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Overview

The goal of this project is to develop a general-purpose research data repository "recommender" service to be hosted by the NDS.  The basic use case is a researcher that has data that they want to deposit, but they do not know where to put it.  A few possible use cases:

• There is no existing community repository
• The data doesn't fit the researcher's usual repository.  For example, someone working in a new interdisciplinary space or has data they believe might be useful to another community.
• Novice or "lazy" user – however, most advice from these users will come from social media, conferences, and training.

There are several existing services in this space including the Registry of Research Data Repositories (RE3Data), Biosharing.org, and the SEAD C3PR service.  Informal discussions with U of I Research Data Service makes the following recommendation:

"Deposition of data into a web-accessible repository is generally the preferred mechanism for public data sharing because it ensures wide-spread and consistent access to the data.  If your discipline already has a trusted repository, we recommend you deposit where your community knows to look.  To find a repository, re3data.org is a large, vetted, and searchable catalog of data repositories.  If no discipline-specific repository exists, there are several options, including Illinois’ IDEALS repository (free) and other general-purpose repositories like DataDryad (fee-based)."

In addition to these existing registries of research data repositories, funding agencies and publishers provide lists of recommended repositories. 

To be useful, the NDS repository recommender must differentiate itself from these existing tools and services. For example

• Improved search over Re3Data through the use of priors (e.g., "trustworthiness" or some sort of impact factor)
• Accounting for user motivations (funding agency requirements, publisher requirements, data size) through guided search

Background

What tools already exist in this space?

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There are (at least) two major registries of research data repositories.  Publishers and funding agencies often direct researchers to search for repositories using these tools:

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• The schema is based on BioDBCore: http://biocuration.org/community/standards-biodbcore/, 
• License:  Creative Commons by Share Alike 4.0
• See also:
  • BioSharing: curated and crowd-sourced metadata standards, databases and data policies in the life sciences

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Publishers refer to both in their lists of recommended repositories, but both services appear to be intended for librarians, curators, publishers and funding agencies instead of the average researcher. The re3data is easily available for download and could be incorporated into our system. It's not clear whether the Bioshare data is available (technically, it could be crawled).

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(This list is not exhaustive – it's likely that many publishers, agencies, and organizations will provide similar lists):

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Note that the Biosharing database already includes information about whether a repository is recommended by a funding agency:

• https://biosharing.org/policy/1947
• https://biosharing.org/policy/1931

SEAD C3PR/Matchmaker

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SEAD Publication API

See also  and the actual 

A primary function of the SEAD Publication API (C3PR) is to match or recommend a repository given a research data object based on a set of technical requirements implemented as rules:

• Maximum dataset size
• Purpose
• Organization match
• Acceptable data types (based on mimetypes)
• Minimal required metadata
• Maximum total size
• Maximum collection depth
• Rights-holder requirements 

SEAD 2.0 introduces the "publish" workflow.  The user selects "publish" and the "live object" is copied to a staging area into a "curation object". The user is able to modify the curation object – adding removing files, metadata, etc. There can be many curation objects for a live object.  During the publish workflow, SEAD/Clowder represents the curation object as an ORE MAP and sends a request to the C3PR service.  The C3PR service matches the ORE-MAP to available repositories based on a set of rules/criteria.  The user is presented with a ranked list of repositories based on a best-match against the ORE.  The user can opt to publish to any listed repository.

See also:

• SEAD 2.0 Publication API Walkthrough

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• C3PR API server

• Workflow of Operating Your Repository with SEAD

• • http://www.ijdc.net/index.php/ijdc/article/view/8.2.172

• Plale et al (2013). SEAD Virtual Archive: Building a Federation of Institutional Repositories for Long-Term Data Preservation in Sustainability Science

• Git repository https://github.com/Data-to-Insight-Center/sead2
/tree/master/sead-matchmaker

• SEAD 2.0 Publication API Walkthrough:

Workflow of Operating Your Repository with SEAD

Other sources of information:

What other sources of information might we include in a recommender service?

• Researcher identifiers, such as ORCID Persistent digital identifier for researchers: these might be helpful in collecting researcher profile information that can be used for recommendation.
• Journal/publication information: We can relate specific journals to data repositories. If the user is publishing in a specific journal, we can recommend where to put the data.  
• Abstract: Use text matching techniques to match an abstract to a repository.
• https://www.datacite.org/
• BrownDog: Can we use information from extractors to identify criteria for recommendation?

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