Update:  For clarity, this is a piece of documentation for a specific group rather than a “regular” blog post. It may be of wider interest but it makes a number of contextual assumptions…

This document assumes that you have some familiarity with intent of the Learning Registry (LR) http://www.learningregistry.org/ and that you are interested in contributing information about your resources. It lists a few things to consider before you get into the detail of the how to guide. More extensive information is available from the Learning Registry document collection. This document draws on that documentation (By US Dept of Ed, SRI International, and others) and feedback from the LR development team. It’s primary audience are those in the UK community thinking about in contributing metadata/ paradata/ resources. It’s intended to help technical managers get a quick overview of the issues in contributing to the Learning Registry test node and forthcoming experimental node at MIMAS.

Preparing your data

The primary purpose of the LR record is to indicate the existence, location, and owner of the resource and related metadata and paradata. The LR allows you to submit full or partial metadata, and to (optionally) include the resource itself as payload. The more metadata you submit, the more discoverable your resources become. It does allow you to optionally include some basic information about resources to support filtering and browsing you can opt to include original records in the data rather than referring to them. The LR does not care what metadata formats you use (though data consumers who discover your information through the LR might…).
Contributors submit/push data about their resources to a node which distributes that data to other nodes in the system. In itself the LR will not harvest/ gather information about your resources, you need to actively contribute it.

However, there are issues of local practice that you may want to consider prior to the process of sharing your data. In particular – how are you identifying your resources (e.g. does it have a cool uri? and how are you exposing any usage/activity data which you have about those resources (the paradata format developed alongside the learning registry might be useful).

Mechanisms for LR deposit

Contributors have to create a signature (OpenPGP key pair) for themselves on the LR (anonymous contribution is not permitted). This is a relatively simple self –registration process and will let users interact with the LR test node. However, contributors should note that to contribute to the live LR they will need an agreement with a given live node which has opted to accept their signed data.

The LR uses JSON rather than xml and offers a number of approaches to publishing data, these are:

• Http post (basic publish). This is fully described in: The Learning Registry in 20 minutes or less . You need to be able to submit your data as JSON.
• an OAI-PMH Publish Utility (under development). This is fully described in: OAI-PMH to Learning Registry Publish Utility the utility will wrap your oai-pmh xml in a JSON envelope and surface elements of it.
• a SWORD Publish Utility (under development). This is outlined as part of the LR Quick Reference Guide .
• (other options may be developed)

Policy and License Issues

Please note the LR requests that any data you create or publish to the LR is clearly licensed. A Creative Commons Zero (CC0) or Attribution (CC: BY) licence are good options [Reccommended by both the Learning Registry, JISC, and UK Discovery]. You should ensure that you have the rights to assign this licence if it not already assigned and that the data you publish conforms with appropriate data protection and privacy laws. whatever data you submit to the LR is likely to move between legal jurisdictions.

The Learning Registry: Rough Guide for Contributors by R. John Robertson is licensed under a Creative Commons Attribution 3.0 Unported License.