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Data is perceived to be a key asset in the digital economy. Many governments have been keen to promote and exploit data driven economies. Data scraping is a widely used technique that automatically extracts information from different (often online) sources, whilst data mining is the machine reading of data to identify useful information not immediately obvious on human reading. In 2014, the UK implemented a limited exception to copyright law for text and data mining (TDM). However, copyright is only one layer of legal protection available to ‘data’ and the protection of data has been the subject of a long-running tension between property based rights and concurrent protection for data owners in liability rules arising through competition and contract law. Maintaining an appropriate balance between protecting rightholders and users has remained problematic. This paper summarises the legal protection available in the UK for different types of data, and the (limited) interpretation of that protection by the UK courts. The analysis is situated in a review of the academic literature. Ultimately this paper will conclude that the layered protection for data is confusing for end users, and that the case law on the protection and exceptions available to those seeking to engage in TDM limited and fact dependent.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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