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BackgroundPandemics, even more than other medical problems, require swift integration of knowledge. When caused by a new virus, understanding the underlying biology may help finding solutions. In a setting where there are a large number of loosely related projects and initiatives, we need common ground, also known as a “commons.” Wikidata, a public knowledge graph aligned with Wikipedia, is such a commons and uses unique identifiers to link knowledge in other knowledge bases. However, Wikidata may not always have the right schema for the urgent questions. In this paper, we address this problem by showing how a data schema required for the integration can be modeled with entity schemas represented by Shape Expressions.ResultsAs a telling example, we describe the process of aligning resources on the genomes and proteomes of the SARS-CoV-2 virus and related viruses as well as how Shape Expressions can be defined for Wikidata to model the knowledge, helping others studying the SARS-CoV-2 pandemic. How this model can be used to make data between various resources interoperable is demonstrated by integrating data from NCBI (National Center for Biotechnology Information) Taxonomy, NCBI Genes, UniProt, and WikiPathways. Based on that model, a set of automated applications or bots were written for regular updates of these sources in Wikidata and added to a platform for automatically running these updates.ConclusionsAlthough this workflow is developed and applied in the context of the COVID-19 pandemic, to demonstrate its broader applicability it was also applied to other human coronaviruses (MERS, SARS, human coronavirus NL63, human coronavirus 229E, human coronavirus HKU1, human coronavirus OC4).

Knowledge Graphs (KGs) are widely used to represent heterogeneous domain knowledge on the Web and within organizations. Various methods exist to manage KGs and ensure the quality of their data. Among these, the Shapes Constraint Language (SHACL) and the Shapes Expression Language (ShEx) are the two state-of-the-art languages to define validating shapes for KGs. Since the usage of these constraint languages has recently increased, new needs arose. One such need is to enable the efficient generation of these shapes. Yet, since these languages are relatively new, we witness a lack of understanding of how they are effectively employed for existing KGs. Therefore, in this work, we answer How validating shapes are being generated and adopted? Our contribution is threefold. First, we conducted a community survey to analyze the needs of users (both from industry and academia) generating validating shapes. Then, we cross-referenced our results with an extensive survey of the existing tools and their features. Finally, we investigated how existing automatic shape extraction approaches work in practice on real, large KGs. Our analysis shows the need for developing semi-automatic methods that can help users generate shapes from large KGs.

Tutorial given at the Second Indo-American Conference on Knowledge Graphs and Semantic Web: KGSWC-2021 https://kgswc.org/winter-school-virtual/

International audience; We present ShERML, a tool for facilitating the data exchange from relational data to RDF. The main feature of the tool is a graphical user interface for designing a relational-to-RDF mapping by drawing arrows between schematic representations of the relational schema on the one hand, and a SHACL or ShEx schema on the other hand. The mapping thus constructed can be used directly by the tool for materializing the RDF graph, or be exported as an R2RML mapping.

We present a method for the construction of SHACL or ShEx constraints for an existing RDF dataset. It has two components that are used conjointly: an algorithm for automatic schema construction, and an interactive workflow for editing the schema. The schema construction algorithm takes as input sets of sample nodes and constructs a shape constraint for every sample set. It can be parametrized by a schema pattern that defines structural requirements for the schema to be constructed. Schema patterns are also used to feed the algorithm with relevant information about the dataset coming from a domain expert or from some ontology. The interactive workflow provides useful information about the dataset, shows validation results w.r.t. the schema under construction, and offers schema editing operations that combined with the schema construction algorithm allow to build a complex ShEx or SHACL schema.

International audience; We study the problem of containment of shape expression schemas (ShEx) for RDF graphs. We identify a subclass of ShEx that has a natural graphical representation in the form of shape graphs and whose semantics is captured with a tractable notion of embedding of an RDF graph in a shape graph. When applied to pairs of shape graphs, an embedding is a sufficient condition for containment, and for a practical subclass of deterministic shape graphs, it is also a necessary one, thus yielding a subclass with tractable containment. Containment for general shape graphs is EXP-complete. Finally , we show that containment for arbitrary ShEx is decid-able. CCS CONCEPTS • Information systems → Graph-based database models ; Resource Description Framework (RDF); • Theory of computation → Database theory; Database interoper-ability.

International audience; We present Shape Designer, a graphical tool for building SHACL or ShEx constraints for an existing RDF dataset. Shape Designer allows to automatically extract complex constraints that are satisfied by the data. Its integrated shape editor and validator allow expert users to combine and modify these constraints in order to build an arbitrarily complex ShEx or SHACL schema.

A poster prepared for the international Semantic Web Research Summer School (ISWS) 2018. The big white rectangle in the middle was filled with physical puzzle pieces, see https://sven-lieber.org/en/2018/07/02/isws-2018-poster/

International audience; ShEx (Shape Expressions) is a language for expressing constraints on RDF graphs. In this work we optimize the evaluation of conjunctive SPARQL queries, on RDF graphs, by taking advantage of ShEx constraints. Our optimization is based on computing and assigning ranks to query triple patterns , dictating their order of execution. We first define a set of well formed ShEx schemas, that possess interesting characteristics for SPARQL query optimization. We then define our optimization method by exploiting information extracted from a ShEx schema. We finally report on evaluation results performed showing the advantages of applying our optimization on the top of an existing state-of-the-art query evaluation system.

Slides for a presentation to the Force2017 Software Citation Implementation Working Group describing software and file format data in Wikidata and data validation using ShEx.

International audience; ShEx (Shape Expressions) is a language for expressing constraints on RDF graphs. In this work, we optimise the evaluation of conjunctive SPARQL queries, on RDF graphs, by taking advantage of ShEx constraints. Our optimisation is based on computing and assigning ranks to query triple patterns, dictating their order of execution. We first define a set of well-formed ShEx schemas, that possess interesting characteristics for SPARQL query optimisation. We then define our optimisation method by exploiting information extracted from a ShEx schema. We finally report on evaluation results performed showing the advantages of applying our optimisation on the top of an existing state-of-the-art query evaluation system.

Data structured in the Resource Description Framework (RDF) are increasingly available in large volumes. This leads to a major need and research interest in novel methods for query analysis and compilation for making the most of RDF data extraction. SPARQL is the widely used and well supported standard query language for RDF data. In parallel to query language evolutions, schema languages for expressing constraints on RDF datasets also evolve. Shape Expressions (ShEx) are increasingly used to validate RDF data, and to communicate expected graph patterns. Schemas in general are important for static analysis tasks such as query optimisation and containment. Our purpose is to investigate the means and methodologies for SPARQL query static analysis and optimisation in the presence of ShEx schema constraints.Our contribution is mainly divided into two parts. In the first part we consider the problem of SPARQL query containment in the presence of ShEx constraints. We propose a sound and complete procedure for the problem of containment with ShEx, considering several SPARQL fragments. Particularly our procedure considers OPTIONAL query patterns, that turns out to be an important feature to be studied with schemas. We provide complexity bounds for the containment problem with respect to the language fragments considered. We also propose alternative method for SPARQL query containment with ShEx by reduction into First Order Logic satisfiability, which allows for considering SPARQL fragment extension in comparison to the first method. This is the first work addressing SPARQL query containment in the presence of ShEx constraints.In the second part of our contribution we propose an analysis method to optimise the evaluation of conjunctive SPARQL queries, on RDF graphs, by taking advantage of ShEx constraints. The optimisation is based on computing and assigning ranks to query triple patterns, dictating their order of execution. The presence of intermediate joins between the query triple patterns is the reason why ordering is important in increasing efficiency. We define a set of well-formed ShEx schemas, that possess interesting characteristics for SPARQL query optimisation. We then develop our optimisation method by exploiting information extracted from a ShEx schema. We finally report on evaluation results performed showing the advantages of applying our optimisation on the top of an existing state-of-the-art query evaluation system.; La disponibilité de gros volumes de données structurées selon le modèle Resource Description Framework (RDF) est en constante augmentation. Cette situation implique un intérêt scientifique et un besoin important de rechercher de nouvelles méthodes d’analyse et de compilation de requêtes pour tirer le meilleur parti de l’extraction de données RDF. SPARQL est le plus utilisé et le mieux supporté des langages de requêtes sur des données RDF. En parallèle des langages de requêtes, les langages de définition de schéma d’expression de contraintes sur des jeux de données RDF ont également évolués. Les Shape Expressions (ShEx) sont de plus en plus utilisées pour valider des données RDF et pour indiquer les motifs de graphes attendus. Les schémas sont importants pour les tâches d’analyse statique telles que l’optimisation ou l’injection de requêtes. Notre intention est d’examiner les moyens et méthodologies d’analyse statique et d’optimisation de requêtes associés à des contraintes de schéma.Notre contribution se divise en deux grandes parties. Dans la première, nous considérons le problème de l’injection de requêtes SPARQL en présence de contraintes ShEx. Nous proposons une procédure rigoureuse et complète pour le problème de l’injection de requêtes avec ShEx, en prenant en charge plusieurs fragments de SPARQL. Plus particulièrement, notre procédure gère les patterns de requêtes OPTIONAL, qui s’avèrent former un important fonctionnalité à étudier avec les schémas. Nous fournissons ensuite les limites de complexité de notre problème en considération des fragments gérés. Nous proposons également une méthode alternative pour l’injection de requêtes SPARQL avec ShEx. Celle-ci réduit le problème à une satisfiabilité de Logique de Premier Ordre, qui permet de considérer une extension du fragment SPARQL traité par la première méthode. Il s’agit de la première étude traitant l’injection de requêtes SPARQL en présence de contraintes ShEx.Dans la seconde partie de nos contributions, nous proposons une méthode d’analyse pour optimiser l’évaluation de requêtes SPARQL groupées, sur des graphes RDF, en tirant avantage des contraintes ShEx. Notre optimisation s’appuie sur le calcul et l’assignation de rangs aux triple patterns d’une requête, permettant de déterminer leur ordre d’exécution. La présence de jointures intermédiaires entre ces patterns est la raison pour laquelle l’ordonnancement est important pour gagner en efficicacité. Nous définissons un ensemble de schémas ShEx bien- formulés, qui possède d’intéressantes caractéristiques pour l’optimisation de requêtes SPARQL. Nous développons ensuite notre méthode d’optimisation par l’exploitation d’informations extraites d’un schéma ShEx. Enfin, nous rendons compte des résultats des évaluations effectuées, montrant les avantages de l’application de notre optimisation face à l’état de l’art des systèmes d’évaluation de requêtes.

Data structured in the Resource Description Framework (RDF) are increasingly available in large volumes. This leads to a major need and research interest in novel methods for query analysis and compilation for making the most of RDF data extraction. SPARQL is the widely used and well supported standard query language for RDF data. In parallel to query language evolutions, schema languages for expressing constraints on RDF datasets also evolve. Shape Expressions (ShEx) are increasingly used to validate RDF data, and to communicate expected graph patterns. Schemas in general are important for static analysis tasks such as query optimisation and containment. Our purpose is to investigate the means and methodologies for SPARQL query static analysis and optimisation in the presence of ShEx schema constraints.Our contribution is mainly divided into two parts. In the first part we consider the problem of SPARQL query containment in the presence of ShEx constraints. We propose a sound and complete procedure for the problem of containment with ShEx, considering several SPARQL fragments. Particularly our procedure considers OPTIONAL query patterns, that turns out to be an important feature to be studied with schemas. We provide complexity bounds for the containment problem with respect to the language fragments considered. We also propose alternative method for SPARQL query containment with ShEx by reduction into First Order Logic satisfiability, which allows for considering SPARQL fragment extension in comparison to the first method. This is the first work addressing SPARQL query containment in the presence of ShEx constraints.In the second part of our contribution we propose an analysis method to optimise the evaluation of conjunctive SPARQL queries, on RDF graphs, by taking advantage of ShEx constraints. The optimisation is based on computing and assigning ranks to query triple patterns, dictating their order of execution. The presence of intermediate joins between the query triple patterns is the reason why ordering is important in increasing efficiency. We define a set of well-formed ShEx schemas, that possess interesting characteristics for SPARQL query optimisation. We then develop our optimisation method by exploiting information extracted from a ShEx schema. We finally report on evaluation results performed showing the advantages of applying our optimisation on the top of an existing state-of-the-art query evaluation system.; La disponibilité de gros volumes de données structurées selon le modèle Resource Description Framework (RDF) est en constante augmentation. Cette situation implique un intérêt scientifique et un besoin important de rechercher de nouvelles méthodes d’analyse et de compilation de requêtes pour tirer le meilleur parti de l’extraction de données RDF. SPARQL est le plus utilisé et le mieux supporté des langages de requêtes sur des données RDF. En parallèle des langages de requêtes, les langages de définition de schéma d’expression de contraintes sur des jeux de données RDF ont également évolués. Les Shape Expressions (ShEx) sont de plus en plus utilisées pour valider des données RDF et pour indiquer les motifs de graphes attendus. Les schémas sont importants pour les tâches d’analyse statique telles que l’optimisation ou l’injection de requêtes. Notre intention est d’examiner les moyens et méthodologies d’analyse statique et d’optimisation de requêtes associés à des contraintes de schéma.Notre contribution se divise en deux grandes parties. Dans la première, nous considérons le problème de l’injection de requêtes SPARQL en présence de contraintes ShEx. Nous proposons une procédure rigoureuse et complète pour le problème de l’injection de requêtes avec ShEx, en prenant en charge plusieurs fragments de SPARQL. Plus particulièrement, notre procédure gère les patterns de requêtes OPTIONAL, qui s’avèrent former un important fonctionnalité à étudier avec les schémas. Nous fournissons ensuite les limites de complexité de notre problème en considération des fragments gérés. Nous proposons également une méthode alternative pour l’injection de requêtes SPARQL avec ShEx. Celle-ci réduit le problème à une satisfiabilité de Logique de Premier Ordre, qui permet de considérer une extension du fragment SPARQL traité par la première méthode. Il s’agit de la première étude traitant l’injection de requêtes SPARQL en présence de contraintes ShEx.Dans la seconde partie de nos contributions, nous proposons une méthode d’analyse pour optimiser l’évaluation de requêtes SPARQL groupées, sur des graphes RDF, en tirant avantage des contraintes ShEx. Notre optimisation s’appuie sur le calcul et l’assignation de rangs aux triple patterns d’une requête, permettant de déterminer leur ordre d’exécution. La présence de jointures intermédiaires entre ces patterns est la raison pour laquelle l’ordonnancement est important pour gagner en efficicacité. Nous définissons un ensemble de schémas ShEx bien- formulés, qui possède d’intéressantes caractéristiques pour l’optimisation de requêtes SPARQL. Nous développons ensuite notre méthode d’optimisation par l’exploitation d’informations extraites d’un schéma ShEx. Enfin, nous rendons compte des résultats des évaluations effectuées, montrant les avantages de l’application de notre optimisation face à l’état de l’art des systèmes d’évaluation de requêtes.

A variety of embedded systems is used within the design and the construction of trucks within Scania. Because of their heterogeneity and complexity, such systems require the use of many software tools to support embedded systems development. These tools need to form a well-integrated and effective development environment, in order to ensure that product data is consistent and correct across the developing organisation. A prototype is under development which adapts a linked data approach for data integration, more specifically this prototype adapt the Open Services for Lifecycle Collaboration(OSLC) specification for data-integration. The prototype allows users, to design OSLC-interfaces between product management tools and OSLC-links between their data. The user is further allowed to apply constraints on the data conforming to the OSLC validation language Resource Shapes(ReSh). The problem lies in the prototype conforming only to the language of Resource Shapes whose constraints are often too coarse-grained for Scania’s needs, and that there exists no standardised language for the validation of linked data. Thus, for framing this study two research questions was formulated (1) How can a common graphical language be created for supporting all validation technologies of RDF-data? and (2) How can this graphical language support the automatic generation of RDF-graphs? A case study is conducted where the specific case consists of a software tool named SESAMM-tool at Scania. The case study included a constraint language comparison and a prototype extension. Furthermore, a design science research strategy is followed, where an effective artefact was searched for answering the stated research questions. Design science promotes an iterative process including implementation and evaluation. Data has been empirically collected in an iterative development process and evaluated using the methods of informed argument and controlled experiment, respectively, for the constraint language comparison and the extension of the prototype. Two constraint languages were investigated Shapes Constraint Language (SHACL) and Shapes Expression (ShEx). The result of the constraint language comparison concluded SHACL as the constraint language with a larger domain of constraints having finer-grained constraints also with the possibility of defining new constraints. This was based on that SHACL constraints was measured to cover 89.5% of ShEx constraints and 67.8% for the converse. The SHACL and ShEx coverage on ReSh property constraints was measured to 75% and 50%. SHACL was recommended and chosen for extending the prototype. On extending the prototype abstract super classes was introduced into the underlying data model. Constraint language classes were stated as subclasses. SHACL was additionally stated as such a subclass. This design offered an increased code reuse within the prototype but gave rise to issues relating to the plug-in technologies that the prototype is based upon. The current solution still has the issue that properties of one constraint language may be added to classes of another constraint language. En mängd olika inbyggda system används inom design och konstruktion av lastbilar inom Scania. På grund av deras heterogenitet och komplexitet kräver sådana system användningen av många mjukvaruverktyg för att stödja inbyggd systemutveckling. Dessa verktyg måste bilda en välintegrerad och effektiv utvecklingsmiljö för att säkerställa att produktdata är konsekventa och korrekta över utvecklingsorganisationen.En prototyp håller på att utvecklas som anpassar en länkad datainriktning för dataintegration, mer specifikt anpassar denna prototyp en dataintegration specifikation utvecklad av Open Services for Lifecycle Collaboration(OSLC). Prototypen tillåter användare att utforma OSLC-gränssnitt mellan produkthanteringsverktyg och OSLC-länkar mellan deras data. Användaren får vidare tillämpa begränsningar på de data som överensstämmer med OSLC-valideringsspråket Resource Shapes. Problemet ligger i prototypen som endast överensstämmer med Resource Shapes, vars begränsningar ofta är för grova för Scanias behov och att det inte finns något standardiserat språk för validering av länkad data. Således, för att utforma denna studie formulerades två forskningsfrågor (1) Hur kan ett gemensamt grafiskt språk skapas för att stödja alla valideringsteknologier av RDF-data? och (2) Hur kan detta grafiska språk stödja Automatisk generering av RDF-grafer? En fallstudie genomförs där det specifika fallet består av ett mjukvaruverktyg som heter SESAMM-tool hos Scania. Fallstudien innehöll en jämförelse av valideringsspråk och vidareutveckling av prototypen. Vidare följs Design Science som forskningsstrategi där en effektiv artefakt sökts för att svara på de angivna forskningsfrågorna. Design Science främjar en iterativ process inklusive genomförande och utvärdering. Data har empiriskt samlats på ett iterativt sätt och utvärderats med hjälp av utvärderingsmetoderna informerat argument och kontrollerat experiment, för valideringsspråkjämförelsen och vidareutvecklingen av prototypen. Två valideringsspråk undersöktes Shapes Constraint Language (SHACL) och Shapes Expression (ShEx).Resultatet av valideringsspråksjämförelsen konkluderade SHACL som valideringsspråket med en större domän av begränsningar, mer finkorniga begränsningar och med möjligheten att definiera nya begränsningar. Detta var baserat på att SHACL-begränsningarna uppmättes täcka 89,5 % av ShEx-begränsningarna och 67,8 % för det omvända. SHACL- och ShEx-täckningen för Resource Shapes-egenskapsbegränsningar mättes till 75 % respektive 50 %. SHACL rekommenderades och valdes för att vidareutveckla prototypen.Vid vidareutveckling av prototypen infördes abstrakta superklasser i den underliggande datamodellen. Superklasserna tog i huvudsak rollen som tidigare klasser för valideringsspråk, som istället utgjordes som underklasser. SHACL anges som en sådan underklass. Denna design erbjöd hög kodåteranvändning inom prototypen men gav också upphov till problem som relaterade till plugin-teknologier som prototypen bygger på. Den nuvarande lösningen har fortfarande problemet att egenskaper hos ett valideringsspråk kan läggas till klasser av ett annat valideringsspråk.

Šis bakalaura darbs apraksta semantiskajā tīmeklī pieejamo RDF datu validācijas iespējas, izmantojot divas no populārākajām datu formu ierobežojumu valodām - SHACL un ShEx. Datu formu ierobežojumu valodas ļauj pārliecināties, vai semantiskā tīmekļa dati atbilst sagaidītajam formātam no datu lietotāja viedokļa, kā arī, dod iespēju uzlabot šo datu kvalitāti no datu īpašnieka viedokļa. Darba ievadā ir sniegts vispārīgs ieskats semantiskā tīmekļa tehnoloģijās, parādot to sasaisti ar darba pamattēmu. Iztirzājuma daļā ir aprakstītas RDF datu formu ierobežojumu valodas SHACL un ShEx, kā arī dots abu valodu sniegto iespēju salīdzinājums. Atsevišķi tiek apskatīta arī RDF datu praktiskā validācija. Bakalaura darba ietvaros tika izstrādāta tīmekļa lietotne, kas ļauj uz reālu un jau pārbaudītu RDF datu pamata izveidot ShEx datu formas, kuras var izmantot citu līdzīgu RDF datu validācijai. Ņemot vērā to, ka abas datu formu ierobežojumu valodas (SHACL un ShEx) joprojām ir izstrādes stadijā, šajā darbā ir iekļauta tikai tā informācija, kas bija pieejama līdz darba iesniegšanas brīdim., This thesis describes validation options of RDF data originated from the semantic web, by using two of the most popular data shape constraint languages - SHACL and ShEx. Data shape constraint languages let one make sure that the data comply with the format that the user expects, as well as provide an opportunity to improve the quality of the data from the data owner's point of view. The introductory part provides with an insight into the general information about the semantic web technologies, demonstrating their connection with the main topic. The theoretical part includes a description of data shape constraint languages SHACL and ShEx, as well as a comparison of both languages. A separate chapter is devoted to the practical RDF data validation. Within the framework of the thesis a web application has been developed that can accept real and already tested RDF data as an input, and create ShEx data shapes as an output that can be used to validate other similar RDF data. Given the fact that both data forms restriction languages (SHACL and ShEx) are still in the development phase, this thesis contains only the information that was available till the moment of submission.

Presentation at WikidataCon 2019 in Berlin.

Presentation at WikidataCon 2019 in Berlin., Additional funding from the Alfred P. Sloan Foundation under grant number G-2019-11458.