The Shapes Constraint Language (SHACL) allows for formalizing constraints over RDF data graphs. A shape groups a set of constraints that may be fulfilled by nodes in the RDF graph. We investigate the problem of containment between SHACL shapes. One shape is contained in a second shape if every graph node meeting the constraints of the first shape also meets the constraints of the second. To decide shape containment, we map SHACL shape graphs into description logic axioms such that shape containment can be answered by description logic reasoning. We identify several, increasingly tight syntactic restrictions of SHACL for which this approach becomes sound and complete.

Graph data models are interesting in various domains, in part because of the intuitiveness and flexibility they offer compared to relational models. Specialized query languages, such as Cypher for property graphs or SPARQL for RDF, facilitate their use. In this paper, we present an empirical study on the usage of graph-based query languages in opensource Java projects on GitHub. We investigate the usage of SPARQL, Cypher, Gremlin and GraphQL in terms of popularity and their development over time. We select repositories based on dependencies related to these technologies and employ various popularity and source-code based filters and ranking features for a targeted selection of projects. For the concrete languages SPARQL and Cypher, we analyze the activity of repositories over time. For SPARQL, we investigate common application domains, query use and existence of ontological data modeling in applications that query for concrete instance data. Our results show, that the usage of graph query languages in open-source projects increased over the last years, with SPARQL and Cypher being by far the most popular. SPARQL projects are more active in terms of query related artifact changes and unique developers involved, but Cypher is catching up. Relatively few applications use SPARQL to query for concrete instance data: A majority of those applications employ multiple different ontologies,

Abstract. The Semantic Web is intended as a web of machine readable data where every data source can be the data provider for different kinds of applications. However, due to a lack of support it is still cumbersome to work with RDF data in modern, object-oriented programming languages, in particular if the data source is only available through a SPARQL endpoint without further documentation or published schema information. In this setting, it is desirable to have an integrated tool-chain that helps to understand the data source during development and supports the developer in the creation of persistent data objects. To tackle these issues, we introduce LITEQ, a paradigm for integrating RDF data sources into programming languages and strongly typing the data. Additionally, we report on two use cases and show that compared to existing approaches LITEQ performs competitively according to the Halstead metric.

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Abstract. Semantic data fuels many different applications, but is still lacking proper integration into programming languages. Untyped access is error-prone. Mapping approaches cannot fully capture the conceptualization of semantic data. In this paper, we present λDL, a typed λ-calculus with constructs for operating on semantic data. This is achieved by the integration of description logics into the λ-calculus for both typing and data access or querying. The language is centered around several key design principles, in particular: (1) the usage of semantic conceptualizations as types, (2) subtype inference for these types, and (3) type-checked query access to the data by both ensuring the satisfiability of queries as well as typing query results precisely. The paper motivates the use of a designated type system for semantic data and it provides the theoretic foundation for the integration of description logics as well as the core formal definition of λDL including a proof of type safety.