Toward Semantics-aware Representation of Digital Business Processes

An extended enterprise (EE) can be described by a set of models each representing a specific aspect of the EE. Aspects can for example be the process flow or the value description. However, different models are done by different people, which may use different terminology, which prevents relating the models. Therefore, we propose a framework consisting of process flow and value aspects and in addition a static domain model with structural and relational components. Further, we outline the usage of the static domain model to enable relating the different aspects

Ontop: answering SPARQL queries over relational databases

We present Ontop, an open-source Ontology-Based Data Access (OBDA) system that allows for querying relational data sources through a conceptual representation of the domain of interest, provided in terms of an ontology, to which the data sources are mapped. Key features of Ontop are its solid theoretical foundations, a virtual approach to OBDA, which avoids materializing triples and is implemented through the query rewriting technique, extensive optimizations exploiting all elements of the OBDA architecture, its compliance to all relevant W3C recommendations (including SPARQL queries, R2RML mappings, and OWL2QL and RDFS ontologies), and its support for all major relational databases

The use of ontologies for effective knowledge modelling and information retrieval

© 2017 The dramatic increase in the use of knowledge discovery applications requires end users to write complex database search requests to retrieve information. Such users are not only expected to grasp the structural complexity of complex databases but also the semantic relationships between data stored in databases. In order to overcome such difficulties, researchers have been focusing on knowledge representation and interactive query generation through ontologies, with particular emphasis on improving the interface between data and search requests in order to bring the result sets closer to users research requirements. This paper discusses ontology-based information retrieval approaches and techniques by taking into consideration the aspects of ontology modelling, processing and the translation of ontological knowledge into database search requests. It also extensively compares the existing ontology-to-database transformation and mapping approaches in terms of loss of data and semantics, structural mapping and domain knowledge applicability. The research outcomes, recommendations and future challenges presented in this paper can bridge the gap between ontology and relational models to generate precise search requests using ontologies. Moreover, the comparison presented between various ontology-based information retrieval, database-to-ontology transformations and ontology-to-database mappings approaches provides a reference for enhancing the searching capabilities of massively loaded information management systems

Using ontologies to abstract relational databases conceptual model

This paper addresses the problematic Digital Preservation and focuses on the conceptual model within a specific class of digital objects: Relational Databases. Previously, a neutral format was adopted to pursue the goal of platform independence and to achieve a standard format in the digital preservation of relational databases, both data and structure (logical model). Currently, in this project, we intend to address the preservation of relational databases by focusing on the conceptual model of the database, considering the database semantics as an impor- tant preservation ”property”. For the representation of this higher level of abstraction present in databases we use an ontology based approach. At this higher abstraction level exists inherent Knowledge associated to the database semantics that we tentatively represent using ”Web Ontol- ogy Language” (OWL). We developed a prototype (supported by case study) and define a mapping algorithm for the conversion between the database and OWL. The ontology approach is adopted to formalize the knowledge associated to the conceptual model of the database and also a methodology to create an abstract representation of it

Integrating Distributed Sources of Information for Construction Cost Estimating using Semantic Web and Semantic Web Service technologies

A construction project requires collaboration of several organizations such as owner, designer, contractor, and material supplier organizations. These organizations need to exchange information to enhance their teamwork. Understanding the information received from other organizations requires specialized human resources. Construction cost estimating is one of the processes that requires information from several sources including a building information model (BIM) created by designers, estimating assembly and work item information maintained by contractors, and construction material cost data provided by material suppliers. Currently, it is not easy to integrate the information necessary for cost estimating over the Internet. This paper discusses a new approach to construction cost estimating that uses Semantic Web technology. Semantic Web technology provides an infrastructure and a data modeling format that enables accessing, combining, and sharing information over the Internet in a machine processable format. The estimating approach presented in this paper relies on BIM, estimating knowledge, and construction material cost data expressed in a web ontology language. The approach presented in this paper makes the various sources of estimating data accessible as Simple Protocol and Resource Description Framework Query Language (SPARQL) endpoints or Semantic Web Services. We present an estimating application that integrates distributed information provided by project designers, contractors, and material suppliers for preparing cost estimates. The purpose of this paper is not to fully automate the estimating process but to streamline it by reducing human involvement in repetitive cost estimating activities

Relational databases conceptual preservation

Previously, a neutral format was adopted to pursue the goal of platform independence and to achieve a standard format in the digital preservation of relational databases, both data and structure (logical model). Currently, we intend to address the preservation of relational databases by focusing on the conceptual model of the database, considering the database semantics as an important preservation ”property”. For the representation of this higher level of abstraction present in databases we use an ontology based approach. At this higher abstraction level exists inherent Knowledge associated to the database semantics that we tentatively represent using ”Web Ontology Language” (OWL). We developed a prototype (supported by case study) and define a mapping algorithm for the conversion between the database and OWL

Equality-friendly well-founded semantics and applications to description logics

We tackle the problem of defining a well-founded semantics (WFS) for Datalog rules with existentially quantified variables in their heads and nega- tions in their bodies. In particular, we provide a WFS for the recent Datalog± family of ontology languages, which covers several important description logics (DLs). To do so, we generalize Datalog± by non-stratified nonmonotonic nega- tion in rule bodies, and we define a WFS for this generalization via guarded fixed point logic. We refer to this approach as equality-friendly WFS, since it has the advantage that it does not make the unique name assumption (UNA); this brings it close to OWL and its profiles as well as typical DLs, which also do not make the UNA. We prove that for guarded Datalog± with negation under the equality- friendly WFS, conjunctive query answering is decidable, and we provide precise complexity results for this problem. From these results, we obtain precise defi- nitions of the standard WFS extensions of EL and of members of the DL-Lite family, as well as corresponding complexity results for query answering

New dimension in relational database preservation : raising the abstraction level

The work addressed in this paper focuses on the preserva- tion of the conceptual model within a specific class of dig- ital objects: Relational Databases. Previously, a neutral format was adopted to pursue the goal of platform inde- pendence and to achieve a standard format in the digital preservation of relational databases, both data and struc- ture (logical model). Currently, in this project, we address the preservation of relational databases by focusing on the conceptual model of the database, considering the database semantics as an important preservation ”property”. For the representation of this higher layer of abstraction present in databases we use an ontology based approach. At this higher abstraction level exists inherent Knowledge associated to the database semantics that we tentatively represent using ”Web Ontology Language” (OWL). We developed a proto- type (supported by case study) and define a mapping algo- rithm for the conversion between the database and OWL. The ontology approach is adopted to formalize the knowl- edge associated to the conceptual model of the database and also a methodology to create an abstract representation of it

Sharing e-Health information through ontological layering

e-Health information, including patient clinical and demographic data, is very often dispersed across various environments, which either generate them or retrieve them from different sources. Healthcare professionals often need related e-health information in order to obtain a more comprehensive picture of a patient's health status. There are many obstacles to retrieving information and data from heterogeneous sources. In this paper we show that our ontological layering helps in (a) classifying requests imposed by healthcare professionals when retrieving e-health information from heterogeneous sources and (b) resolving semantic heterogeneities across repositories and composing an adequate answer to issued requests. We use a layered software architectural model based on Generic ontology for Context-aware, Interoperable and Data sharing (Go- CID) software applications, applicable to e-Health environments. Ontological layering and reasoning have been demonstrated with semantic web technologies