ARTICLE
7 February 2014

The application of traditional legal rights in a big data world

SF
Spruson & Ferguson

Contributor

Established in 1887, Spruson & Ferguson is a leading intellectual property (IP) service provider in the Asia-Pacific region, with offices in Australia, China, Indonesia, Malaysia, Philippines, Singapore, and Thailand. They offer high-quality services to clients and are part of the IPH Limited group, which includes various professional service firms operating under different brands in multiple jurisdictions. Spruson & Ferguson is an incorporated entity owned by IPH Limited, with a strong presence in the industry.
Copyright has been the focus of database protection but unstructured data poses challenges to traditional legal rights.
Australia Intellectual Property

Big Data: Legal Challenges (Full Report)

The form in which data is stored, the human skill and attention which goes into its collection and arrangement, the way in which data is protected, the need to preserve or destroy data at given intervals, the control, location and ownership of data and the sensitivity of data from a commercial and privacy perspective all require an increasingly close interaction between lawyers and the CIO or Chief Information Officer of corporations.

A well-defined data strategy is necessary to ensure proper treatment of this all important "new asset class".

Unstructured data poses particular challenges to traditional legal principles. Copyright has typically been the focus of protection of databases, but unstructured data in particular is not typically the province of the copyright lawyer, given the emphasis in copyright law on expression rather than ideas.

Many questions arise as to legal protection for unstructured data, given much of it may have no useful meaning at all before the data analyst weaves his or her magic. Is such data protected as confidential? Can such collections of information be licensed? These questions are analysed in this paper. In the following section we focus on key areas of law most likely to arise in relation to databases and consider the extent to which they accommodate the realities of Big Data.

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