RDF triplestores and property graph databases are two approaches for data management which are based on modeling, storing and querying graph-like data. In spite of such common principle, they present special features that complicate the task of database interoperability. While there exist some methods to transform RDF graphs into property graphs, and vice versa, they lack compatibility and a solid formal foundation. This paper presents three direct mappings (schema-dependent and schema-independent) for transforming an RDF database into a property graph database, including data and schema. We show that two of the proposed mappings satisfy the properties of semantics preservation and information preservation. The existence of both mappings allows us to conclude that the property graph data model subsumes the information capacity of the RDF data model.

Resource Description Framework (RDF) can seen as a solution in today's landscape of knowledge representation research. An RDF language has symmetrical features because subjects and objects in triples can be interchangeably used. Moreover, the regularity and symmetry of the RDF language allow knowledge representation that is easily processed by machines, and because its structure is similar to natural languages, it is reasonably readable for people. RDF provides some useful features for generalized knowledge representation. Its distributed nature, due to its identifier grounding in IRIs, naturally scales to the size of the Web. However, its use is often hidden from view and is, therefore, one of the less well-known of the knowledge representation frameworks. Therefore, we summarise RDF v1.0 and v1.1 to broaden its audience within the knowledge representation community. This article reviews current approaches, tools, and applications for mapping from relational databases to RDF and from XML to RDF. We discuss RDF serializations, including formats with support for multiple graphs and we analyze RDF compression proposals. Finally, we present a summarized formal definition of RDF 1.1 that provides additional insights into the modeling of reification, blank nodes, and entailments. arXiv:2001.00432v1 [cs.DB] 2 Jan 2020 organizing information from different information sources. In particular, RDF can be seen as a general proposition language for the Web, which consolidates data from heterogeneous sources. It can provide interoperability between applications that exchange the data.Knowledge representation and data integration in the context of RDF is relevant for several reasons, including: promotes data exchange and interoperability; facilitates the reuse of available systems and tools; enables a fair comparison of Web systems by using benchmarks. In particular, this article shows how the RDF data model can be related to other models.The RDF language enables large portions of existing data to be processed and analyzed. This produces the need to develop the foundations of this language. This article addresses this challenge by developing an abstract model that is suitable to formalize and explain properties about the RDF data. We study the RDF data model, minimal and maximal representations, and show complexity bounds for the main problems. ContributionsWhen we examine the state of the RDF data model, we see evidence of trade-offs that occurred as various constituencies took part in the design process. Many of these trade-offs were never completely summarized in the RDF standards. Our article reviews a final state of RDF, and to identify areas where this data model is poorly understood. Our contributions are:1. to compare the RDF reification approaches, 2. to analyze the RDF 1.1 interpretations, entailments and their complexity, 3. to study the RDF blank nodes and their complexity, 4. to compare the various RDF data integration approaches, 5. to compare the RDF 1.1 serialization formats, including multiple graph syntaxes,...

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We report on a community effort between industry and academia to shape the future of property graph constraints. The standardization for a property graph query language is currently underway through the ISO Graph Query Language (GQL) project. Our position is that this project should pay close attention to schemas and constraints, and should focus next on key constraints.The main purposes of keys are enforcing data integrity and allowing the referencing and identifying of objects. Motivated by use cases from our industry partners, we argue that key constraints should be able to have different modes, which are combinations of basic restriction that require the key to be exclusive, mandatory, and singleton. Moreover, keys should be applicable to nodes, edges, and properties since these all can represent valid real-life entities. Our result is PG-Keys, a flexible and powerful framework for defining key constraints, which fulfills the above goals.PG-Keys is a design by the Linked Data Benchmark Council's Property Graph Schema Working Group, consisting of members from industry, academia, and ISO GQL standards group, intending to bring the best of all worlds to property graph practitioners. PG-Keys aims to guide the evolution of the standardization efforts towards making systems more useful, powerful, and expressive.

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