What’s going on related to CEDAR?

CEDAR Release 2.4

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We released version 2.4 of the CEDAR Workbench on September 6, providing more user features and enhancements.

OpenView offers public option for CEDAR artifacts

OpenView of metadata instanceDid you ever want to show your template or metadata values to a colleague, without logging in? Do you want to view all your metadata on the web? Or maybe you’d like an IRI that anyone can use to see your work?

Now you can make your CEDAR artifact—metadata instance, template, element, or field—visible on the web. CEDAR’s OpenView service presents the CEDAR artifact as a publicly visible web page, with pop-up metadata descriptions and access to JSON and RDF views of the content. To make public your template, element, or field, simply enable OpenView from the workspace menu for the artifact. For now, if you want to make your metadata public, the template it’s based on must also be public—we can help you with this.

Instructions for CEDAR’s OpenView feature may be found at its CEDAR manual page.

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CEDAR Release 2.3

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We released version 2.3 of the CEDAR Workbench on May 1, offering significant new user features and internal capabilities.

New Value Recommender Service

Shows example recommendations from Human 1.0 metadata We significantly updated CEDAR’s value recommendation capabilities in this release. The new approach adopts a powerful mechanism to suggest new values for fields in a templates as users fill in those fields. If the template creator enables the value recommender for at least 2 text fields (using each field’s SUGGESTIONS tab), CEDAR will find patterns across all the previously entered values for recommendation-enabled fields. If those patterns are strong enough over many metadata instances, CEDAR will recommend values to a user based on the (enabled) values that the user has already filled in.

This functionality is documented in more detail here.

New Sharing Modes

Shared asset controls in workspaceCEDAR now provides Shared With Me and Shared With Everybody modes on the workspace to let users see globally shared resources, or just resources explicitly shared with them. The default Workspace view just shows the files you own and administer. Shared with Me shows content that someone shared with you directly; and Shared with Everybody shows content that all CEDAR users can see (there are a lot of those!).

Your searches will always find everything you can see, no matter how it was shared.

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Drone Metadata and CEDAR at ESIP Summer Meeting

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You can find the CEDAR team at ESIP’s Summer Meeting this July, thanks to the Linked data And Networked DRoNeS (LANDRS) community.

Simple Drone minimum information model
The Drone Minimum Information framework contains basic elements describing drones and their missions.

We’ll support the Small Unmanned Aircraft Systems’ Data Interest Group at the Drone Data Hackathon on Tuesday July 16. During the hackathon we will help create drone metadata templates and terms, and perhaps help model the metadata model used by the group.

CEDAR template with Drone metadata fields
After: CEDAR represents drone metadata.

 

 

 

Then we (and BioPortal) will roam the grounds until the UnConference (Thursday afternoon July 18) and Semantic Committee work (Friday July 19).





Publication: CEDAR offers metadata recommendations from mined rules

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Marcos Martinez-Romero and his co-authors have published a new paper describing CEDAR’s updated implementation of intelligent authoring. The new methods use rule mining to generate recommendations based on previously entered metadata in the CEDAR system, and offer the users only the most likely recommendations given previous metadata entries for the template.

Suggested values seen by users
The intelligent authoring metadata recommendations take into account rules derived from previously entered metadata with the same values.

You can find instructions for setting up this capability in the CEDAR User Manual page Understanding the Suggestion System.

Martínez-Romero M, O’Connor MJ, Egyedi AL, Willrett D, Hardi J, Graybeal J, Musen MA. Using association rule mining and ontologies to generate metadata recommendations from multiple biomedical databases. Database. Volume 2019, 10 June 2019. https://doi.org/10.1093/database/baz059.