdentifierValue>
</premis:eventIdentifier>
<premis:eventType>fixity check</premis:eventType>
<premis:eventDateTime>2015-08-21</premis:eventDateTime>
<premis:eventDetail>program="python"; module="hashlib.sha256()"</premis:eventDetail>
<premis:eventOutcomeInformation>
  <premis:eventOutcome>Pass</premis:EventOutcome>
  <premis:eventOutcomeDetail>
    <premis:eventOutcomeDetailNote>Dataverse checksum 91b65277959ec273763d28ef002e83a6b3fba57c7a35436c9e5b66536333d720 verified</premis:eventOutcomeDetailNote>
   </premis:eventOutcomeDetail>
  <premis:eventOutcomeInformation>
</premis:linkingAgentIdentifier>
  <premis:linkingAgentIdentifierType>URI</premis:linkingAgentIdentifierType>
  <premis:linkingAgentIdentifierValue>http://dataverse.scholarsportal.info/dvn/</premis:linkingAgentIdentifierValue>
</premis:linkingAgentIdentifier>
Retrieved from "https://wiki.archivematica.org/index.php?title=Dataverse&oldid=10836"