Weaving a Web of Linked Resources

Weaving a Web of Linked Resources

Semantic Web 8 (2017) 767–772 767 DOI 10.3233/SW-170284 IOS Press Editorial Weaving a Web of linked resources Fabien Gandon a,*, Marta Sabou b and Harald Sack c a Wimmics, Université Côte d’Azur, Inria, CNRS, I3S, Sophia Antipolis, France E-mail: [email protected] b CDL-Flex, Vienna University of Technology, Austria E-mail: [email protected] c FIZ Karlsruhe, Leibniz Institute for Information Infrastructure, KIT Karlsruhe, Germany E-mail: Harald.Sack@fiz-Karlsruhe.de Abstract. This editorial introduces the special issue based on the best papers from ESWC 2015. And since ESWC’15 marked 15 years of Semantic Web research, we extended this editorial to a position paper that reflects the path that we, as a community, traveled so far with the goal of transforming the Web of Pages to a Web of Resources. We discuss some of the key challenges, research topics and trends addressed by the Semantic Web community in its journey. We conclude that the symbiotic relation of our community with the Web requires a truly multidisciplinary research approach to support the Web’s diversity. Keywords: Semantic Web, trends, challenges 1. From a Web of pages to a Web of resources a first wave of deployment of the Semantic Web with the Linked Data principles and the Linked Open Data As we write this article Tim Berners-Lee just re- 5-Star rules [3] leading to the publication and growth ceived the Turing Award “for inventing the World of linked open datasets towards the Web of Data, as Wide Web, the first Web browser, and the fundamental depicted in Fig. 1 and Fig. 2 protocols and algorithms allowing the Web to scale” Twenty five years after its invention, the Web has [1]. But Tim not only invented the Web: he kept de- exceeded its initial status of a distributed document- fending it year after year and continuously works to centric space. Following its numerous evolutions, it lead it to its full potential. In particular, a bit less has become a virtual place where people and soft- than ten years after he submitted his proposal for an ware can co-operate within hybrid communities [10]. information management system in March 1989 [6], It supports a mixed society where humans and Web Tim wrote in September 1998 the Semantic Web Road robots interact in particular via shared metadata. Web map [2] to give a high-level plan of the architecture sites such as Wikipedia, DBpedia, and Wikidata are of the Semantic Web and as a continuation to his the most prominent examples of this space, where soft- wish in 1994 to provide on the Web “more machine- ware (Web robots) and humans interact in hybrid com- oriented semantic information, allowing more sophis- munities on a worldwide scale. ticated processing” [4]. This vision has been made vis- One of the major evolutions of the Web was the ad- ible to a broad audience in 2001 with an article in the vent of the Web of Data based on Linked Data princi- Scientific American [5]. And again a few years later, ples. It transformed the document centered Web into a Tim was instrumental in pushing what can be seen as distributed database. Linked Data provides an open in- terface based on widely used W3C standards, such as *Corresponding author. E-mail: [email protected]. URIs (Uniform Resource Identifiers) as universal iden- 1570-0844/17/$35.00 © 2017 – IOS Press and the authors. All rights reserved 768 F. Gandon et al. / Weaving a Web of linked resources Fig. 1. Number of linked open datasets on the Web plotted from 2007 to 2017 with data from [13]and[16]. tifiers, HTTP (Hypertext Transfer Protocol) for web- rity, streaming, etc. In terms of data management, scal- based access, and RDF (Resource description Frame- ability of storage and efficiency of querying are ac- work) as common standard for data encoding. These tive research and development domains to improve pillars enable efficient identification, access, and inter- RDF store performances. In terms of data access, many linking of data on the Web. Since its start in 2007, the approaches now exist on a continuum from HTTP Web of Data has grown up to almost 10,000 interlinked gets, to, Linked Data Fragments, Linked Data Plat- datasets covering a broad range of topics, as e.g., bib- form REST approach, and SPARQL services, proto- liographical data, geographical data, lexicographical col and language. Moreover, to provide reliable, per- data, biomedical data, or social networking data with sistent, and trustworthy Linked Data services, topics DBpedia, the Linked Data version of the popular on- such as access control, version management, long term line encyclopedia Wikipedia, as its referential central preservation are of utmost importance. But again ef- hub (cf. Fig. 1,Fig.2)[12]. ficiency, federation and hybridization remain hot re- search questions. 2. This is for everything 2.2. Formal knowledge and artificial intelligence During his participation in the London 2012 Sum- On top of these core topics of data management mer Olympics opening ceremony, Tim Berners-Lee and access, the Semantic Web community has always tweeted “This is for everyone” as a statement about the been interested in providing intelligent processing of Web. With its fundamental idea of using URIs to lit- the linked data of the Web, starting with reasoning. erally identify and henceforth describe “every thing” This remains a challenging and important topic with around us, the Web is now used in every human ac- hard problems in scaling, approximating and distribut- tivity. As a result many challenges have emerged from ing reasoning. In addition to classical logical deriva- different visions of the Semantic Web and from its dif- tion, many other artificially intelligent behaviours are ferent contexts of use and the constraints they bring studied in the community including machine learning with them. and data mining, induction of knowledge, deontic rea- soning on data licences, etc. In particular, hybrid ap- 2.1. From V to S in data management proaches investigating whether and how techniques of description logic and reasoning can be combined with The so called “Vs” of big data (velocity, variety, statistical machine learning are in the focus of current volume, veracity) translate to many “S” of Seman- research with the promise to further improve artificial tic Web: scalability, storage, search, semantics, secu- intelligence beyond the current state-of-the-art. F. Gandon et al. / Weaving a Web of linked resources 769 Fig. 2. The Linked Open Data Cloud diagram shows major datasets published in Linked Data format as of 2017-02-20 [16]. 2.3. Heterogeneity of graph types and life cycles data in a smart city), etc. And each type of graph of the Web is not an isolated island. Graphs interact with The initial graph of linked pages of the Web has each other: the networks of communities influence the been extended by a growing number of other graphs message flows, their subjects and types, the semantic including: sociograms capturing social network struc- links between terms interact with the links between tures, workflows specifying decision paths to be fol- sites and vice versa, the small changing graphs of sen- lowed, browsing logs capturing trails of navigation, au- sors are joined to the large stable geographical graphs tomata of service compositions specifying distributed that position them, etc. Not only do we need meth- processing, linked open data from distant datasets, etc. ods to represent and analyse each kind of graph, we Moreover, these graphs are distributed over many dif- also require the means to combine them and to perform ferent sources with very different characteristics. Some multi-criteria analyses on their combinations. sub-graphs are public (e.g. DBpedia), while others are private (e.g. semantic intrawebs). Some sub-graphs are 2.4. A truly open-world assumption small and local (e.g., a user’s profile on a device), and some are huge and hosted on clusters (e.g., Wikipedia). One of the major changes when trying to port Some are largely stable (e.g., a thesaurus for Latin), database and knowledge base approaches to the Web some change several times per second (e.g., sensor is the open world assumption (OWA) principle that un- 770 F. Gandon et al. / Weaving a Web of linked resources derlies Semantic Web technologies. Many existing re- cepted. With the advent of Linked Data technologies, sults from more established research domains, such as our community increasingly addressed large-scale databases, knowledge based systems or model-based data integration problems with enterprises knowledge engineering, have to be revisited to account for this graphs. Recent years have seen the uptake of Seman- open-world assumption. But in a broader sense, the tic Web technologies in application domains that span open world of linked data on the Web also adds addi- the borders of the digital and physical world. As a re- tional challenges to address uncertainty, data quality, sult we explored the use of our technologies as integral data and processing traceability in order to be able to part of cyber-physical systems such as adaptive traffic provide reasons for the users to trust the systems and control systems in smart cities [8] or flexible assembly their results. lines in smart factories [7]. 2.5. Human–machine partnership 3. Leading the Semantic Web to its full potential This expanding Web of data, together with the schemas, ontologies and vocabularies used to structure 3.1. Dynamics of research topics in Semantic Web and link it, form a formal Semantic Web with which we have to design new interaction means to support The previous topics are only a taste of the many im- the next generation of Web applications.

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