The Specification of Requirements in the MADAE-Pro Software Process

MADAE-Pro is an ontology-driven process for multi-agent domain and application engineering which promotes the construction and reuse of agent-oriented applications families. This article introduces MADAE-Pro, emphasizing the description of its domain analysis and application requirements engineering phases and showing how software artifacts produced from the first are reused in the last one. Illustrating examples are extracted from two case studies we have conducted to evaluate MADAE-Pro. The first case study assesses the Multi-Agent Domain Engineering sub-process of MADAE-Pro through the development of a multi-agent system family of recommender systems supporting alternative (collaborative, content-based and hybrid) filtering techniques. The second one, evaluates the Multi-Agent Application Engineering sub-process of MADAE-Pro through the construction of InfoTrib, a Tax Law recommender system which provides recommendations based on new tax law information items using a content-based filtering technique. ONTOSERS and InfoTrib were modeled using ONTORMAS, a knowledge-based tool for supporting and automating the tasks of MADAEPro

Ontology in software engineering

© 2018 authors. During the past years, ontological thinking and design have become more and more popular in the field of Artificial Intelligence (AI). More recently, Software Engineering (SE) has evolved towards more conceptual approaches based on the extensive adoption of models and meta-models. This paper briefly discusses the role of ontologies in SE according to a perspective that closely matches the theoretical life-cycle. These roles vary considerably across the development lifecycle. The use of ontologies to improve SE development activities is still relatively new (2000 onward), but it is definitely no more a novelty. Indeed, the role of such structures is well consolidated in certain SE aspects, such as requirement engineering. On the other hand, despite their well-known potential as knowledge representation mechanisms, ontologies are not completely exploited in the area of SE. We first (i) proposes a brief overview of ontologies and their current understanding within the Semantic Web with a focus on the benefits provided; then, the role that ontologies play in the more specific context of SE is addressed (ii); finally, we deal with (iii) some brief considerations looking at specific types of software architecture, such as Multi-Agent Systems (MAS) and Service-Oriented Architecture (SOA). The main limitation of our research is that we are focusing on traditional developments, where phases occur mostly sequentially. However, industry has fully embraced agile developments. It is unclear that agile practitioners are willing to adopt ontologies as a tool, unless we ensure that they can provide a clear benefit and they be used in a lean way, without introducing significant overhead to the agile development process

Using ontologies to synchronize change in relational database systems

Ontology is a building block of the semantic Web. Ontology building requires a detailed domain analysis, which in turn requires financial resources, intensive domain knowledge and time. Domain models in industry are frequently stored as relational database schemas in relational databases. An ontology base underlying such schemas can represent concepts and relationships that are present in the domain of discourse. However, with ever increasing demand for wider access and domain coverage, public databases are not static and their schemas evolve over time. Ontologies generated according to these databases have to change to reflect the new situation. Once a database schema is changed, these changes in the schema should also be incorporated in any ontology generated from the database. It is not possible to generate a fresh version of the ontology using the new database schema because the ontology itself may have undergone changes that need to be preserved. To tackle this problem, this paper presents a generic framework that will help to generate and synchronize ontologies with existing data sources. In particular we address the translation between ontologies and database schemas, but our proposal is also sufficiently generic to be used to generate and maintain ontologies based on XML and object oriented databases

Ontology in software engineering

During the past years, ontological thinking and design have become more and more popular in the field of Artificial Intelligence (AI). More recently, Software Engineering (SE) has evolved towards more conceptual approaches based on the extensive adoption of models and meta-models. This paper briefly discusses the role of ontologies in SE according to a perspective that closely matches the theoretical life-cycle. These roles vary considerably across the development lifecycle. The use of ontologies to improve SE development activities is still relatively new (2000 onward), but it is definitely no more a novelty. Indeed, the role of such structures is well consolidated in certain SE aspects, such as requirement engineering. On the other hand, despite their well-known potential as knowledge representation mechanisms, ontologies are not completely exploited in the area of SE. We first (i) proposes a brief overview of ontologies and their current understanding within the Semantic Web with a focus on the benefits provided; then, the role that ontologies play in the more specific context of SE is addressed (ii); finally, we deal with (iii) some brief considerations looking at specific types of software architecture, such as Multi-Agent Systems (MAS) and Service-Oriented Architecture (SOA). The main limitation of our research is that we are focusing on traditional developments, where phases occur mostly sequentially. However, industry has fully embraced agile developments. It is unclear that agile practitioners are willing to adopt ontologies as a tool, unless we ensure that they can provide a clear benefit and they be used in a lean way, without introducing significant overhead to the agile development process

The strategic value of targeted knowledge management - case study of an Australian refrigeration company

 This thesis is a study of design and implementation of an engineering knowledge management system to facilitate knowledge capture, sharing and reuse to both ensure business continuity and resolve a make-span problem in an Australian refrigeration company. The company had encountered problems with a number of engineering staff in the small product development team leaving the company and taking their expertise with them. This situation has impacted the business continuity of the company, because the knowledge and expertise used in the refrigerated display cabinet development process is a combination of explicit and tacit knowledge as the engineers conduct the product development process intuitively. Records of previous design and testing processes were either non-existent or stored in ways that were not accessible. The other business problem in the company resulted from product development taking too long, in effect from 6 weeks up to the worst case of one year. The company needed research solutions to both of these problems to strategically maintain the competitiveness of the company business. This research applied a single case study research method with a problem-solving paradigm, Design Science methodology, to develop and then test solutions. Design Science as a research methodology has two components, first design development and second, design evaluation. The researcher developed an engineering knowledge based system as an artefact to solve the problem of enabling company business continuity. Using ontology as a structural base, the KBS contains both knowledge elements captured from the engineers during the data collection process and existing knowledge artefacts in the company. The research used a set of multilayered research techniques, including semi-formal and formal interviews, serendipitous interviews, group meetings, observation and shadowing, to capture and then structure both the tacit and explicit knowledge. The resultant ontology was used to build the KBS to store both tacit and explicit knowledge and answer the engineers’ questions about their existing and previous product development processes. The KBS developed in this research is a knowledge repository to maintain records of the products design and testing processes in a searchable form. Use and then an evaluation of the system by the engineers and the executive staff of the company confirmed that the intention of the system to address the business continuity problem by knowledge capture, classification and storage was achieved and met the company’s business needs. This research also applied Heuristic Process Mining to the knowledge stored in the KBS to address the second problem identified initially by the company, that of lengthy make span in new product design and development. HPM is a technique using mathematical models to find relationships between tasks in the process. HMP measures dependency and frequency values between tasks and tasks with low D/F value can be eliminated from the process. This then can lead to the shorter product testing process. The research showed that the application of HPM to the stored process knowledge in the KMS was able to significantly reduce the product design and testing process in the company