Leveraging SPARQL Queries for UML Consistency Checking

2021 ◽  
Vol 31 (04) ◽  
pp. 635-654
Author(s):  
Bingyang Wei ◽  
Jing Sun
Keyword(s):  
Knowledge Base ◽  
Query Language ◽  
Knowledge Engineering ◽  
Software Requirements ◽  
Consistency Checking ◽  
Engineering Approach ◽  
Requirements Modeling ◽  
Ontology Language ◽  
Uml Diagrams ◽  
Requirements Models

Context and motivation: Multiple-viewed requirements modeling method describes the system to-be from different perspectives. Some requirements models are then specified in various UML diagrams. Question/problem: Managing those models can be tedious and error-prone, since a lot of CASE tools provide poor support for reasoning and consistency checking. Principal ideas/results: Ontology is a formal notation for describing concepts and their relations in a domain. Since software requirements are a kind of knowledge, we propose to adopt a knowledge engineering approach for managing the consistency of requirements models. In this paper, an ontology for three most commonly used UML diagrams is developed in Web Ontology Language (OWL). The transformation of UML class, sequence and state diagrams to OWL knowledge base is presented. Owing to the underlying logical reasoning capability of OWL, a semantic query language, SPARQL (SPARQL Protocol and RDF Query Language), is used to query the knowledge base for consistency checking. Contribution: This paper introduces a semantic web-based knowledge engineering approach to represent and manage software requirements knowledge in OWL. By experimenting with a concrete software system, we demonstrate the feasibility and applicability of this knowledge approach.

An Ontology-Based Information Extraction System for Organic Farming

2021 ◽  
Vol 17 (2) ◽  
pp. 79-99
Author(s):  
Adebayo Adewumi Abayomi-Alli ◽  
Oluwasefunmi 'Tale Arogundade ◽  
Sanjay Misra ◽  
Mulkah Opeyemi Akala ◽  
Abiodun Motunrayo Ikotun ◽  
...  
Keyword(s):  
Information Extraction ◽  
Knowledge Base ◽  
Organic Farming ◽  
Description Logic ◽  
Query Language ◽  
Relevant Information ◽  
Extraction System ◽  
Ontology Development ◽  
Ontology Language ◽  
Information Extraction System

In the existing farming system, information is obtained manually, and most times, farmers act based on their discretion. Sometimes, farmers rely on information from experts and extension officers for decision making. In recent times, a lot of information systems are available with relevant information on organic farming practices; however, such information is scattered in different context, form, and media all over the internet, making their retrieval difficult. The use of ontology with the aid of a conceptual scheme makes the comprehensive and detailed formalization of any subject domain possible. This study is aimed at acquiring, storing, and providing organic farming-based information available to current and intending software developer who may wish to develop applications for farmers. It employs information extraction (IE) and ontology development techniques to develop an ontology-based information extraction (OBIE) system called ontology-based information extraction system for organic farming (OBIESOF). The knowledge base was built using protégé editor; Java was used for the implementation of the ontology knowledge base with the aid of the high-level application programming language for working web ontology language application program interface (OWL API). In contrast, HermiT was used to checking the consistencies of the ontology and for submitting queries in order to verify their validity. The queries were expressed in description logic (DL) query language. The authors tested the capability of the ontology to respond to user queries by posing instances of the competency questions from DL query interface. The answers generated by the ontology were promising and serve as positive pointers to its usefulness as a knowledge repository.

Personalized cloud service review analysis based on modularized ontology

2020 ◽  
Vol 44 (5) ◽  
pp. 953-975
Author(s):  
Emna Ben-Abdallah ◽  
Khouloud Boukadi ◽  
Mohamed Hammami ◽  
Mohamed Hedi Karray
Keyword(s):  
Knowledge Base ◽  
Positive Impact ◽  
Cloud Service ◽  
Service Evaluation ◽  
End Users ◽  
Cloud Services ◽  
Limited Information ◽  
Content Type ◽  
Ontology Language ◽  
Modular Ontology

PurposeThe purpose of this paper is to analyze cloud reviews according to the end-user context and requirements.Design/methodology/approachpropose a comprehensive knowledge base composed of interconnected Web Ontology Language, namely, modular ontology for cloud service opinion analysis (SOPA). The SOPA knowledge base will be the basis of context-aware cloud service analysis using consumers' reviews. Moreover, the authors provide a framework to evaluate cloud services based on consumers' reviews opinions.FindingsThe findings show that there is a positive impact of personalizing the cloud service analysis by considering the reviewers' contexts in the performance of the framework. The authors also proved that the SOPA-based framework outperforms the available cloud review sites in term of precision, recall and F-measure.Research limitations/implicationsLimited information has been provided in the semantic web literature about the relationships between the different domains and the details on how that can be used to evaluate cloud service through consumer reviews and latent opinions. Furthermore, existing approaches are lacking lightweight and modular mechanisms which can be utilized to effectively exploit information existing in social media.Practical implicationsThe SOPA-based framework facilitates the opinion based service evaluation through a large number of consumer's reviews and assists the end-users in analyzing services as per their requirements and their own context.Originality/valueThe SOPA ontology is capable of representing the content of a product/service as well as its related opinions, which are extracted from the customer's reviews written in a specific context. Furthermore, the SOPA-based framework facilitates the opinion based service evaluation through a large number of consumer's reviews and assists the end-users in analyzing services as per their requirements and their own context.

scholarly journals Uncertainty modeling process for semantic technology

2016 ◽  
Vol 2 ◽  
pp. e77 ◽  
Author(s):  
Rommel N. Carvalho ◽  
Kathryn B. Laskey ◽  
Paulo C.G. Da Costa
Keyword(s):  
Knowledge Engineering ◽  
Uncertainty Modeling ◽  
Domain Model ◽  
Proof Of Concept ◽  
Semantic Technology ◽  
Modeling Process ◽  
Ontology Language ◽  
Domain Semantics ◽  
Probabilistic Ontology

The ubiquity of uncertainty across application domains generates a need for principled support for uncertainty management in semantically aware systems. A probabilistic ontology provides constructs for representing uncertainty in domain ontologies. While the literature has been growing on formalisms for representing uncertainty in ontologies, there remains little guidance in the knowledge engineering literature for how to design probabilistic ontologies. To address the gap, this paper presents the Uncertainty Modeling Process for Semantic Technology (UMP-ST), a new methodology for modeling probabilistic ontologies. To explain how the methodology works and to verify that it can be applied to different scenarios, this paper describes step-by-step the construction of a proof-of-concept probabilistic ontology. The resulting domain model can be used to support identification of fraud in public procurements in Brazil. While the case study illustrates the development of a probabilistic ontology in the PR-OWL probabilistic ontology language, the methodology is applicable to any ontology formalism that properly integrates uncertainty with domain semantics.

scholarly journals Building an OWL ontology with Xper3

2018 ◽  
Vol 2 ◽  
pp. e25614 ◽  
Author(s):  
Florian Pellen ◽  
Sylvain Bouquin ◽  
Isabelle Mougenot ◽  
Régine Vignes-Lebbe
Keyword(s):  
Semantic Web ◽  
Knowledge Base ◽  
Expressive Power ◽  
Knowledge Bases ◽  
User Friendliness ◽  
Standard Format ◽  
Ontology Language ◽  
Closed World ◽  
Web Standards ◽  
Description Framework

Xper3 (Vignes Lebbe et al. 2016) is a collaborative knowledge base publishing platform that, since its launch in november 2013, has been adopted by over 2 thousand users (Pinel et al. 2017). This is mainly due to its user friendly interface and the simplicity of its data model. The data are stored in MySQL Relational DBs, but the exchange format uses the TDWG standard format SDD (Structured Descriptive DataHagedorn et al. 2005). However, each Xper3 knowledge base is a closed world that the author(s) may or may not share with the scientific community or the public via publishing content and/or identification key (Kopfstein 2016). The explicit taxonomic, geographic and phenotypic limits of a knowledge base are not always well defined in the metadata fields. Conversely terminology vocabularies, such as Phenotype and Trait Ontology PATO and the Plant Ontology PO, and software to edit them, such as Protégé and Phenoscape, are essential in the semantic web, but difficult to handle for biologist without computer skills. These ontologies constitute open worlds, and are expressed themselves by RDF triples (Resource Description Framework). Protégé offers vizualisation and reasoning capabilities for these ontologies (Gennari et al. 2003, Musen 2015). Our challenge is to combine the user friendliness of Xper3 with the expressive power of OWL (Web Ontology Language), the W3C standard for building ontologies. We therefore focused on analyzing the representation of the same taxonomic contents under Xper3 and under different models in OWL. After this critical analysis, we chose a description model that allows automatic export of SDD to OWL and can be easily enriched. We will present the results obtained and their validation on two knowledge bases, one on parasitic crustaceans (Sacculina) and the second on current ferns and fossils (Corvez and Grand 2014). The evolution of the Xper3 platform and the perspectives offered by this link with semantic web standards will be discussed.

Semantic Search Engine and Object Database Guidelines for Service Oriented Architecture Models

2013 ◽  
pp. 225-250
Author(s):  
Omar Shehab ◽  
Ali Hussein Saleh Zolait
Keyword(s):  
Search Engine ◽  
Service Oriented Architecture ◽  
Query Language ◽  
Semantic Search ◽  
Semantic Query ◽  
Qualitative Survey ◽  
Ontology Language ◽  
Service Oriented ◽  
The Cost ◽  
Semantic Search Engine

In this paper, the authors propose a Semantic Search Engine, which retrieves software components precisely and uses techniques to store these components in a database, such as ontology technology. The engine uses semantic query language to retrieve these components semantically. The authors use an exploratory study where the proposed method is mapped between object-oriented concepts and web ontology language. A qualitative survey and interview techniques were used to collect data. The findings after implementing this research are a set of guidelines, a model, and a prototype to describe the semantic search engine system. The guidelines provided help software developers and companies reduce the cost, time, and risks of software development.

SWRLx

2018 ◽  
pp. 348-367
Author(s):  
Souad Bouaicha ◽  
Zizette Boufaida
Keyword(s):  
Semantic Web ◽  
Knowledge Base ◽  
Object Oriented ◽  
Web Ontology Language ◽  
Rule Engine ◽  
Ontology Language ◽  
New Knowledge ◽  
Semantic Web Rule Language

Although OWL (Web Ontology Language) and SWRL (Semantic Web Rule Language) add considerable expressiveness to the Semantic Web, they do have expressive limitations. For some reasoning problems, it is necessary to modify existing knowledge in an ontology. This kind of problem cannot be fully resolved by OWL and SWRL, as they only support monotonic inference. In this paper, the authors propose SWRLx (Extended Semantic Web Rule Language) as an extension to the SWRL rules. The set of rules obtained with SWRLx are posted to the Jess engine using rewrite meta-rules. The reason for this combination is that it allows the inference of new knowledge and storing it in the knowledge base. The authors propose a formalism for SWRLx along with its implementation through an adaptation of different object-oriented techniques. The Jess rule engine is used to transform these techniques to the Jess model. The authors include a demonstration that demonstrates the importance of this kind of reasoning. In order to verify their proposal, they use a case study inherent to interpretation of a preventive medical check-up.

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