Licensing Linked Data

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

Introductory Statement: Challenges of 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

Overview
1. The Economic Rationale of Linked Data
2. Creating Licensing Policies for Linked Data
3. Mapping Licenses to Business Models
4. Conclusion
3

The Economic Rationale of
Linked Data

Metadata Shift
Research Area Pre-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.

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
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

Data in the Content 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
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

Data Traffic Patterns
Source: Andreas Blumauer, Semantic Web Company, 2011
8

Creating Licensing Policies
for Linked Data

Licenses on the LOD
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)

Why Linked Data Licensing 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
11

Protecting Data as Intellectual 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.

Components of a Linked 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.
13

Benefits & Limitations of 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
14

Alternative Protection Instruments I: Creative
Commons
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

Alternative Protection Instruments II: Open
Data Commons
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

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.
17

Community Norm II: Examples
18
http://www.embeddedmetadata.org/embedded-metatdata-manifesto.php

Rights Expression Languages I: 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.
19

Rights Expression Languages II: 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.
20

Rights Expression Languages III: 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.
21

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).
22

Rights Expression Languages V: 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.
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>.

Mapping
Licenses to Business Models

Instance Data
Metadata
Ontology
Content
Services
Technology
Stakeholders
Revenue
Model
Linked
Data Assets
Linked Data
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

Mapping Licenses to Business Models – A
Discussion Proposal
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

Mapping Licenses to Stakeholders – A
Discussion Proposal
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:

Linked Data Licensing – How others do it …*
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:
* Please consider that these licensing policies have regional limitations due to differing regulatory regimes!

Conclusion: Challenges of Linked 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!
29

Licensing Linked Data

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