Puneet Kishor, Oshani Seneviratne, and Noah Giansiracusa. 2009. Policy Aware Geospatial Data. ACMGIS 2009, Seattle, Washington. Nov. 2009.
![policyawaregeospatial_data.pdf] Download full paper.
Digital Rights Management (DRM) prevents end-users from using content in a manner inconsistent with its creator’s wishes. The license describing these use-conditions typically accompanies the content as its metadata. A resulting problem is that the license and the content can get separated and lose track of each other. The best metadata have two distinct qualities – they are created automatically without user intervention, and they are embedded within the data that they describe. If licenses are also created and transported this way, data will always have licenses, and the licenses will be readily examinable. When two or more datasets are combined, a new dataset, and with it a new license, are created. This new license is a function of the licenses of the component datasets and any additional conditions that the person combining the datasets might want to impose. Following the notion of a data-purpose algebra, we model this phenomenon by interpreting the transfer and conjunction of data as inducing an algebraic operation on the corresponding licenses. When a dataset passes from one source to the next its license is transformed in a deterministic way, and similarly when datasets are combined the associated licenses are combined in a non-trivial algebraic manner. Modern, computer-savvy, licensing regimes such as Creative Commons allow writing the license in a special kind of language called Creative Commons Rights Expression Language (ccREL). ccREL allows creating and embedding the license using RDFa utilizing XHTML. This is preferred over DRM which includes the rights in a binary file completely opaque to nearly all users. The colocation of metadata with human-visible XHTML makes the license more transparent. In this paper we describe a methodology for creating and embedding licenses in geographic data utilizing ccREL, and programmatically examining embedded licenses in component datasets and determining the resulting license of the composite dataset as determined by the relevant data-purpose algebra. We are inspired by the concept of affordance as it applies in the context of human-computer interaction (HCI). Instead of using technology to make it difficult for the user to do the wrong thing, we want to use technology to make it easy for the user to do the right thing. A technical solution that will assist the user do the right thing can go a long way in easing the burden on the authors creating and distributing licenses along with data, and in easing the burden on the users determining the appropriate use of datasets based on their licenses. This can assist in implementing a policy that protects intellectual property while encouraging sharing and use.