This repository was archived by the owner on Feb 2, 2020. It is now read-only.
SEAD 2.0 Publishing Services
SEAD 2.0 is funded in large part by a grant from the National Science Foundation.
The primary components of the SEAD 2.0 suite are:
- Curbee: a lightweight publishing workflow;
- PDT: a mongoDB repository of People, Data, Things used by the publishing services;
- SEAD Matchmaker: recommendation tool that selects repositories for deposit using information from PDT;
Services suite for a hybrid HPC storage server/repository that accepts deposits from the SEAD services. Used to develop IU SEAD Cloud at Indiana University, and a test HPC storage server/repository solution that runs at the National Data Service at NCSA.
SEAD create data services designed to meet the needs of sustainability science research.
- reliable cyber-infrastructure
- enhanced ability to manage, integrate, share, curate, and preserve data
SEAD enables to curate, shares and preserves/publish data via any number of repositories.
SEAD API Documentation should be accessible through the following URL.
https://seadva.d2i.indiana.edu/sead-c3pr/index.html
- Simple Java based publishing pipeline, keeps track of published objects, extracts minimal metadata, forms a metadata object for DataONE harvesting and support multiple repositories
- Accepts Research Objects that are formed as a single ORE package
- Applies a set of micro-services to RO to ready it for a repository. Such as: Validate the object (validating the URLs) and Persist in PDT
- Notifies recommended repository of prepared submission
- Retains information about all objects it handles for enhanced visibility of the objects through 3rd party tools(ex: DataONE)
- Utilizes profiles about People, Data, and Repositories to recommend the most appropriate repository for a research object.
- Repository profile : inspired by the Registry of Research Data Repositories(re3data.org)
- People profiles: Orcid ID, Google ID, Clowder identity (NCSA)
- Data profiles are in JSON-LD format : defined by SEAD
Preserve data for long-term reliability
- Large scale replicated storage server at Indiana University
- Highly available and ingests large scale objects easily
- Pulls new Research Objects from SEAD
- Uses BagIt to describe the research objects
- Harvests minimal metadata and creates landing page per object
- Assigns DOIs(Data Object Identifier)*
