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![Licensing Linked Data
Workshop
I-SEMANTICS 2013 Conference
September 6, 2013
Graz / Austria
Tassilo Pellegrini
firstname.lastname[at]fhstp.ac.at
http://de.slideshare.net/pellegrinit/licensing-linked-data](https://image.slidesharecdn.com/licensinglinkeddata-130905142052-/85/Licensing-Linked-Data-1-320.jpg)
![Licensing Linked Data
Workshop
I-SEMANTICS 2013 Conference
September 6, 2013
Graz / Austria
Tassilo Pellegrini
firstname.lastname[at]fhstp.ac.at
http://de.slideshare.net/pellegrinit/licensing-linked-data](https://image.slidesharecdn.com/licensinglinkeddata-130905142052-/75/Licensing-Linked-Data-1-2048.jpg)
Licensing Linked Data
- 1. Licensing Linked Data Workshop I-SEMANTICS2013 Conference September 6, 2013 Graz / Austria Tassilo Pellegrini firstname.lastname[at]fhstp.ac.at http://de.slideshare.net/pellegrinit/licensing-linked-data
- 2. Introductory Statement: Challengesof Linked Data Licensing • Licensing has been widely neglected in Linked Data R&D • Data licensing is not a trivial issue – especially under conditions of dual licensing • Requires technological knowledge • Requires asset diversification awareness & strategy • Depends on business strategy & models • Is confronted with competing legal regimes (i.e. EU vs. USA) • Data licensing shapes social relationships by granting and restricting access to resources. • (Linked) Data licensing defines the access conditions under which transactions will be performed in the future (by machines). • Exposing licensing information as Linked Data is the precondition for automated rights clearance & brokering systems. Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 2
- 3. Overview 1. The EconomicRationale of Linked Data 2. Creating Licensing Policies for Linked Data 3. Mapping Licenses to Business Models 4. Conclusion Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 3
- 4. The Economic Rationaleof Linked Data
- 5. Metadata Shift Research AreaPre-Web Post-Web Metadata Applications / Uses -- 16 % Cataloging / Classification 14 % 15 % Classifying Web Information -- 14 % Interoperability -- 13 % Machine Assisted Knowledge Organization 14 % 12 % Education 7 % 7 % Digital Preservation/ Libraries -- 7 % Thesauri Initiatives 7 % 5 % Indexing / Abstracting 29 % 4 % Organizing Corporate or Business Information -- 4 % Librarians as Knowledge Organizers of the Web -- 2 % Cognitive Models 29 % 1 % Research Areas in Library and Information Science (Source: Saumure, Kristie; Shiri, Ali (2008). Knowledge organization trends in library and information studies: a preliminary comparison of pre- and post-web eras. In: Journal of Information Science, 34/5, 2008, p. 651–666) Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 5 The survey illustrates four trends: 1) the spectrum of research areas has broadened significantly; 2) certain areas have kept their status over the years (i.e. Cataloging & Classification or Machine Assisted Knowledge Organization), 3) new areas of research have entered the discipline (i.e. Metadata Applications & Uses, Classifying Web Information, Interoperability Issues) and others have declined or dissolved into other areas; 4) metadata issues have significantly increased in importance in terms of the quantity of papers that is explicitly and implicitly dealing with corresponding issues.
- 6. Content-Assets Metadata-Assets Information Load EconomicRelevance Source: Haase,Kenneth (2004). Context for Semantic Metadata. In: MM’04, October 10–16, 2004, New York, New York, USA. ACM Price Waterhouse Coopers (2009). Technology Forecast: Spinning a Web of Data. Spring 2009 Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 6 Metadata as a Network Good „The Value of Metadata rises as the product of the log of the corpus size and the log of the size of the user community increases.“ (Kenneth Haase, 2004) Metcalfe`s Law
- 7. Data in theContent Value Chain Content Acquisition Content Editing Content Bundling Content Distribuiton Content Consumption Harvesting, storage & integration of internal or external data sources for purposes like Content Pooling Semantic analysis, adaptation & linking of data for purposes like Content Enrichment Contextualisation & perso-nalisation of information products for purposes like Landing Pages, Dossiers or Customized Delivery Provision of machine-readable & semantically interoperable data & metadata via APIs or Endpoints Improved findability, navigability & visualization on top of semantic metadata via Semantic Search & Recommenda- tion Engines Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 7 Pellegrini, Tassilo (2012). Semantic Metadata in the News Production Process. Achievements and Challenges. In: Lugmayr, Artur; Franssila, Heljä; Paavilainen, Janne; Kärkkäinen, Hannu (Eds). Proceeding of the 16th International Academic MindTrek Conference 2012, Tampere / Finland. ACM SIGMM, p. 125-133
- 8. Data Traffic Patterns Source:Andreas Blumauer, Semantic Web Company, 2011 Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 8
- 9. Creating Licensing Policies forLinked Data
- 10. Licenses on theLOD Cloud – State of the Art License Number of Datasets License Not Specified 251 Creative Commons Attribution 135 Creative Commons CCZero 72 Creative Commons Attribution Share-Alike 71 Creative Commons Non-Commercial (Any) 49 Other (Attribution) 38 UK Open Government Licence (OGL) 36 Open Data Commons Open Database License (ODbL) 28 Open Data Commons Public Domain Dedication and Licence (PDDL) 27 Other (Not Open) 26 Other (Open) 25 Other (Public Domain) 25 Open Data Commons Attribution License 14 GNU Free Documentation License 9 Other (Non-Commercial) 9 ukcrown-withrights 6 W3C 1 apache 1 gpl-2.0 1 gpl-3.0 1 LicensesontheLODCloud(Source:Pellegrini&Ermilov2013…toappear) Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 10 1) Licensing has long been neglected, but awareness is rising 2) High heterogeneity of licenses (CC, ODC, GPL, APACHE, individual licenses …) 3) Insufficient / unappropriate protection of intellectual assets (not all asset types are covered) 4) The „meaning“ of the various licenses stays implicit (not machine-readable) – source of errors & legal uncertainty A community discussion & standardization process is required to nuture a licensing culture for Linked Data See also Prateek et al. (2013): There is no money in LOD (http://knoesis.wright.edu/faculty/pascal/pub/nomoneylod.pdf)
- 11. Why Linked DataLicensing Matters? • Data is an intellectual asset and can be protected by intelllectual property rights • Licenses secure (y)our property rights – for private and public purposes! • Licenses create a secure business environment • Licenses are an efficient means to diversify business models • Dual Licensing can be used to extend traditional copyright and allow to reuse, share and consume data for purposes not originally intended Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 11
- 12. Protecting Data asIntellectual Property Legal Protection Instruments Copyright Database Right Unfair Practice Patents Linked Data Assets Instance Data Case by Case yes yes Case by Case Metadata Case by Case yes yes Case by Case Ontology yes yes yes Case by Case Content yes no yes no (Services) yes no yes yes (Technology) yes no yes yes Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 12 Pellegrini, Tassilo (2012). Semantic Metadata in the News Production Process. Achievements and Challenges. In: Lugmayr, Artur; Franssila, Heljä; Paavilainen, Janne; Kärkkäinen, Hannu (Eds). Proceeding of the 16th International Academic MindTrek Conference 2012, Tampere / Finland. ACM SIGMM, p. 125-133 Legend: Copyright … protects the originality of creative works. Database Right … protects the investment made in compiling a database, even when this does not involve the 'creative' aspect that is reflected by copyright. Unfair Practices Act … protects against fraud, misrepresentation, and oppressive or unconscionable acts or practices by businesses. Patents … protects a novel solution to a specific technological problem.
- 13. Components of aLinked Data Licensing Policy A Linked Data licensing policy should consist of three components: a machine-readable statement about content-related assets (copyright), a machine-readable statement about database-related assets (database right) and a human-readable Community Norm. • Herein the contents of a linked dataset, which are comprised of the terms, definitions and its ontological structure, are protected by copyright (or Creative Commons). • The underlying database, which is comprised of all independent elements and works that are arranged in a systematic or methodological way and are accessible by electronic or other means, are protected by database right (or Open Data Commons). • The Community Norm explicitly defines the expectations of the rights holder towards “good conduct” when a dataset is being utilized. Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 13
- 14. Benefits & Limitationsof traditional Copyright / Datebase Right • Benefits: • Easy to handle: rights are usually granted automatically at the moment of publication • Internationally established institutions & experience of conduct (legal affairs, trials etc.) • Strong property rights are often the foundation of established business models • Limitations: • Very restrictive – not suiteable to generate network effects or open innovation • Regional differences in legal issues (USA vs. Europe) • Costly & risky to diversify the IPR strategy (i.e. error prone process, learning curves, fears to „let go“) • Hard to enforce Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 14
- 15. Alternative Protection InstrumentsI: Creative Commons Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 15 Creative Commons is an extension to copyright which allows various degrees of freedom to repurpose content via granularly defined constraints. The various licenses can be ordered within a hierarchy of restrictions depending on the usage rights and associated permissions granted by the specific license. • Benefits: • Enables fine granular expression of usage rights • Allows diversification of creation & distribution of assets • Allows diversification of business models • Contributes to the public domain • Limitations: • Complex to handle • Might interfere with etsablished business models • Requires cultural change • Hard to enforce
- 16. Alternative Protection InstrumentsII: Open Data Commons Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 16 Open Data Commons are an extension of Database Right and work analogue to Creative Commons. The various licenses can be ordered within a hierarchy of restrictions depending on the usage rights and associated permissions granted by the specific license. • Benefits: • Enables fine granular expression of usage rights • Allows diversification of creation & distribution of assets • Allows diversification of business models • Contributes to the public domain • Limitations: • Very new instrument – work in progress / little experience • Might interfere with etsablished business models • Requires cultural change • Hard to enforce
- 17. Community Norm I •Beside licensing information expressed by Copyright / Creative Commons and Database Right / Open Data Commons a so called Community Norm is the third component of a Linked Data licensing policy. • A community norm is basically a human-readable recommendation of how the data should be used, managed and structured as intended by the data provider. It should provide administrative information (i.e. creator, publisher, license and rights), structural information about the dataset (i.e. version number, quantity of attributes, types of relations) and recommendations for interlinking (i.e. preferred vocabulary to secure semantic consistency). • Community norms can differ widely in depth and complexity. Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 17
- 18. Community Norm II:Examples Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 18 http://www.embeddedmetadata.org/embedded-metatdata-manifesto.php
- 19. Rights Expression LanguagesI: ODRL • Rights Expression Languages are used to express usage rights about a digital asset in a machine- readable way. • A prominent example is ODRL (Open Digital Rights Language), an XML vocabulary to express rights, rules, and conditions - including permissions, prohibitions, obligations, and assertions - for interacting with online content. See: http://www.w3.org/community/odrl/ • ODRL utilizes an Entity-Attribute-Value Model to express a policy about rights and restrictions associated with a digital artefact. • BUT: ODRL does not provide a licensing attribute. This must be added by referring to other vocabularies like CCREL. • There are several possibilities how to provide the licensing information: • as an annotation of the HTML document using RDFa, • as a complementary document, which reflects the information on the page for machines (RDF/XML, N3, Turtle or other notation), • as a public SPARQL endpoint, which can be queried by applications and users, • as a dump file. Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 19
- 20. Rights Expression LanguagesII: CCREL • The Creative Commons Community has developed CCREL (Creative Commons Rights Expression Language) to represent the various CC licenses in a machine-readable format. See http://www.w3.org/Submission/CCREL/ or http://creativecommons.org/schema.rdf • CCREL complements the ODRL vocabulary. It provides a condensed and hierarchically ordered set of properties that define the actions allowed with certain licenses. These properties can be seamlessly integrated into the ODRL vocabulary and allow to define fine-granular usage policies and constraints associated with a certain asset. • A combination of ODRL and CCREL is not obligatory. The semantic expressivity of CCREL is sufficient to simply annotate existing assets with licensing information for automated processing. But in case of very complex and differentiated usage scenarios a combination of ODRL and CCREL is recommended, as ODRL provides the necessary semantic expressivity to define fine-granular usage policies associated with a certain asset that go beyond the simple explication of licensing information, i.e. for various user groups or stakeholders. Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 20
- 21. Rights Expression LanguagesIII: CCREL Examples • One RDF triple is enough to attach license information to the work, given that the license URI is dereferenceable and described by RDF vocabulary provided by Creative Commons Foundation. Here is a basic example of how the CC-BY license can be attached to the asset (ex:myImage): • @prefix ex: <http://example.org/>. • @prefix cc: <http://creativecommons.org/ns#>. • ex:myImage cc:license <http://creativecommons.org/licenses/by/3.0/> . • Such an RDF document usually complements an asset (an image in our case) on a web page, where the licensing information should be represented in a human-readable fashion (i.e. with HTML). Via the RDF link an application can attain the information necessary for telling its user how this asset can be processed. Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 21
- 22. 1 @prefix xml:<http://www.w3.org/XML/1998/namespace>. 2 @prefix cc: <http://creativecommons.org/ns#>. 3 @prefix foaf: <http://xmlns.com/foaf/0.1/>. 4 @prefix dc: <http://purl.org/dc/elements/1.1/>. 5 @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>. 6 @prefix dcq: <http://purl.org/dc/terms/>. 7 <http://creativecommons.org/licenses/by/3.0/> cc:legalcode <http://creativecommons.org/licenses/by/3.0/legalcode>; 8 cc:licenseClass <http://creativecommons.org/license/>; 9 cc:permits cc:DerivativeWorks, 10 cc:Distribution, 11 cc:Reproduction; 12 cc:requires cc:Attribution, 13 cc:Notice; 14 dc:creator <http://creativecommons.org>; 15 dc:identifier "by"; 16 dc:title "${Attribution} 3.0 ${Unported}"@i18n, ... 108 dcq:hasVersion "3.0"; 109 a cc:License; 110 foaf:logo <http://i.creativecommons.org/l/by/3.0/80x15.png>, 111 <http://i.creativecommons.org/l/by/3.0/88x31.png>. Rights Expression Languages IV: CCREL Examples • Each RDF license includes the necessary information encoded in RDF, such as what is allowed and what is prohibited. For example, the CC-BY-SA 3.0 used in the example is represented as follows: • The code of the CC-BY license defines its URI, legal code, title and other attributes. • The most important properties of this license are stated on lines 9 - 13: an asset under this license can be distributed, reproduced and made derivation from (cc:permits) if notice, sharealike and attribution are provided (cc:requires). Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 22
- 23. Rights Expression LanguagesV: ODC Examples • In contrast to Creative Commons, who have provided CCREL as a machine readable language to express licensing information, ODC licenses are available as plain text only and thus not easily processable by machines. • But as ODC shares several attributes and characteristics with CC it is possible and reasonable to apply attributes from the CCREL vocabulary. • On the right you see an example how to combine ODC licensing information with CCREL expressions (lines 7 - 11). Herein the description of the license inside the dataset about a database is the same as in the previous CCREL example. Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 23 1 @prefix xml: <http://www.w3.org/XML/1998/namespace>. 2 @prefix cc: <http://creativecommons.org/ns#>. 3 @prefix foaf: <http://xmlns.com/foaf/0.1/>. 4 @prefix dc: <http://purl.org/dc/elements/1.1/>. 5 @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>. 6 @prefix dcq: <http://purl.org/dc/terms/>. 7 @prefix ex: <http://example.org/> 8 ex:myDatabase 9 cc:attributionName "Name of the author"^^xsd:string; 10 cc:attributionURL <http://firstname.lastname.me/>; 11 cc:license <http://opendatacommons.org/licenses/by/1.0/>. 12 <http://creativecommons.org/licenses/by/3.0/> cc:legalcode <http://creativecommons.org/licenses/by/3.0/legalcode>; 13 cc:licenseClass <http://creativecommons.org/license/>; 14 cc:permits cc:DerivativeWorks, 15 cc:Distribution, 16 cc:Reproduction; 17 cc:requires cc:Attribution, 18 cc:Notice; 19 dc:creator <http://creativecommons.org>; 20 dc:identifier "by"; 21 dc:title "${Attribution} 3.0 ${Unported}"@i18n, ... 113 dcq:hasVersion "3.0"; 114 a cc:License; 115 foaf:logo <http://i.creativecommons.org/l/by/3.0/80x15.png>, 116 <http://i.creativecommons.org/l/by/3.0/88x31.png>.
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- 25. Instance Data Metadata Ontology Content Services Technology Stakeholders Revenue Model Linked Data Assets LinkedData Business Cube Subsidies Subscription Advertising Certification Affiliate Program Value Add Traffic / SEO Branding Revenue Model Legend: Subscription: Selling data & services access Advertising: Sell paid placements / advertisements inside data feeds & services Certification: Charge for reviews, verification, compliance checks, quality assurance Affiliate Program: Charge for affiliate links within data feeds or services Value Add: Utilizing Linked Data to enhance data sets & services Traffic / SEO: Utilizing Linked Data to improve findability & generate traffic Branding: Provide data sets, vocabs & ontologies to shape market & fuel data driven applications Subsidies: Public / non-profit funding & regulatory publishing policies (Adopted from Brinkner (2010): http://chiefmartec.com/2010/01/the- 8th-linked-data-business-model/) Stakeholder Legend: Internal … within a company // Partners … Between strategic partners // B2B … Business to Business // B2G … Business to Government // B2C … Business to Customer // C2C … Customer to Customer / Co2Co … Community to Community
- 26. Mapping Licenses toBusiness Models – A Discussion Proposal Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 26 Instance Data Metadata Ontology Content Services Technology / App Subsidies CC / ODC ODC CC / ODC CC CC / FOSS / ToT FOSS / ToT Branding CC / © / ODC / DBR ODC CC / ODC CC / © CC / FOSS / ToT FOSS / © / ToT Traffic / SEO CC / © / ODC / DBR ODC CC / ODC CC / © CC / FOSS / ToT n.r. Value Add CC / © / ODC / DBR ODC / DBR CC / ODC CC / © CC / © / FOSS / ToT n.r. Affiliate Prog. CC / © / ODC / DBR ODC / DBR CC / © / ODC / DBR CC / © CC / © / FOSS / ToT FOSS / © / ToT Certification CC / © / ODC / DBR ODC / DBR CC / © / ODC / DBR CC / © © / ToT © / ToT Advertising CC / © / ODC / DBR ODC / DBR CC / © / ODC / DBR CC / © © / ToT © / ToT Subscription © / DBR ODC / DBR CC / © / ODC / DBR © © / ToT © / ToT Legend: CC … Creative Commons // ODC … Open Data Commons // © … Copyright // DBR … Database Right // FOSS … Free & Open Source License // ToT … Terms of Trade // n.r. … not relevant
- 27. Mapping Licenses toStakeholders – A Discussion Proposal Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 27 Instance Data Metadata Ontology Content Services Technology / App Internal © / DBR DBR © / DBR © © / ToT © / ToT Partners CC / © / ODC / DBR ODC / DBR CC / © / ODC / DBR CC / © © / ToT FOSS / © / ToT B2B CC / © / ODC / DBR ODC CC / ODC CC / © CC / FOSS / ToT FOSS / © / ToT B2G CC / © / ODC / DBR ODC CC / ODC CC / © CC / © / FOSS / ToT FOSS / © / ToT B2C CC / © / ODC / DBR ODC CC / © / ODC / DBR CC / © CC / © / FOSS / ToT FOSS / © / ToT C2C CC / © / ODC / DBR ODC / DBR CC / © / ODC / DBR CC / © CC / © / FOSS / ToT FOSS / © / ToT Co2Co CC / ODC ODC CC / ODC CC CC / FOSS CC / FOSS Legend: CC … Creative Commons // ODC … Open Data Commons // © … Copyright // DBR … Database Right // FOSS … Free & Open Source License // ToT … Terms of Trade // n.r. … not relevant
- 28. Linked Data Licensing– How others do it …* Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 28 Instance Data Metadata Ontology Content Services Technology / App BBC (Sports) © / DBR CC-BY 3.0 CC-BY 3.0 © ?? ?? NYT (Subject Headings) CC-BY 3.0 CC-BY 3.0 CC-BY 3.0 © ToT n.r. The Guardian (Music Albums) ?? ?? ?? ?? ToT n.r. DBpedia CC-BY-SA 3.0 / GNU FDL CC-BY-SA 3.0 / GNU FDL CC-BY-SA 3.0 / GNU FDL CC-BY-SA 3.0 / GNU FDL Misc. Misc. MusicBrainz CC0 CC0 CC0 CC-BY-NC-SA 3.0 CC-BY-NC-SA 3.0 GPLv2 GeoNames CC-BY 3.0 CC-BY 3.0 CC-BY 3.0 CC-BY 3.0 ToT ToT Legend: CC … Creative Commons // ODC … Open Data Commons // © … Copyright // DBR … Database Right // FOSS … Free & Open Source License // ToT … Terms of Trade // n.r. … not relevant * Please consider that these licensing policies have regional limitations due to differing regulatory regimes!
- 29. Conclusion: Challenges ofLinked Data Licensing • Linked Data Licensing is technologically simple, but business-wise complex. • Linked Data Licensing is a context sensitive issue and requires a good understanding of the intersections of technology, law and business development • Assets & stakeholders • Markets & ressources • Regulatory & legal conditions • Technology & infrastructure • Linked Data Licensing challenges traditional business models & culture … can be considered a „radical innovation“ • FUTURE: Linked Licensing Data will bring about new applications & services for rights clearance, publishing & billing purposes ... High transformation potential for ecommerce & procurement! Prof. Dr. Tassilo Pellegrini, University of Applied Sciences St. Pölten, Licensing Linked Data 29