Abstract
This chapter is an introduction to the Semantic Web, the Web of Data, regulatory models, and the law. It does not take anything for granted. The first part of the chapter describes the languages of the Semantic Web, and shows how the perspective of the Web of Services and Linked Data is related to the conditions under which services can be offered, managed and used. The Web has been massively populated with both data and services. Semantically structured data, the Linked Data Cloud, allows and fosters human-machine interaction. Linked Data aims at creating ecosystems to facilitate the browsing, discovery, exploitation and reuse of datasets for applications. Licensed Linked Data is offered along with information about the rights involved. Rights Expression Languages are able to regulate half-automatically the use and reuse of content.
The second part of the chapter shows that the nature of law is experiencing a deep transformation in the cloud. What links the information flow, social intelligence, rights management, and modelling in the Web of Data is the pragmatic approach —what we call the pragmatic turn, i.e. the representation of users’ needs and contexts to facilitate the automated interactive and collective management of knowledge. Both ontology building and knowledge acquisition share this perspective. The Web of Data brings about new challenges on agency, knowledge, communication, and the coordination of actions. Institutions can regulate both human and machine behaviours within these new environments. Licensed Linked Data, Licensed Linguistic Linked Data, Right Expression Languages, Semantic Web Regulatory Models, Electronic Institutions, Artificial Socio-cognitive Systems are examples of regulatory and institutional design (Regulations by Design). Regulatory systems become more complex in the cloud, in order to be simpler.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-3-319-44601-1_18
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Notes
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- 2.
See the last version of the famous SW ‘cake’ or stake of languages by T. Berners-Lee at http://www.w3.org/2007/03/layerCake.png
- 3.
“The act of retrieving a representation of a resource identified by a URI is known as dereferencing that URI. Applications, such as browsers, render the retrieved representation so that it can be perceived by a user. Most Web users do not distinguish between a resource and the rendered representation they receive by accessing it” (Lewis 2007).
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Folksonomies relate to crowdsourcing. They are usually understood as a system in which users apply public tags to online items. We will define ontologies and come back in the next sections on this particular problem.
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REL were born in the early nineties, when Mark Stefik developed at Xerox PARC a language that would became the eXtensible Right Markup Language (XrML). Permissions and restrictions can be modelled according to Creative Commons principles (ccREL), Open Digital Rights Language (ODRL), MPEG-21, or national copyright protections. There is no universal Right Expression Language, but many —among the more relevant: ODRL, MPEG-21 REL, XACML, ccREL, MPEG-21, MVCO and WAC (Rodríguez-Doncel et al. 2013a; 2013b).
- 11.
https://www.w3.org/community/odrl/model/2.1/ See a recollection of models at http://delicias.dia.fi.upm.es/~vrodriguez/pdf/Poster-LicensingPatternsForLinkedData.pdf
- 12.
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W3C Working Group Note, Web Services Glossary, http://www.w3.org/TR/2004/NOTE-ws-gloss-20040211/#webservice
- 15.
Gartner’s 2014 hype for emerging technologies, https://www.gartner.com/doc/3100227
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- 17.
RuleML is a markup language to express rules in XML for inferential purposes and reasoning. Vid. an introduction to LegalRuleML principles in Athan et al. (2015).
- 18.
“EPs are considered as disclosures about an ‘object’ (e.g. patents-norms/ precedents/guidelines) of law, with its pragmatics referring to the context in which such an ‘object’ is understood and applied by a ‘reasonable man’” (Ramakrishna and Paschke 2014: 312). See also Weigand and Paschke (2012), and Paschke (2013).
- 19.
https://www.w3.org/community/hydra/, spec. published by the W3C Hydra Community Group.
- 20.
“For knowledge-based systems, what “exists” is exactly that which can be represented. When the knowledge of a domain is represented in a declarative formalism, the set of objects that can be represented is called the universe of discourse. This set of objects, and the describable relationships among them, are reflected in the representational vocabulary with which a knowledge-based program represents knowledge. Thus, we can describe the ontology of a program by defining a set of representational terms. In such an ontology, definitions associate the names of entities in the universe of discourse (e.g., classes, relations, functions, or other objects) with human-readable text describing what the names are meant to denote, and formal axioms that constrain the interpretation and well-formed use of these terms.” (Gruber 1993, 1).
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- 23.
“Model-theoretic semantics (and sound and complete reasoning based on it) functions as a gold standard, but applications dealing with large-scale and noisy data usually cannot afford the required runtimes. Approximate methods, including deductive ones, but also approaches based on entirely different methods like machine learning or nature inspired computing need to be investigated, while quality assurance needs to be done in terms of precision and recall values (as in information retrieval) and not necessarily in terms of soundness and completeness of the underlying algorithms.” (Hitzler and van Harmelen 2010, 39).
- 24.
See the state of the art in law and the semàntic web, summarising fifteen years of research at Casanovas et al. (2016).
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- 26.
- 27.
- 28.
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- 30.
tuple DF = <O, L, I, CL, Time>, where O stands for Ontology, L stands for language for domain content, I is the set of Illocutionary particles, CL is the agent (communication) language, Time is a discrete and partially ordered set of instants.
- 31.
Cfr. Ossowski (2013) for the state of the art in agreement technologies. An example of electronic institution for mediation purposes can be found at the Annex of the Catalan White Book on Mediation (Spanish version), cfr. Noriega and López del Toro (2009), http://www.llibreblancmediacio.com/. For the full study, cfr. Poblet et al. (2010a), and Casanovas et al. (2009).
- 32.
This is the approach proposed by Searle (1995) —X counts as Y in context C. According to Searle, the underlying principles in any society are quite simple: (i) collective intentionality, (ii) the assignment of function, (iii) constitutive or institutional structures: function-status assignments that take the form X counts as Y in context C. “What is an institution? An institution is any collectively accepted system of rules (procedures, practices) that enable us to create institutional facts” (Searle 2005). Cfr. Searle (2010) for further developments of the same thesis. This perspective stems from philosophy of language, not from empirical social sciences. Tuomela (2011) contends that the emergence of intentional collective action goes beyond Searle’s individualistic account based on speech act theory. Cfr. Bolander et al. (2014).
- 33.
See especially the example furnished by Singh et al. (2013, 192 and ff.) as part of the NSFfunded Ocean Observatories Initiative (OOI), a thirty-year $400 million project, with thousands of stakeholders (ocean scientists, resource providers, technicians, operators, policy makers, application developers, and the general public). “OOI provides novel capabilities for data acquisition, distribution, modelling, planning and control of oceanographic experiments, with the main goal of supporting long-term oceanographic and climate research”.
- 34.
This work has been carried out under the projects: DER2012-39492-C02-01 CROWDSOURCING, IPT-2012-0968-390000 CROWDCRISISCONTROL and the Australian Project CRC Data2Decisions. We thank Pablo Noriega and Marta Poblet for previous reading and useful comments.
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Casanovas, P., Rodríguez-Doncel, V., González-Conejero, J. (2017). The Role of Pragmatics in the Web of Data. In: Poggi, F., Capone, A. (eds) Pragmatics and Law. Perspectives in Pragmatics, Philosophy & Psychology, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-44601-1_12
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