While it is preferable that Linked Data is published without access or licence restrictions, there will always remain certain datasets which, perhaps due to financial considerations, cannot be published as Linked Open Data. If these valuable datasets do join the Web of Linked Data, it will be as Linked Closed Data - Linked Data with access and license restrictions. In this paper, we outline a research agenda for Linked Closed Data that considers the effects that access and license restrictions may have on the Web of Linked Data. If implemented poorly, access restrictions have the potential to break URI resolvability, but even when implemented well, we can expect them to affect dataset selection processes and inter-dataset link creation rates. Additionally, there remains the technical challenge of developing and standardising access restriction and automated payment techniques for the Web of Linked Data

Black, Jennifer

Carr, Les

Cobden, Marcus

Gibbins, Nicholas

Shadbolt, Nigel

English

Southampton (e-Prints Soton)

A Research Agenda for Linked Closed Data(vision paper)Marcus Cobden, Jennifer Black, Nicholas Gibbins, Les Carr, and NigelShadbolt{mc08r,jlb08r,nmg,lac,nrs}@ecs.soton.ac.ukUniversity of Southampton, UKAbstract. While it is preferable that Linked Data is published withoutaccess or licence restrictions, there will always remain certain datasetswhich, perhaps due to nancial considerations, cannot be published asLinked Open Data. If these valuable datasets do join the Web of LinkedData, it will be as Linked Closed Data { Linked Data with access and li-cense restrictions. In this paper, we outline a research agenda for LinkedClosed Data that considers the eects that access and license restrictionsmay have on the Web of Linked Data. If implemented poorly, access re-strictions have the potential to break URI resolvability, but even whenimplemented well, we can expect them to aect dataset selection pro-cesses and inter-dataset link creation rates. Additionally, there remainsthe technical challenge of developing and standardising access restrictionand automated payment techniques for the Web of Linked Data.1 IntroductionTo date, most research from the Linked Data community has focussed on LinkedOpen Data and failed to consider its logical counterpart Linked Closed Data. ByLinked Closed Data, we refer to datasets which adhere to the principles of LinkedData publishing, but for which access to and use of the data is subject to legal ortechnical restrictions which go beyond attribution and share-alike obligations.Linked Closed Data may seem at odds with the aims of the Linked Datacommunity, however, this is not necessarily the case. Undoubtedly it would bea shame if existing `open' datasets changed to a `closed' publishing model, butit would still be preferable to the datasets becoming completely unavailable dueto nancial pressures on their publishers.High quality data has value. If we wish to see more high quality datasetspublished as Linked Data, we must provide incentives for publishers to do so.Prot is arguably the most signicant publishing incentive, and so, revenue mod-els, and how they interact with Linked Data publishing patterns, are of greatimportance to the future of the Web of Linked Data.While publishing `open' datasets is to be commended, we anticipate thatfew companies will be prepared, or able, to make their data available withoutsome access or licence restrictions. Ordnance Survey, Great Britain's nationalmapping agency, is in this position; they are required to operate as a self-fundedorganisation through the commercial sale of mapping data. Oering all theirdata for free would undermine their primary source of income.2 A Research Agenda for Linked Closed DataThe Times and The New York Times newspapers both used to oer freeaccess to articles on their Web site, recently, however, they both adopted asubscription-based access model for their Web content. Crucially, unlike TheTimes, The New York Times allows non-subscribers free access to view up to 20articles per calendar month. Despite the dierence in markets, the introductionof paid access may be comparable to the addition of restrictions to Linked Datapublishing.It is imperative that we fully understand the implications of Linked ClosedData so that we can be sure that desirable properties of the Web of Data will notbe lost in the face of access and license restrictions. Against this background, inthis paper we identify the key research challenges posed by Linked Closed Data.2 Access and LicensingWhile we describe datasets as `open' and `closed', reality is less clear-cut; in prac-tice we observe a spectrum of `openness', which varies with the access restrictionsa dataset is published with (who is permitted to `see' the data), and the licenceunder which access is granted (what they are permitted to do with the data).2.1 Access restrictionsAccess to a dataset may be: completely open, restricted only by the resources ofthe dataset host; restricted, open to users who meet specic access criteria; orprivate, open only to its owner. If badly realised, access restrictions have the po-tential to undermine the resolvability of Linked Data URIs and to dis-incentivisethe creation of inter-dataset links. The resolvability of a URI would be under-mined if, due to access restrictions, it is no longer possible to resolve that URI toa description document. Access restrictions might also remove any useful infor-mation from a URI description document. Creating links to a restricted datasetis less worthwhile if URIs within it cannot be resolved to a useful description.2.2 Dataset licencesDataset licences range from public domain dedications (where all intellectualproperty rights are waived)[9], to permissive licences (which may impose any-thing from attribution, to more weighty obligations such as copyleft) to restric-tive licences (which specify permitted uses of a dataset). Currently, 85% of thedatasets in the Linked Data Cloud do not declare any license [2].We are unlikely to see a restrictive license on a dataset without also encoun-tering access restrictions; if access is open and practically anonymous, licensebreaches would be dicult to detect and punish. Since it is only worthwhile im-posing license restrictions on valuable data, we expect that the publisher wouldalso take the step of imposing access restrictions to protect its investments.3 Business modelsThe `openness' of a dataset is generally determined by the business model ofthe publisher. A range of business models have been proposed for Linked DataA Research Agenda for Linked Closed Data 3publishers, including subsidised publishing, subscription or micropayment-basedaccess, sponsorship/advertising funded publishing, and loss-leader models (todrive interest or sales in other products, or to shape markets) [3].Broadly, we can classify these business models into those which oer only freeaccess products, only paid access products, or some combination of both. Therevenue models of the individual products these business models are build fromcan also be split between free and paid access. We can then further categorisethem by how their costs are recovered:Advertising supported Costs are covered by revenue from advertising withinthe content. We consider this to cover both per-view advertising payments,and per-sale commission through aliate links.Loss-leader Costs are written o as an investment. Loss-leader models mayattempt to drive interest in other products, or perhaps to shape markets inthe hope of future sales.Subsidised Costs are covered by some form of sponsorship or subsidy. Commonin public sector undertakings.Free access models should, in theory, employ at least one of these strategies,though our list is not exhaustive. Equally, paid access models might employ anycombination of these to complement revenue from access payments. Currently,all Linked Data publishers operate under loss-leader or subsidy-based revenuemodels { none have adopted paid access or advertising supported revenue models.In the last year, Ordnance Survey have begun to oer free access to someof their data. These free datasets include postcode location data, electoral andadministrative boundaries, and gazetteer (at 1:50000 scale), though only someof these are published as Linked Data. Currently, as they oer no paid accessLinked Data, this is likely to be a loss-leader exercise, perhaps to demonstratewhat is possible with their premium subscriptions, or to shape the market inanticipation of a paid oering. Coupling a premium Linked Data product with afree version may be an eective way of mitigating the eects of access restrictionson phenomena such as link creation, providing they use the same URIs, and URIresolvability is maintained.4 Research ChallengesThe addition of access restrictions to Linked Data publishing systems and theemergence of datasets published under proprietary licenses will be an inevitablefact of commercial Linked Data. These changes will alter our expectations ofURI resolvability and change the ways in which we use Linked Data.We have identied six key challenges which are important in a Linked Dataecosystem where not all data is free { they are: i) building dataset reputation,ii) developing access, authentication and payment protocols, iii) fostering linksbetween datasets, iv) managing condential data, v) respecting license terms,and vi) validating business models. We elaborate further on these in the remain-der of this section.4 A Research Agenda for Linked Closed Data4.1 Building reputationAccess restrictions make it all the more important for a dataset to have a goodreputation. Without access, prospective users will be unable to evaluate whetherthe dataset meets their needs before they commit to a purchase. Reputationand word of mouth are a common means through which users judge whether aproduct meets their requirements when considering a purchase.Unfortunately there are few incentives to risk purchasing access to a datasetof unknown quality, so new and untried datasets are unlikely to create a rep-utation for themselves. To combat this bootstrapping problem, publishers willneed to improve their reputation through other means; perhaps by (temporarily)removing access restrictions, or by seeking endorsements from trusted authori-ties. Freemium revenue models [1] and free time- or extent-limited licences area common means of providing access to prospective customers. Future researchis needed to explore this area in more detail, and to identify other dataset rep-utation bootstrapping techniques.4.2 Access, authentication and paymentThe issue of restricting access to closed datasets poses clear technical challenges.HTTP content negotiation and redirection allows dierent documents to beserved in response to a URI resolution attempt. Similar methods are neededfor restricted-access datasets in order to eld requests between free and paidcontent. Additionally, a new vocabulary is needed with which one can declarethe presence of related documents which require payment to access, otherwisepremium content may not be discoverable.Authentication is a requirement of any access restriction techniques. Thefoundations for authentication are already being laid; the W3C WebID incubatorgroup is standardising TLS client certicate based authentication [4].Finally, in order for automated access to premium content to succeed beyondisolated individual publishers, we must standardise the means by which we indi-cate that payment is needed, and the methods by which payment can be made.The HTTP `402 Payment Required' response code has long been reserved, butno standards have yet specied how it should be used [6].4.3 Fostering linksRestricting access to a dataset may also negatively impact how likely externalsources are to create links to that dataset. Inter-dataset links are said to addvalue to datasets, and incoming links provide a form of advertisement and en-dorsement for the target dataset.Publishers of Linked Closed Data will need to take into account the eectthat their particular access and licensing schemes may have on incoming linkcreation rates. Datasets with schemes which permit some degree of free accessmay maintain a higher rate of link creation than those under more restrictiveschemes. The dierent paid access models adopted by The Times and The NewYork Times may allow us to examine how access restriction aects link creationon the Web, although whether this translates to a Semantic Web context remainsan open research question. Further research is needed to examine this behaviourin detail, and to explore other means of encouraging link creation.A Research Agenda for Linked Closed Data 54.4 Managing condentialityIt is not inconceivable that linked datasets might contain sensitive information.While authentication and authorisation schemes can be used to limit accessto restricted information, the challenges posed by condential data go beyondaccess, particularly in systems containing mixed condentiality-level data.Care must be taken that sensitive information cannot be inferred from non-sensitive data. For example, unique identication number ranges with unex-plained gaps may suggest hidden information. Further, a Linked Data system,which adheres to current best practices, might inadvertently admit the existenceof a sensitive URI by responding with an `HTTP 403: Forbidden' response codeinstead of an `HTTP 404: Not Found'. While this alone means little, if the URIcontains embedded information, or can be correlated with other available data,it may constitute a breach of condentiality.Examining the issues in detail, and publishing amended best practices forpublishing Linked Data in the presence of condential information, remains anopportunity for future research.4.5 Respecting licensesAs we mentioned in Section 2.2, there are a wide range of common licenceswhich datasets might be licensed under. Standardised licences, such as the GNUPublic Licences (GPL), Creative Commons (CC) and Open Database Licences(ODBL), often oer variants with additional restrictions such as attribution,non-commercial use, and copyleft sharing requirements. Some of these licences,such as the GPL and CC, may eventually fall out of favour for Linked Data asthey were not designed to be used in this context [9]. Governments often havetheir own licenses for data, for example the United Kingdom's Open GovernmentLicence (OGL).Dataset licenses present two main challenges: tracking the licences underwhich data was received, and respecting the license conditions. In order to be ableto honour license restrictions, Linked Data systems need to maintain appropriateprovenance records of license conditions. Provenance is an active area of researchfor Linked Data [8], and we expect that once provenance-aware systems reachmaturity much of this will be automated.Ensuring adherence to dataset licenses is a more dicult research challenge.Interpreting licenses condently and accurately requires legal training. Ideallystandard licenses would include an approved machine-understandable descrip-tion of the license, describing how a dataset might be used. Existing work hasexplored the potential of this approach [7]; however, further work is needed toapply this to common license conditions.4.6 Validating business modelsWhile many business models have been proposed for the Semantic Web andLinked Data publishers [3], it remains to be seen how many of them will proveviable. Some, such as advertising-supported Linked Data publishing, have been6 A Research Agenda for Linked Closed Datacalled into question somewhat [5]; however, ultimately, the success of any busi-ness model will depend upon the market conditions in which is employed. Nonethe-less, until there exist successful businesses built around these models, we mustconsider them unsolved research challenges.5 ConclusionsIn this paper, we introduced the notion of Linked Closed Data: Semantic Webdatasets which are published in accordance with Linked Data principles, butwhich include access and licence restrictions. While we described Linked ClosedData as the logical counterpart to Linked Open Data, license restrictions arealready common among `Open' datasets (although they usually only requireattribution as the source of the data); the addition of access restrictions is ofgreater signicance. We argued that Linked Closed Data is likely to be theform of Linked Data publishing ultimately adopted by commercial Linked Datapublishers when oering premium, paid access products, as they are likely torequire some form of access restriction.Finally, we identied six research challenges which are of new, or increased,signicance when considering the eect of access and license restrictions on theWeb of Data. These are: building dataset reputation despite access restrictions;developing and standardising access, authentication and payment protocols; fos-tering the creation of links to access restricted datasets; managing condentialdata; tracking data licenses and ensuring license adherence; and the validationof Linked Data business models.References1. Anderson, C.: Free: The Future of a Radical Price: The Economics of Abundanceand Why Zero Pricing Is Changing the Face of Business. Random House Books(Aug 2009)2. Bizer, C., Jentzsch, A., Cyganiak, R.: State of the LOD Cloud (Aug 2011), http://www4.wiwiss.fu-berlin.de/lodcloud/state/3. Brinker, S.: Business models for linked data and web 3.0 (Mar 2010), http://www.chiefmartec.com/2010/03/business-models-for-linked-data-and-web-30.html4. Corlosquet, S., Sporny, M., Inkster, T., Story, H., Harbulot, B., Bachmann-Gm ur,R.: WebID 1.0 - Web Identication and Discovery (Draft) (Feb 2011), http://www.w3.org/2005/Incubator/webid/spec/5. Dodds, L.: Thoughts on Linked Data Business Models (Jan 2010), http://www.ldodds.com/blog/2010/01/thoughts-on-linked-data-business-models/6. Fielding, R., Gettys, J., Mogul, J., Frystyk, H., Masinter, L., Leach, P., Berners-Lee, T.: Hypertext Transfer Protocol { HTTP/1.1. RFC 2616 (Draft Standard) (Jun1999), updated by RFC 28177. Hanson, C., Kagal, L., Berners-Lee, T., Sussman, G., Weitzner, D.: Data-purposealgebra: Modeling data usage policies. In: POLICY '07. pp. 173 {177 (Jun 2007)8. Hartig, O.: Provenance information in the web of data. Proceedings of the 2ndWorkshop on Linked Data on the Web (LDOW2009) (Jan 2009)9. Miller, P., Styles, R., Heath, T.: Open data commons, a license for open data. In:Proceedings of the WWW2008 Workshop on Linked Data on the Web (LDOW)(2008)

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A Research Agenda for Linked Closed Data

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