The Institute of Metadata Management (IMM) is hosting a linked data mash-up challenge, sponsored by one of our major sponsors.The aim of this challenge is to create an incentive for linking information in novel and ingenious ways to foster the knowledge discovery process and deliver end-user benefits.
The challenge will also demonstrate to delegates the potential value in linking datasets. We' are now inviting submissions of web applications that perform mash-ups on raw and / or linked data, via novel mechanisms or technologies, and that showcase the benefits of Linked Data to end-users.
Entry Details
Submissions must be original and must not have been submitted / demonstrated elsewhere. Abstracts should follow the Springer LNCS formatting guidelines found here. Submissions are to be made by email to mashupchallenge@metalounge.org as PDF documents Submissions should not exceed 2 pages.
For full details including Data & Application requirements, Evaluation Criteria and Panel of Judges download the Mash-up Challenge brochure here
The challenge will also demonstrate to delegates the potential value in linking datasets. We' are now inviting submissions of web applications that perform mash-ups on raw and / or linked data, via novel mechanisms or technologies, and that showcase the benefits of Linked Data to end-users.
THE DEADLINE FOR SUBMITTING MASH-UP ENTRIES: 10 MAY 2011
Entry Details
Submission Format
Submissions must be original and must not have been submitted / demonstrated elsewhere. Abstracts should follow the Springer LNCS formatting guidelines found here. Submissions are to be made by email to mashupchallenge@metalounge.org as PDF documents Submissions should not exceed 2 pages.
For full details including Data & Application requirements, Evaluation Criteria and Panel of Judges download the Mash-up Challenge brochure here
Data & Applications Requirements
- The challenge does not impose any requirements on the datasets or applications used to create the mash-up.
- In the case of acceptance of a submission that uses any proprietary data or applications, the authors of the submission will carry the responsibility of ensuring that all privacy / IP aspects are being dealt with, until the entry is presented during the conference.
- By submitting an entry that falls into this category, the authors automatically acknowledge and adhere to this responsibility.
Evaluation Criteria
- Innovation & Creativity: combine datasets (via selective facets) in novel, ingenious ways.
- Reuse: adopt well-known existing vocabularies and ontologies (including alignment ontologies), instead of providing a proprietary-developed solution
- Discovery: enable automatic discovery of new data (e.g., in forms of new relationships between different concepts), instead of restricting the mash-up to plain visualization
- Added value: demonstrate the potential benefit users might gain from using the mash-up in real-world use-cases.
