DQM-Vocabulary announced by Christian Fürber:
The DQM-Vocabulary supports data quality management activities in Semantic Web architectures. It’s major strength is the ability to represent data requirements, i.e. prescribed (individual) directives or consensual agreements that define the content and/or structure that constitute high quality data instances and values, so that computers can interpret the requirements and take further actions. Among other things, the DQM-Vocabulary supports the following tasks:
- Automated creation of data quality monitoring and assessment reports based on previously specified data requirements
- Exchange of data quality information and data requirements on web-scale
- Automated consistency checks between data requirements
The DQM-Vocabulary is available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 license at http://purl.org/dqm-vocabulary/v1/dqm
A primer with examples on how to use the DQM-Vocabulary can be found at http://purl.org/dqm-vocabulary
A mailing list for issues and questions around the DQM-Vocabulary can be found at http://groups.google.com/group/dqm-vocabulary
Interesting work but I think pretty obviously only commercial interests are going to have an incentive to put in the time and effort to use such a system.
Which reminds me, how is this different from the OASIS Universal Business Language (UBL) activity? UBL has already been adopted in a number of countries, particularly for government contracts. They have specified the semantics that businesses need to automate some contractual matters.
I suppose more broadly, where is the commercial demand for the DQM-Vocabulary?
Are there identifiable activities that lack data quality management now, for which DQM will be a solution? If so, which ones?
If other data quality management solutions are in place, what advantages over current systems are offered by DQM? Are those sufficient to justify changing present systems?