Validation and data quality

[E. Cohen]

Validation and data quality are important in the world of XBRL. Whether it is the basics provided by XML and XML Schema, the extensions of XBRL including XBRL Formula and other XML-based rules languages or additional layers, such as those that can be provided by the audit profession, the goal is secure, authentic, usable and trustworthy information.

As we speak to ontological approaches to leveraging XBRL, it is important to consider validation and data quality approaches to Linked Open Data. The W3 will be holding a workshop in September where the needs of the market related to the data expressed in XBRL today can be provided as part of the discussion. If the corporate data provided in XBRL today was provided as Linked Open Data, there might be issues. Per the W3C, here is one of the issues today:

"While the Linked Open Data cloud keeps expanding, the inconsistency in quality of the data it is made of limits its use. Indeed, organizations cannot directly use the LOD cloud. Instead, they must shield themselves from all the inconsistencies that it contains by using a local replica which they have curated using custom made processes. The curating process is expensive, must be repeated every time the local replica is refreshed and does not benefit anyone else."
- https://www.w3.org/2012/12/rdf-val/Overview.php

How can we publish and share rules, assertions and other helps for the kinds of data XBRL can represent? How do we crowd-source and communicate? How do we make it so there is shared benefit (where applicable) and data can directly be used (where possible)? How do we make curation an open and shared process (where valuable)?

Learn more about the RDF Validation Workshop, 10-11 September at Cambridge, at https://www.w3.org/2012/12/rdf-val/