Metadata to the rescue -- enabling understanding of data and fitness for
use through quality descriptions that also trace its history
Abstract
In the era of overwhelming amounts of data and information being readily
available over the web and other media sources it is vitally important
to adopt machine-to-machine readable techniques that enable quick,
reliable and repeatable resource discovery and then based on rules and
definitions, facilitate determination as to whether the data and
information are relevant and fit for purpose. Quality metadata can
provide such a tool as: • It allows the creation of multiple discipline
specific metadata profiles based on international generic standards
(e.g. ISO 19115-1, DCAT2) thus improving data management and
interoperability of data • When expressed as an XML, Turtle or RDFXML it
provides a machine readable format which is easy to manipulate and
automate • Through cross-walks to other community defined standards, it
can be easily translated and used by multiple communities, (e.g. from
the ISO 19115-1 to DCAT2 and schema.org) • It enables the user to
understand the data, its purpose, suitability and usability by capturing
the history of acquisition and subsequent transformations, the
description and evaluations of data quality, and the data dictionaries
used • Through the application of consistent vocabulary tags and
persistent identifiers it helps improve data discoverability on the web
and also trace its usage and incorporation in derivative products • It
records and explains how to access and use data by related services,
APIs and other tools Australian and New Zealand Metadata Working Group
(ANZ MDWG) has been working on development a consistent methods of
implementing such tool across disciplines, communities and sectors to
facilitate a conversation, support a wider understanding and consistent
application. Numerous communication and educational materials have been
developed to support it. The current focus of the group is on
development of improving interoperability and consistency of data
management and description through developing discipline specific
profiles and ontologies. This presentation will examine challengers,
achievements and current plans of the ANZ MDWG.