Implementing flexible operators for regular path queries

Given the heterogeneity of complex graph data on the web, such as RDF linked data,a user wishing to query such data may lack full knowledge of its structure and irregularities. Hence, providing users with flexible querying capabilities can be beneficial. The query language we adopt comprises conjunctions of regular path queries, thus including extensions proposed for SPARQL 1.1 to allow for querying paths using regular expressions. To this language we add two operators: APPROX, supporting standard notions of approximation based on edit distance, and RELAX, which performs query relaxation based on RDFS inference rules. We describe our techniques for implementing the extended language and present a performance study undertaken on two real-world data sets. Our baseline implementation performs competitively with other automaton-based approaches, and we demonstrate empirically how various optimisations can decrease execution times of queries containing APPROX and RELAX, sometimes by orders of magnitude

Updating Graph Databases with Cypher

International audienc

A novel class of CoA-transferase involved in short-chain fatty acid metabolism in butyrate-producing human colonic bacteria

Peer reviewedPublisher PD

Graph Pattern Matching in GQL and SQL/PGQ

As graph databases become widespread, JTC1 -- the committee in joint charge of information technology standards for the International Organization for Standardization (ISO), and International Electrotechnical Commission (IEC) -- has approved a project to create GQL, a standard property graph query language. This complements a project to extend SQL with a new part, SQL/PGQ, which specifies how to define graph views over an SQL tabular schema, and to run read-only queries against them. Both projects have been assigned to the ISO/IEC JTC1 SC32 working group for Database Languages, WG3, which continues to maintain and enhance SQL as a whole. This common responsibility helps enforce a policy that the identical core of both PGQ and GQL is a graph pattern matching sub-language, here termed GPML. The WG3 design process is also analyzed by an academic working group, part of the Linked Data Benchmark Council (LDBC), whose task is to produce a formal semantics of these graph data languages, which complements their standard specifications. This paper, written by members of WG3 and LDBC, presents the key elements of the GPML of SQL/PGQ and GQL in advance of the publication of these new standards

Approximation and relaxation of semantic web path queries

Given the heterogeneity of complex graph data on the web, such as RDF linked data, it is likely that a user wishing to query such data will lack full knowledge of the structure of the data and of its irregularities. Hence, providing flexible querying capabilities that assist users in formulating their information seeking requirements is highly desirable. In this paper we undertake a detailed theoretical investigation of query approximation, query relaxation, and their combination, for this purpose. The query language we adopt comprises conjunctions of regular path queries, thus encompassing recent extensions to SPARQL to allow for querying paths in graphs using regular expressions (SPARQL 1.1). To this language we add standard notions of query approximation based on edit distance, as well as query relaxation based on RDFS inference rules. We show how both of these notions can be integrated into a single theoretical framework and we provide incremental evaluation algorithms that run in polynomial time in the size of the query and the data, returning answers in ranked order of their `distance' from the original query. We also combine for the first time these two disparate notions into a single `flex' operation that simultaneously applies both approximation and relaxation to a query conjunct, providing even greater flexibility for users, but still retaining polynomial time evaluation complexity and the ability to return query answers in ranked order

The Future is Big Graphs! A Community View on Graph Processing Systems

Graphs are by nature unifying abstractions that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users and consumers of graph instances and graph workloads understand these abstractions, future problems will require new abstractions and systems. What needs to happen in the next decade for big graph processing to continue to succeed?Comment: 12 pages, 3 figures, collaboration between the large-scale systems and data management communities, work started at the Dagstuhl Seminar 19491 on Big Graph Processing Systems, to be published in the Communications of the AC

Flexible querying of lifelong learner metadata

We propose combining query approximation and query relaxation techniques in order to support flexible querying of heterogeneous data arising from lifelong learners' educational and work experiences. A key aim of such querying facilities is to allow learners to identify possible choices for their future learning and professional development from what others have done. With our approach, query results can be computed incrementally, in polynomial time, and returned in order of increasing "distance" from the user's original query

Minimal module extraction from DL-Lite ontologies using QBF solvers

We present a formal framework for (minimal) module extraction based on an abstract notion of inseparability w.r.t. a signature between ontologies. Two instances of this framework are discussed in detail for DL-Lite ontologies: concept inseparability, when ontologies imply the same complex concept inclusions over the signature, and query inseparability, when they give the same answers to existential queries for any instance data over the signature. We demonstrate that different types of corresponding minimal modules for these inseparability relations can be automatically extracted from large-scale DL-Lite ontologies by composing the tractable syntactic locality-based module extraction algorithm with intractable extraction algorithms using the multi-engine QBF solver AQME. The extracted minimal modules are compared with those obtained using non-logic-based approaches