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Complexity and efforts of rights clearance

by taspel | November 07, 2016


Licenses express permissions and obligations associated with a protectable asset as defined by copyright law or competition law. Licenses control access to, usage of, and transactions on top of digital assets - be it under conditions of property rights (all rights reserved) or public domain (no rights reserved) (Fig. 1).[1]

dalicc-data-governance

Figure 1: Governance of Data Licensing

The growing popularity especially of protective and permissive licenses (some rights reserved) has added to the complexity of rights clearance in the commercial exploitation of derivative works. As a consequence a wide array of data publishing guidelines were recommended[2],[3],[4], giving expression to the fact that licensing of data is a fairly new kind of economic practice and still subject to debate concerning the adequate design of licensing policies.[5],[6],[7],[8] This is supported by a recent survey conducted by Ermilov & Pellegrini [9] on 441.315 publicly accessible datasets. The situation is characterized by 1) insufficient documentation of licensing information (64% of all datasets had no licenses at all), 2) a high degree of license heterogeneity (more than 60 different license types), and 3) the absence of machine-readable licenses as a foundation for the automated clearance of compatibility issues.[10] Hence, the creation of derivative data works, i.e. for purposes like content creation, service delivery or process automation, is often accompanied by legal uncertainty about usage rights and high costs in the clearance of rights issues.[11]

The efforts of license clearance increase nearly exponentially with each additional source added to a system [f(n)= n*(n-1)/2]. According to Frangos (2015) these efforts can be a serious obstacle to a company to create new products and services.[12] Large companies usually operate rights clearance centres that manually evaluate legal issues in the repurposing of existing works (i.e. open source software). Such undertakings are costly in terms of time and expert knowledge needed, and often out of scope especially for small and medium sized enterprises. This is not just an obstacle to the emergence of new business models associated with data, but also slows down the rate of adoption of new data management practices, especially in the context of open innovation practices and the commercial reutilization of existing and future data assets towards “a coherent European data ecosystem”. [13]

Sources:

[1] Ball, Alex (2014). How to License Research Data. A Digital Curation Centre and JISC Legal ‘working level’ guide.

[2] Guibault, L. M. (2011). Open content licensing: from theory to practice. Amsterdam: Amsterdam Univ. Press.

[3] Hyland, B., & Wood, D. (2011). The Joy of Data - A Cookbook for Publishing Linked Government Data on the Web. In D. Wood (Hrsg.), Linking Government Data (S. 3–26). New York, NY: Springer New York.

[4] Frosterus, M., Hyvönen, E., & Laitio, J. (2011). Creating and Publishing Semantic Metadata about Linked and Open Datasets. In D. Wood (Hrsg.), Linking Government Data (S. 95–112). New York, NY: Springer New York.

[5] Archer, Phil et al. Study on business models for Linked Open Government Data. ISA programme by PwC EU Services. European Union, 2013.

[6] Pellegrini, T. (2014). Linked Data Licensing – Datenlizenzierung unter netzökonomischen Bedingungen. In E. Schweighöfer et al. (Hrsg.), Transparenz. 17. Int. Rechtsinformatik Symposium IRIS 2014. Wien: OCG Verlag.

[7] Sonntag, Michael (2006). Rechtsschutz für Ontologien. In e-Staat und e-Wirtschaft aus rechtlicher Sicht. Stuttgart: Richard Boorberg Verlag.

[8] Sande, Miel Vander; Portier, Marc; Mannens, Erik; Van de Walle, Rik (2012).  Challenges for open data Usage: Open Derivatives and Licensing. In: https://www.w3.org/2012/06/pmod/pmod2012_submission_4.pdf, accessed February 12, 2016

[9] Ermilov, I., & Pellegrini, T. (2015). Data licensing on the cloud: empirical insights and implications for linked data (S. 153–156). ACM Press.

[10] Similar results are reported by Jain et al. especially with respect to the large variety of licenses in European data clouds. See also: P. Jain, P. Hitzler, K. Janowicz, and C. Venkatramani (2013). There's no money in linked data. In: http://knoesis.wright.edu/pascal/pub/nomoneylod.pdf

[11] Houghton, John (2011). The Costs and Benefits of Data Provision. Report to the Australian National Data Service. Centre for Strategic Economic Studies, Victoria University

[12] Frangos, John (2015). New Transparency in Licensing:  Overview of the Licensing Facilitation Act. In: Informed Counsel, 6/1, p. 2

[13] European Commission (2014). Towards a thriving data-driven economy. Brussels, 2.7.2014, COM(2014) 442 final

Tags: 

compatibility issues, data ecosystem, data governance, open data, rights clearance

Category: 

Data Governance, Project Details

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