Related papers: Ontology Based Data Integration Over Document and …
More information is now being published in machine processable form on the web and, as de-facto distributed knowledge bases are materializing, partly encouraged by the vision of the Semantic Web, the focus is shifting from the publication…
Ontologies represent the conceptual knowledge of a domain. At the core of an ontology is the taxonomy of concepts and subconcepts that represent specific entities, which can be complex to build. In many cases, information is available in…
NoSQL data stores are commonly schema-less, providing no means for globally defining or managing the schema. While this offers great flexibility in early stages of application development, developers soon can experience the heavy burden of…
The eXtensible Markup Language (XML) can be used as data exchange format in different domains. It allows different parties to exchange data by providing common understanding of the basic concepts in the domain. XML covers the syntactic…
Low-code application development as proposed by the OutSystems Platform enables fast mobile and desktop application development and deployment. It hinges on visual development of the interface and business logic but also on easy integration…
Ontology-Based Data Access (OBDA) has traditionally focused on providing a unified view of heterogeneous datasets, either by materializing integrated data into RDF or by performing on-the fly querying via SPARQL query translation. In the…
Schema evolution is a crucial aspect in database management. The proposed taxonomies of schema changes have neglected the set of operations that involves relationships between entity types: aggregation and references, as well as the…
We present an ontology for representing workflows over components with Read-Write Linked Data interfaces and give an operational semantics to the ontology via a rule language. Workflow languages have been successfully applied for modelling…
The heterogeneity of data poses a great challenge when data from different sources is to be merged for one application. Solutions for this are offered, for example, by ontology-based data management (OBDM). A challenge of OBDM is the…
Modeling data lineage in relational databases remains a challenging problem, particularly in scenarios involving incomplete or missing dependencies between database objects. In this paper, we propose a novel ontology for relational database…
Translating natural language utterances to executable queries is a helpful technique in making the vast amount of data stored in relational databases accessible to a wider range of non-tech-savvy end users. Prior work in this area has…
Over the past decade, Knowledge Graphs have received enormous interest both from industry and from academia. Research in this area has been driven, above all, by the Database (DB) community and the Semantic Web (SW) community. However,…
Natural language is understandable by human and not machine. None technical persons can only use natural language to specify their business requirements. However, the current version of Business process management and notation (BPMN) tools…
Today's international corporations such as BASF, a leading company in the crop protection industry, produce and consume more and more data that are often fragmented and accessible through Web APIs. In addition, part of the proprietary and…
Ontologies are built on systems that conceptually evolve over time. In addition, techniques and languages for building ontologies evolve too. This has led to numerous studies in the field of ontology versioning and ontology evolution. This…
This paper introduces annotative indexing, a novel framework that unifies and generalizes traditional inverted indexes, column stores, object stores, and graph databases. As a result, annotative indexing can provide the underlying indexing…
Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within…
The benefit of using ontologies, defined by the respective data standards, is shown. It is presented how ontologies can be used for the semantic enrichment of data and how this can contribute to the vision of the semantic web to become…
Big Data technology is described. Big data is a popular term used to describe the exponential growth and availability of data, both structured and unstructured. There is constructed dataspace architecture. Dataspace has focused solely - and…
NoSQL databases support semi-structured data, typically modeled as JSON. They also provide limited (but expanding) query languages. Their idiomatic, non-SQL language constructs, the many variations, and the lack of formal semantics inhibit…