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Dataverse in the
European Open Science Cloud
Slava Tykhonov (DANS/CESSDA)
Philipp Conzett (UiT/CLARIN)
Marion Wittenberg (DANS/CESSDA)
Dataverse Community Meeting at Harvard University
20 June, 2019
SSHOC objective and deliverables
Objective
Development of a research data repository service on EOSC, for SSH
institutions currently without such a facility for their designated communities
Deliverables
After 38 months: Data repository service running on EOSC
After 40 months: Report on principles of governance and sustainability of
the data repository service
Development process
DataverseSSHOC project has two parallel tracks of the development:
● Core development team is working on the modification and extension
of the Dataverse core functionality.
● The application development team will create new or will integrate
existent tools that will be published on Dataverse App Store website.
Our goal is to build the distributed and mature data infrastructure based on
sustainable microservices.
Development methodology
We follow SCRUM with quick but small updates, all new functionality will go through DTAP
(development, testing, acceptance and production) pipeline:
local (own PC) – test (cloud) – acceptance (cloud) – production (cloud)
DataverseEU deployment in CESSDA Cloud
Docker Compose for the local development and testing
Kubernetes (K8s) for the deployment of services in the Cloud
(CI/CD pipeline with Jenkins and Helm)
Services in European Open Science Cloud (EOSC)
● EOSC requires the level 8 of maturity
(at least)
● we need the highest quality of software
to be accepted as a service
● clear and transparent evaluation of
services is essential
● the evidence of technical maturity is the
key to success
● the limited warranty will allow to stop
out-of-warranty services
Testing process for the core and apps
Testing process follows the CESSDA maturity model
https://zenodo.org/record/2591055#.XKR6ny2B2u5
Important: every change of Dataverse functionality should be supplied with
unit tests, changes of external functionality should get Selenium scenarios.
Goal: to score as high as possible according to CESSDA maturity model
Testing procedures
● Writing unit tests (Java) for core development team
● Integration tests (Selenium) for app development team
● Performance/stress tests (Apache JMeter) before Dataverse will go to
Acceptance/Production
Dataverse App Store
Let’s build different services out of tools!
Data preview: DDI Explorer, Spreadsheet/CSV, PDF, Text files, HTML,
Images, video render, audio, JSON, GeoJSON/Shapefiles/Map, XML
Interoperability: external controlled vocabularies (CESSDA CV Manager)
Data processing: NESSTAR DDI migration tool
Linked Data: RDF compliance including SPARQL endpoint
Federated login as a service (OAuth/Shibboleth in the same installation)
Applications maturity level
Every software package should follow the same CESSDA Maturity Model to
be accepted as a service.
Must have: k8s infrastructure with upstream Docker images, warranty
statement, documentation, unit tests, Selenium tests, jenkins pipeline
Running demonstration service will allow to create the connection to your
own Dataverse
Multilingual support
DataverseEU will run Weblate as a service for the user interface, metadata
schema and SOLR translation.
We’ve developed an experimental but adjustable pipeline for multilingual
support that allows to download and synchronize all translations available in
Dataverse Consortium github and provides easy access for translators to
keep all properties up-to-date.
Weblate as Dataverse app
Controlled Vocabularies support
Use Cases
Who is going to benefit from SSHOC?
• European SSH researchers will be offered a
Dataverse installation
• Many of the features to be developed in SSHOC
will benefit also other Dataverse installations /
communities
Use Case: Multilingual support
• Useful for the SSHOC Dataverse installation, e.g.
French users can use French interface, Italian
users can use Italian interface, etc.
• But also useful for existing Dataverse
installations, e.g. DataverseNO
Use Case: Multilingual support
In DataverseNO we ideally
need support for the two
written standards of
Norwegian:
● Bokmål
● Nynorsk
in addition to support for
● English
Use Case: Federated Log-in
Multiple authentication protocol
support (enable use of both
OAuth and Shibboleth
in same installation)
For DataverseNO
users outside
Norway:
For DataverseNO users at
Norwegian higher education and
research institutions:
Use Case: Cloud support
We are considering to have DataverseNO being run in the
cloud by UNINET, Norway’s
national research and education
network.
The Kubernetes approach in
SSHOC will enable this kind of
cloud deployment.
Use Case: CLARIN metadata compliance
Metadata for language resources and data
exists in a multitude of formats.
To overcome this dispersion CLARIN has
developed the Component MetaData
Infrastructure (CMDI).
CMDI provides a framework to describe and
reuse metadata blueprints of profiles.
Use Case: CLARIN metadata compliance
Will enable repositories
like TROLLing (part of
DataverseNO) to
become fully CLARIN
compliant
Partners
CLARIN/UiT DARIAH/PSNC
DARIAH/SUB
E-RIHS/CNR
CESSDA/DANS-KNAW
(lead)
Join our
communityhttps://www.sshopencloud.eu
info@sshopencloud.eu
@SSHOpenClou
d/in/sshopenclou
d

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Dataverse in the European Open Science Cloud

  • 1. Dataverse in the European Open Science Cloud Slava Tykhonov (DANS/CESSDA) Philipp Conzett (UiT/CLARIN) Marion Wittenberg (DANS/CESSDA) Dataverse Community Meeting at Harvard University 20 June, 2019
  • 2. SSHOC objective and deliverables Objective Development of a research data repository service on EOSC, for SSH institutions currently without such a facility for their designated communities Deliverables After 38 months: Data repository service running on EOSC After 40 months: Report on principles of governance and sustainability of the data repository service
  • 3. Development process DataverseSSHOC project has two parallel tracks of the development: ● Core development team is working on the modification and extension of the Dataverse core functionality. ● The application development team will create new or will integrate existent tools that will be published on Dataverse App Store website. Our goal is to build the distributed and mature data infrastructure based on sustainable microservices.
  • 4. Development methodology We follow SCRUM with quick but small updates, all new functionality will go through DTAP (development, testing, acceptance and production) pipeline: local (own PC) – test (cloud) – acceptance (cloud) – production (cloud)
  • 5. DataverseEU deployment in CESSDA Cloud Docker Compose for the local development and testing Kubernetes (K8s) for the deployment of services in the Cloud (CI/CD pipeline with Jenkins and Helm)
  • 6. Services in European Open Science Cloud (EOSC) ● EOSC requires the level 8 of maturity (at least) ● we need the highest quality of software to be accepted as a service ● clear and transparent evaluation of services is essential ● the evidence of technical maturity is the key to success ● the limited warranty will allow to stop out-of-warranty services
  • 7. Testing process for the core and apps Testing process follows the CESSDA maturity model https://zenodo.org/record/2591055#.XKR6ny2B2u5 Important: every change of Dataverse functionality should be supplied with unit tests, changes of external functionality should get Selenium scenarios. Goal: to score as high as possible according to CESSDA maturity model
  • 8. Testing procedures ● Writing unit tests (Java) for core development team ● Integration tests (Selenium) for app development team ● Performance/stress tests (Apache JMeter) before Dataverse will go to Acceptance/Production
  • 9. Dataverse App Store Let’s build different services out of tools! Data preview: DDI Explorer, Spreadsheet/CSV, PDF, Text files, HTML, Images, video render, audio, JSON, GeoJSON/Shapefiles/Map, XML Interoperability: external controlled vocabularies (CESSDA CV Manager) Data processing: NESSTAR DDI migration tool Linked Data: RDF compliance including SPARQL endpoint Federated login as a service (OAuth/Shibboleth in the same installation)
  • 10. Applications maturity level Every software package should follow the same CESSDA Maturity Model to be accepted as a service. Must have: k8s infrastructure with upstream Docker images, warranty statement, documentation, unit tests, Selenium tests, jenkins pipeline Running demonstration service will allow to create the connection to your own Dataverse
  • 11. Multilingual support DataverseEU will run Weblate as a service for the user interface, metadata schema and SOLR translation. We’ve developed an experimental but adjustable pipeline for multilingual support that allows to download and synchronize all translations available in Dataverse Consortium github and provides easy access for translators to keep all properties up-to-date.
  • 14. Use Cases Who is going to benefit from SSHOC? • European SSH researchers will be offered a Dataverse installation • Many of the features to be developed in SSHOC will benefit also other Dataverse installations / communities
  • 15. Use Case: Multilingual support • Useful for the SSHOC Dataverse installation, e.g. French users can use French interface, Italian users can use Italian interface, etc. • But also useful for existing Dataverse installations, e.g. DataverseNO
  • 16. Use Case: Multilingual support In DataverseNO we ideally need support for the two written standards of Norwegian: ● Bokmål ● Nynorsk in addition to support for ● English
  • 17. Use Case: Federated Log-in Multiple authentication protocol support (enable use of both OAuth and Shibboleth in same installation) For DataverseNO users outside Norway: For DataverseNO users at Norwegian higher education and research institutions:
  • 18. Use Case: Cloud support We are considering to have DataverseNO being run in the cloud by UNINET, Norway’s national research and education network. The Kubernetes approach in SSHOC will enable this kind of cloud deployment.
  • 19. Use Case: CLARIN metadata compliance Metadata for language resources and data exists in a multitude of formats. To overcome this dispersion CLARIN has developed the Component MetaData Infrastructure (CMDI). CMDI provides a framework to describe and reuse metadata blueprints of profiles.
  • 20. Use Case: CLARIN metadata compliance Will enable repositories like TROLLing (part of DataverseNO) to become fully CLARIN compliant