Ku¨nstl Intell (2016) 30:117–130 DOI 10.1007/s13218-016-0424-1
TECHNICAL CONTRIBUTION
15 Years of Semantic Web: An Incomplete Survey
1 2 Birte Glimm • Heiner Stuckenschmidt
Received: 7 November 2015 / Accepted: 5 January 2016 / Published online: 23 January 2016 Ó Springer-Verlag Berlin Heidelberg 2016
Abstract It has been 15 years since the first publications today’s Web: Uniform Resource Identifiers (URIs) for proposed the use of ontologies as a basis for defining assigning unique identifiers to resources, the HyperText information semantics on the Web starting what today is Markup Language (HTML) for specifying the formatting known as the Semantic Web Research Community. This of Web pages, and the Hypertext Transfer Protocol (HTTP) work undoubtedly had a significant influence on AI as a that allows for the retrieval of linked resources from across field and in particular the knowledge representation and the Web. Typically, the markup of standard Web pages Reasoning Community that quickly identified new chal- describes only the formatting and, hence, Web pages and lenges and opportunities in using Description Logics in a the navigation between them using hyperlinks is targeted practical setting. In this survey article, we will try to give towards human users (cf. Fig. 1). an overview of the developments the field has gone through In 2001, Tim Berners-Lee, James Hendler, and Ora in these 15 years. We will look at three different aspects: Lassila describe their vision for a Semantic Web [5]: the evolution of Semantic Web Language Standards, the The Semantic Web is not a separate Web but an evolution of central topics in the Semantic Web Commu- extension of the current one, in which information is nity and the evolution of the research methodology. given well-defined meaning, better enabling com- puters and people to work in cooperation.GG Keywords Semantic Web Á Ontologies Á Knowledge representation Á Survey The core idea to realizing the Semantic Web is to no longer leave the semantics of (hyper-)links implicitly given, but to assign names/types also to the link between a source and a 1 The Idea of the Semantic Web target resource (cf. Fig. 2). Each triple (source–link–target) can then be seen as an assertion that is presumed to be true In 1989, Tim Berners-Lee developed the vision for a World (but may be a false statement). This idea of specifying Wide Web in a document called ‘‘Information Manage- basic statements in the form of triples led to the develop- ment: A Proposal’’. Subsequently, he developed the three ment of the Resource Description Framework (RDF), fundamental technologies that remain the foundation of which is a data model for expressing descriptions of resources in the form of subject predicate object (short s po) triples. A set of such triples is interpreted as a graph & Birte Glimm where s and o are nodes and p specifies the label for an [email protected] edge from s to o. Starting from the source–link–target idea, Heiner Stuckenschmidt in RDF source and target can also be arbitrary resources [email protected] and not just Web pages and predicates are used to type the 1 Institute of Artificial Intelligence, University of Ulm, links. 89081 Ulm, Germany This basic idea of a data model for describing resources 2 Chair of Artificial Intelligence, University of Mannheim, and relations between them lead to the development of 68161 Mannheim, Germany several open standards to describe information over the last 123 118 Ku¨nstl Intell (2016) 30:117–130
Fig. 1 Plain links between HTML pages
... ...... A page.html#foo">link! target!
link
http://.../capitalOf http://.../berlin http://.../germany
Fig. 2 Typed links between resources
15 years. The standards are clearly defined, flexible, extensible, and allow for deriving knowledge from the given information. In this survey article, we next summa- rize the evolution of the core Semantic Web standards. Section 3 then describes the evolution of central topics in the Semantic Web community and Sect. 4 gives insights into the evolution of the research methodology. Finally, we conclude this survey in Sect. 5.
2 Semantic Web Standards
Standards are an important basis for the Semantic Web to achieve interoperability across different systems and tools. The important standards for the Semantic Web are devel- oped by the World Wide Web Consortium (W3C) whose Fig. 3 The Semantic Web architecture Copyright 2001 World Wide founder and director Tim Berners-Lee originally envi- Web Consortium (MIT, ERCIM, Keio, Beihang) http://www.w3.org/ Consortium/Legal/2015/doc-license sioned an architecture that is based on a layered stack of technologies (cf. Fig. 3) informally called the ‘‘layer cake’’. The standards for these technologies have under- recommendation ready in 2004 [27]. As outlined in the gone a significant development over the last decade that we introduction, RDF is a data model to express descriptions try to summarize in this section. of resources in the form of subject predicate object (sp o) triples, where a set of such triples is interpreted as a 2.1 The Resource Description Framework RDF (labeled) graph. Subjects are resources given in the form of URIs or blank nodes, which only serve as an object iden- The most basic ‘‘layer’’ that is specific for the Semantic tifier within the document without being globally valid. Web is the Resource Description Framework, for which the Predicates (also called properties) specify the relationship standardization process started in 1998 with the W3C between the subject and the object and are given in the
123 Ku¨nstl Intell (2016) 30:117–130 119 form of a URI. Objects are either URIs, blank nodes or @prefix dbp:
RDF 1.0 RDF 1.1 Prefix: :
3 http://www.loa.istc.cnr.it/old/DOLCE.html OWL 1 defined three increasingly-expressive sublan- guages: OWL Lite, OWL DL, and OWL Full. The worst-case :endurant rdfs:subClassOf [ rdf:type owl:Restriction ; complexity of reasoning in these sub-languages is ExpTime, owl:onProperty :participant-in ; NExpTime, and undecidable, respectively, which illustrates owl:onClass :perdurant that OWL Lite is not really (computationally) light-weight. ]. OWL 2 addresses this by defining three so-called profiles, which are tractable for certain reasoning tasks. Fig. 8 Translation of the existentially quantified subclass axioms to Turtle 1. OWL EL is based on the Description Logic EL?? [1], which captures, for example, many large bio-medical are used, Fig. 8 shows how the existentially quantified ontologies. The computation of the class hierarchy (all superclass of endurant is expressed in Turtle, where the subclass relationships) can be implemented efficiently opening square bracket introduces a blank node that is used with polynomial worst-case complexity. as the subject of the following triples. 2. OWL QL allows for answering conjunctive queries in 0 OWL reasoners consider the semantics of all special AC (data complexity, i.e., with respect to the size of the keywords (e.g., in subclass or disjointness statements) and assertions/facts), while being able to capture the main check whether an ontology is consistent (i.e., free of features necessary to express conceptual models such as logical contradictions), compute the subsumption hierar- UML class diagrams and ER diagrams. The profile is based chy (i.e., explicitly stated and logically following sub- on the Description Logic DL-Lite [12] and is designed so class relationships), or derive other logically entailed that data (assertions/facts) can be stored in a standard facts. Hence, reasoners help in finding modeling errors in relational database system and queries can be answered via an ontology that manifest themselves in unwanted sub- a simple rewriting mechanism, i.e., by rewriting the query sumptions or even an inconsistency. Furthermore, into an SQL query that captures the semantics of the debugging is facilitated since reasoners can compute schema axioms without any changes to the data. which axioms cause an (unwanted) entailment or an 3. OWL RL is defined such that reasoning can be imple- inconsistency. mented by standard rules engines (as RDF(S) reasoning) Apart from the new syntaxes and a clear definition of the in polynomial time. The design of OWL 2 RL was inspired two semantics, OWL 2 adds several other features [22]. by Description Logic Programs [23]andpD*[44]. Ontologies can, for example use an import directive to OWL EL and QL are defined for the Direct Semantics, include also axioms and facts from other ontologies. whereas OWL 2 RL works with both the Direct and the Regarding modeling constructs, some syntactic sugar (e.g., RDF-Based Semantics. The worst-case complexities of the negative property assertions) as well as new constructors different OWL sub-languages are illustrated in Fig. 9. for properties (e.g., for declaring a property as symmetric or disjoint to another one or for defining property chain 2.3 The Query Language SPARQL inclusions) and classes (e.g., qualified cardinality restric- tions to require a minimal, maximal or exact number of SPARQL stands for SPARQL Protocol And RDF Query instances of a given class to which an individual is related Language and is a W3C specification since 2008 with an via a given property) have been added. Furthermore, the extension to SPARQL 1.1 in 2013. The initial specification datatype capabilities have been significantly extended by consists of three parts: the query language [38], the XML allowing for custom datarange definitions based on existing result format [3], and the query protocol for the transmis- datatypes using factes [7] and logical constructors (con- sion of query and result [14]. Version 1.1 extends the query junction, disjunction, negation). The following two axioms language and introduces several new features, which we try in Manchester syntax illustrate these features by defining a to summarize in this section. xsd:integer custom datatype based on (abbreviated to As a simple example, consider the following SPARQL integer in the Manchester syntax) that is then used query, which is to be evaluated over the DBpedia data from together with another custom data range in defining the Fig. 4. class NonAdult:
@PREFIX dbo:
dbp:population OWLWL 1 Full / OWL 2 RDRDF-Based Semantics undecidable We also select cities that use instead of dbo:populationTotal, where DISTINCT eliminates possible duplicates and the filter eliminates 2NExpTime- OWOWLWL 2 DiDirectectt Semantics results where the population is smaller than 10;000. The complete ORDER BY keyword is a so-called solution modifier, which requires the results to be returned ordered in ascending NExpTime- OWOWLWL 1 DL (default) order by the population. Apart from SELECT complete queries, SPARQL also supports other kinds of queries, e.g., query results can be returned in the form of an RDF graph ExpTime- OWL 1 Lite using the CONSTRUCT keyword followed by a pattern that complete is instantiated with the results. In order to formally describe the semantics of queries, the SPARQL Query specification PTime- OWL 2 RL OWL 2 EL complete describes the translation to and evaluation of algebra objects. SPARQL 1.1 adds not only new features to the query In AC0 OWL 2 QL language, but also several new specifications. We refer to the overview [45] for a detailed description and only Fig. 9 Worst-case complexities of the different OWL sub-languages summarize the changes here. Regarding the query lan- guage, important new features are declaration of prefixes. After the SELECT keyword, we list • expressions in the select or the where clause to compute the variables, prefixed with ? or $, that are to be selected values, e.g., (?price * ?amount) AS ?sum), (* selects all variables). People familiar with SQL might • aggregates, e.g., to count the number of results or to miss the FROM clause, which can be omitted in SPARQL compute average values since queries are assumed to be evaluated over an RDF • property paths that allow for regular expressions over data set (cf. Sect. 2.1) and queries without a from clause properties, e.g., we can query for ancestors with the are evaluated over the default graph of the data set. The property path expression FROM NAMED keyword can be used to evaluate queries ?ancestorðex:motherOf j ex:fatherOfÞþ\#me [ over a named graph of the data set. After the WHERE keyword, the query pattern is given, enclosed in curly by following a path of arbitrary length (þ) over brackets. The simplest query pattern, called a basic graph ex:motherOf or (|) ex:fatherOf labeled edges, pattern (BGP), consists of triples where subject, predicate, • negated patterns (MINUS or FILTER NOT EXISTS). and object can be replaced by variables. Answers to such a query are obtained by mapping the BGP onto the queried SPARQL 1.1 further adds a range of new features in graph with variables acting as wild cards. The so obtained new specifications: SPARQL 1.1 Update [20] extends the bindings might be further processed, e.g., by projecting out query language to allow for the manipulation of graphs or variables as required by the select clause. graph content. SPARQL 1.1 Entailment Regimes [21] More complex BGPs can be formed by using the key- redefine the evaluation of BGPs such that entailment word UNION, which allows for specifying alternative parts relations are used instead of subgraph matching to define for a pattern, OPTIONAL to enrich results with optional the results. Supported entailment relations are RDF, RDFS, mappings, and FILTER followed by a filter expression that D (RDFS with extended datatype support), OWL Direct evaluate to truth values (and possibly errors). Many filter and RDF-Based Semantics, and RDF extended with RIF functions are partly taken from the XQuery/XPath-standard rules (cf. Sect. 2.4). SPARQL endpoints that support for XML [29]. Assume, for example, the modification of entailment consider the special semantics of the supported the query above: vocabularies. For example, if the endpoint employs RDFS entailment and one queries for instances of a class, then also asserted instances of subclasses are in the result. @PREFIX dbp:
123 Ku¨nstl Intell (2016) 30:117–130 123 different SPARQL endpoints can be executed, which Prefix(rdfs
Fig. 11 Fraction of papers at the International Semantic Web Conference by topic
Focussing on the ‘Design and Modelling’ type papers, and basic ideas have to be tested in prototypical form. Only we investigated the importance and quality of experi- later, when the field is more established and the problems mental work used to support the claims about the system are better understood, systematic experiments become the or model proposed in the paper. As proposed by Tichy standard way of validation. et al. [46], we used the number of pages devoted to the Further, we annotate all papers of Category 2 with the description of the experiments as an indicator of the following information about the nature of the experiments. importance of the experimental work. In particular, we Standard used for Comparison Does the paper report analyze how the papers distribute across the subcate- about different settings or the system or method? Are gories defined by the fraction of the pages devoted to the results compared against existing baselines? Are results description of experimental work (0 %, (0–10 %], compared against the results of other systems? The latter (20–50 %], [50 %) and look at the development of includes both indirect comparisons against results experimental work over time by plotting the distribution reported in other papers and direct comparisons obtained of papers across all categories over the past eleven years. by executing the other system as part of the experiments. We also look at the average number of pages devoted to Datasets used Has one dataset been used or have several experimental work in the different years and compute the datasets been used within the experiments? Has the correlation between year of publication and number of dataset been self-created by the authors for the purpose pages. of conducting the experiments or is it externally Figure 12 shows that an increase in the importance can provided? be observed. It shows a standard box-plot for the relative number of experiment pages for Category 2 (Design and We use this information as an indication of the quality Modeling) papers. We identified a trend of growing of the experimental design, assuming that an ideal exper- importance of experiments over time. With the exception imental design will compare a proposed system against of 2010, the median is constantly rising up to 25 % in other leading systems or at least sensible baselines using 2012. Measuring this trend in figures, the Spearman Cor- several datasets with different characteristics. One can relation Coefficient is statistically significant argue about whether externally provided datasets should be (rSð402Þ¼:49; p\:000). This means that the importance preferred over self-created ones, in many cases externally of experimental work was rather low in the early years of provided datasets are publicly accessible benchmarks that the ISWC conference. This is not uncommon for new fields support the comparison with other systems, which we of research, as first, the principled ideas have to be laid out consider desirable.
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Fig. 12 Box-plot showing the relative number of pages of Category 2 (Design and Modeling) papers by year of publication. The median starting at 0 % in 2002 increases constantly (with the exception of 2010) over time, reaching its top of 24 % in 2012. The second/third quartile, denoted by the box, varies, but is since 2009 clearly above zero. Outliers are displayed as circles/ stars (taken from [43])
The variables SEVERAL and OTHER can be interpreted as attributed to experimental work. Another factor might be indicators for the universal validity of the reported results. the general development of the community. What has been The variables BASEDIFF and SYS indicate whether the a novel area of research ten years ago, might have become authors informed the reader on the performance (e.g., an established research area associated with well-defined runtimes), quality (e.g., precision), or usability compared to problems, commonly accepted formats, well-known data- alternative approaches. Without such a comparison, it is sets and accepted benchmarks. Obviously, both factors go hardly possible to draw any conclusions related to the hand in hand, resulting in the positive trend that we improvements made. reported in the evaluation. The results of our analysis are shown in Fig. 13, where we depicted the counts for all four variables with respect to Category 2 papers. Figure 13 reveals a clear trend. The 5 Conclusions quality of experimental work is increasing over time with respect to each variable. In 2003 only a minor share of all Over the past 15 years, the Semantic Web has established papers had a positive characteristic in one of the four itself as a research area in its own rights. Based on the variables, while in 2012 more than 50 % of all papers had a development of agreed standards for representing and positive characteristic in three of four variables. However, accessing data on the web, the filed has generated a unique only 33 % of all papers in 2012 compared their results set of methods that address the specific needs of semantic against other systems (SYS). While this is an improvement information processing in an open and distributed envi- compared to the previous years, there are still many papers ronment. While most methods that are currently investi- that do not compare their results against other systems. We gated have their origin in other more established research computed also the correlation between the year of publi- fields, in particular knowledge representation, database cation and the four quality measures using Spearman’s systems and knowledge discovery, the field meanwhile has rank correlation coefficient. We find that all variables show made unique contributions to the state of the art and also positive and statistically significant correlations with the starts to have impact on the research topics in these areas. year of publication (rS between .36 and .46, p :000). The Semantic Web as a research field is still characterized Our observations can be explained by two factors. One by a mix of technologies and methods from different fields factor might be an increasing awareness of the importance and by the application rather than by a unique set of
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Fig. 13 Development of relative share of Category 2 (Design and datasets (OTHER) to increase the most. Nevertheless, even in 2012 only Modeling) papers complying to different evaluation quality indicators about on third of all papers compare themselves to other existing over time. While all indicators start at a low level of B11 % in 2003 systems (SYS) and rise with the years, we found the usage of externally provided
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OWL 2 web ontology language—direct semantics (second edition). In: W3C Birte Glimm is a junior pro- recommendation. W3C, 11 Dec 2012. http://www.w3.org/TR/ fessor at the University of Ulm 2012/REC-owl2-direct-semantics-20121211/ within the Institute of Artificial 33. Motik B, Patel-Schneider PF, Parsia B. OWL 2 web ontology Intelligence. Before that, she got language: structural specification and functional-style syntax her PhD from the University of (second edition). In: W3C recommendation. W3C, 11 Dec 2012. Manchester in 2007 and worked http://www.w3.org/TR/2012/REC-owl2-syntax-20121211/ as research assistant at the 34. Ogbuji C. SPARQL 1.1 graph store HTTP protocol. In: W3C University of Oxford until 2011. recommendation. W3C, 21 Mar 2013. http://www.w3.org/TR/ Her research interests include 2013/REC-sparql11-http-rdf-update-20130321/ knowledge representation and 35. Patel-Schneider PF, Motik B. 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Heiner Stuckenschmidt is a semantic matching and combining logical and probabilistic reasoning. full professor at the University More information can be found at http://dws.informatik.uni-man of Mannheim within the Data nheim.de. and Web Science Group. He received his PhD from the Free University of Amsterdam, where he conducted some of the first steps in using The Web Ontology Language for infor- mation integration on the Web. Since moving back to Germany in 2005 he leads the AI group at the University of Mannheim. His group is conducting theo- retical and applied research on different aspects of semantic web technologies with a focus on
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