CC REL: The Creative Commons Rights Expression Language

Abelson, Harold; Adida, Ben; Linksvayer, Mike; Yergler, Nathan R.

doi:10.11647/obp.0019.10

Cited by 35 publications

(32 citation statements)

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“…The Australian National Data Service (ANDS), for instance, has utilized this additional information to allow filtering of data by license -a positive step towards recognition of this issue. Rights Expression Language ODRL [45], MPEG-21 [46], METSRights [47], PRISM [48] Rights Vocabulary Creative Commons REL [49], L4LOD [50], Copyright Ontology [51] Legal Defeasible Rules LegalRuleML [52], CAF [53], LKIF By contrast to the metadata initiatives, which aim to enable functionality, Rights Expression Languages (REL) aim to encode restrictions on the use of content. More specifically rights expression languages provide formal, machine-readable expressions of copyright usually through creating a controlled vocabulary of verbs standing in as restricted actions.…”

Section: B Computing With Legal Knowledgementioning

confidence: 99%

An eScience Tool for Understanding Copyright in Data Driven Sciences

Hosking

Gahegan

Dobbie

2014

2014 IEEE 10th International Conference on E-Science

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Understanding the impacts of copyright is a challenge for the sharing and reuse of our research data. There is growing recognition of the problem, but the legal knowledge required to navigate through the minefield of restrictions and risks is often too difficult to uncover and understand. As of yet there are no appropriate tools to aid researchers, librarians and research policy makers. To address this gap we present Camden, an automated copyright reasoning tool designed to integrate into existing research workflows. At its core, Camden uses dynamically generated defeasible rules to reason over the legality of a situation of using, combining and publishing data, while additionally suggesting potential licenses by which to safely share derived research outputs. This functionality has been wrapped up into an embedded software library and offered as a web application. In this paper we introduce Camden, describe its model of computational reasoning and discuss how it can be included into existing and future eResearch tools and services.

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Section: B Computing With Legal Knowledgementioning

confidence: 99%

An eScience Tool for Understanding Copyright in Data Driven Sciences

Hosking

Gahegan

Dobbie

2014

2014 IEEE 10th International Conference on E-Science

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“…• An RDF binding of Creative Commons, which is a model for licensing the distribution and reuse of works [7].…”

Section: Linked Open Datamentioning

confidence: 99%

Linked open corpus models, leveraging the semantic web for adaptive hypermedia

O'Keeffe

O’Connor

Cass

et al. 2012

Proceedings of the 23rd ACM Conference on Hypertext and Social Media

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Despite the recent interest in extending Adaptive Hypermedia beyond the closed corpus domain and into the open corpus world of the web, many current approaches are limited by their reliance on closed metadata model repositories. The need to produce large quantities of high quality metadata is an expensive task which results in silos of high quality metadata. These silos are often under utilized due to the proprietary nature of the content described by the metadata and the perceived value of the metadata itself. Meanwhile, the Linked Open Data movement is promoting a pragmatic approach to exposing, sharing and connecting pieces of machine-readable data and knowledge on the WWW using an agreed set of best practices. In this paper we present a novel Linked Open Data based personalization framework that leverages the Web of Data to satisfy the metadata requirements of an Adaptive Hypermedia System. Through the implementation of a prototype system we evaluate the effectiveness of this approach as well as identifying the potential issues that arise from building personalization systems based on Linked Open Data. In the traditional, closed model approach to Adaptive Hypermedia (AH), proprietary models that describe aspects of the system and the environment including the user, the domain and the presentation strategy all need to be defined in advance. These systems also need the content which will be used in the generation of presentations to be in a defined format and described using a specific metadata standard. This reliance upon bespoke, proprietary content and models restricts the ease of adoption, scalability and accessibility of such technologies. This paper proposes an Open Model for AH and Adaptive Web (AW) systems. The aim of the paper is to specify both the non-functional and functional properties of this model. Categories and Subject DescriptorsThe Open Model for AH described by this paper proposes utilizing the vast volume of data available on the WWW to address the issues described above. It is proposed to not only gather content from the web, but also to gather the data which describes that content. A number of web technologies have emerges in recent years which make this Open Model achievable. Linked Open Data (LOD) is a practical approach to exposing, sharing and connecting content via the WWW. The structure and links exposed in LOD repositories can be leveraged quickly. This structure has real value in AH as it describes both the content and the domain, which are both basic requirements of AH systems.To further explore the application of this model this paper presents an architectural description and initial evaluation of a demonstrator system that implements this open model using AH and LOD techniques and technologies. The

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“…Policy containment or self-referentiality is not considered there. Similarly, ccREL o«ers an RDF representation for Creative Commons licenses but uses a static name-based encoding that cannot capture the content-based relationships that we model [1]. Using rules in the policy language AIR [18], the meaning of ccREL terms has been further formalised but without attempting to overcome the restrictions of name-based modelling [30].…”

Section: Related Workmentioning

confidence: 99%

ShareAlike Your Data: Self-referential Usage Policies for the Semantic Web

Krötzsch

Speiser

2011

The Semantic Web – ISWC 2011

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Abstract. Numerous forms of policies, licensing terms, and related conditions are associated with Web data and services. A natural goal for facilitating the reuse and re-combination of such content is to model usage policies as part of the data so as to enable their exchange and automated processing. This paper thus proposes a concrete policy modelling language. A particular diAEculty are self-referential policies such as Creative Commons ShareAlike, that mandate that derived content is published under some license with the same permissions and requirements. We present a general semantic framework for evaluating such recursive statements, show that it has desirable formal properties, and explain how it can be evaluated using existing tools. We then show that our approach is compatible with both OWL DL and Datalog, and illustrate how one can concretely model self-referential policies in these languages to obtain desired conclusions.

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CC REL: The Creative Commons Rights Expression Language

Cited by 35 publications

References 0 publications

An eScience Tool for Understanding Copyright in Data Driven Sciences

An eScience Tool for Understanding Copyright in Data Driven Sciences

Linked open corpus models, leveraging the semantic web for adaptive hypermedia

ShareAlike Your Data: Self-referential Usage Policies for the Semantic Web

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