SPARQL with Property Paths

Kostylev, Egor V.; Reutter, Juan L.; Romero, Miguel; Vrgoč, Domagoj

doi:10.1007/978-3-319-25007-6_1

Cited by 62 publications

(41 citation statements)

References 21 publications

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“…Data value tests in SPARQL are allowed using the FILTER operator, which enables one to test for data (in)equality in a set of CRPQ outputs. Determining the connection between SPARQL queries and graph languages is an important task and, as witnessed by the abundance of the literature on the problem [Libkin et al 2013b;Reutter et al 2015;Kostylev et al 2015b], one that is not solved easily. There are several challenges that we are facing.…”

Section: Future Workmentioning

confidence: 99%

“…To start with, RDF data is in several aspects different from graph databases, and thus, straightforward translations between the two settings are not always possible [Libkin et al 2013b]. Furthermore, property paths are not precisely equivalent to RPQs since they operate over an infinite alphabet of IRIs [Kostylev et al 2015b]. In addition, many graph constructions are not available in SPARQL due to the lack of a more general transitive closure operator.…”

Section: Future Workmentioning

confidence: 99%

See 1 more Smart Citation

Querying Graphs with Data

Libkin

Martens

Vrgoč³

2016

J. ACM

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Graph databases have received much attention as of late due to numerous applications in which data is naturally viewed as a graph; these include social networks, RDF and the Semantic Web, biological databases, and many others. There are many proposals for query languages for graph databases that mainly fall into two categories. One views graphs as a particular kind of relational data and uses traditional relational mechanisms for querying. The other concentrates on querying the topology of the graph. These approaches, however, lack the ability to combine data and topology, which would allow queries asking how data changes along paths and patterns enveloping it.In this article, we present a comprehensive study of languages that enable such combination of data and topology querying. These languages come in two flavors. The first follows the standard approach of path queries, which specify how labels of edges change along a path, but now we extend them with ways of specifying how both labels and data change. From the complexity point of view, the right type of formalisms are subclasses of register automata. These, however, are not well suited for querying. To overcome this, we develop several types of extended regular expressions to specify paths with data and study their querying power and complexity. The second approach adopts the popular XML language XPath and extends it from XML documents to graphs. Depending on the exact set of allowed features, we have a family of languages, and our study shows that it includes efficient and highly expressive formalisms for querying both the structure of the data and the data itself.

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Section: Future Workmentioning

confidence: 99%

Section: Future Workmentioning

confidence: 99%

Querying Graphs with Data

Libkin

Martens

Vrgoč³

2016

J. ACM

Self Cite

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“…There also already exists a proposal to extend the expressive power of PPs [11]. Other strands of research focus on studying properties of PPs such as containment [25] or supporting recursion in SPARQL [32]. However, the main assumption of all these navigational extensions of SPARQL is to work on a single, centralized RDF graph.…”

Section: Related Workmentioning

confidence: 99%

SPARQL with property paths on the Web

Hartig

Pirrò

2017

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Abstract. Linked Data on the Web represents an immense source of knowledge suitable to be automatically processed and queried. In this respect, there are different approaches for Linked Data querying that differ on the degree of centralization adopted. On one hand, the SPARQL query language, originally defined for querying single datasets, has been enhanced with features to query federations of datasets; however, this attempt is not sufficient to cope with the distributed nature of data sources available as Linked Data. On the other hand, extensions or variations of SPARQL aim to find trade-offs between centralized and fully distributed querying. The idea is to partially move the computational load from the servers to the clients. Despite the variety and the relative merits of these approaches, as of today, there is no standard language for querying Linked Data on the Web. A specific requirement for such a language to capture the distributed, graph-like nature of Linked Data sources on the Web is a support of graph navigation. Recently, SPARQL has been extended with a navigational feature called property paths (PPs). However, the semantics of SPARQL restricts the scope of navigation via PPs to single RDF graphs. This restriction limits the applicability of PPs for querying distributed Linked Data sources on the Web. To fill this gap, in this paper we provide formal foundations for evaluating PPs on the Web, thus contributing to the definition of a query language for Linked Data. We first introduce a family of reachability-based query semantics for PPs that distinguish between navigation on the Web and navigation at the data level. Thereafter, we consider another, alternative query semantics that couples Web graph navigation and data level navigation; we call it context-based semantics. Given these semantics, we find that for some PP-based SPARQL queries a complete evaluation on the Web is not possible. To study this phenomenon we introduce a notion of Web-safeness of queries, and prove a decidable syntactic property that enables systems to identify queries that are Web-safe. In addition to establishing these formal foundations, we conducted an experimental comparison of the context-based semantics and a reachability-based semantics. Our experiments show that when evaluating a PP-based query under the context-based semantics one experiences a significantly smaller number of dereferencing operations, but the computed query result may contain less solutions.

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“…With the relation path extension definition in place, two interesting and basic analysis tasks that arise are the containment and equivalence problem, defined in databases query languages (see, e.g., [5] for details of a relational database context, and [3,21,10] for a graph database context). In a query scenario, if a relation path (i.e., 2RPQ) is equivalent to other with better computational properties (e.g., shorter, faster evaluation), then the initial relation path can be replaced for optimization purposes.…”

Section: Propositionmentioning

confidence: 99%

Identifying Equivalent Relation Paths in Knowledge Graphs

Mohamed

Muñoz

Nováček

et al. 2017

Lecture Notes in Computer Science

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Abstract. Relation paths are sequences of relations with inverse that allow for complete exploration of knowledge graphs in a two-way unconstrained manner. They are powerful enough to encode complex relationships between entities and are crucial in several contexts, such as knowledge base verification, rule mining, and link prediction. However, fundamental forms of reasoning such as containment and equivalence of relation paths have hitherto been ignored. Intuitively, two relation paths are equivalent if they share the same extension, i.e., set of source and target entity pairs. In this paper, we study the problem of containment as a means to find equivalent relation paths and show that it is very expensive in practice to enumerate paths between entities. We characterize the complexity of containment and equivalence of relation paths and propose a domain-independent and unsupervised method to obtain approximate equivalences ranked by a tri-criteria ranking function. We evaluate our algorithm using test cases over real-world data and show that we are able to find semantically meaningful equivalences efficiently.

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SPARQL with Property Paths

Cited by 62 publications

References 21 publications

Querying Graphs with Data

Querying Graphs with Data

SPARQL with property paths on the Web

Identifying Equivalent Relation Paths in Knowledge Graphs

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