A decade of agile methodologies

Relational Database (RDB) has been widely used as the back-end database of information system. Contains a wealth of high-quality information, RDB provides conceptual model and metadata needed in the ontology construction. However, most of the existing ontology building approaches convert RDB schema without considering the knowledge resided in the database. This paper proposed the approach for ontology extraction on top of RDB by incorporating concept hierarchy as background knowledge. Incorporating the background knowledge in the building process of Web Ontology Language (OWL) ontology gives two main advantages: (1) accelerate the building process, thereby minimizing the conversion cost; (2) background knowledge guides the extraction of knowledge resided in database. The experimental simulation using a gold standard shows that the Taxonomic F-measure (TF) evaluation reaches 90% while Relation Overlap (RO) is 83.33%. In term of processing time, this approach is more efficient than the current approaches. In addition, our approach can be applied in any of the fields such as eGoverment, eCommerce and so on.

Short Communication: Ontology extraction from relational database: Concept hierarchy as background knowledge

Organization scholars differ in their understanding and application of the construct of ''knowledge'' in theorizing and empirical research. Over the past years, two perspectives have become prevalent in organization science. The individualist perspective assumes the locus of knowledge is people who learn, and that knowledge cannot extend beyond the physical limits of human beings. The collectivist perspective assumes the locus of knowledge is collective. Collective entities accumulate knowledge through forms of social learning. Boundaries of knowledge are drawn around social entities-groups, communities, networks, and organizational units, etc. Recent work in management and organization science has accentuated the differences, and argued against the widespread adoption of a collectivist perspective. This argument holds implications for information systems research. The current paper reviews selected contributions on the locus of knowledge, presents an argument for a combined collectivist and individualist perspective, and outlines future directions for information systems research. Drawing on two significant examples, I show that information systems research has a strategic role to play in greatly advancing this combined perspective.

Individualist and collectivist perspectives on knowledge in organizations: Implications for information systems research

Many methodologies, practices, techniques and tools have been suggested for process improvement, among them knowledge management and agile methodologies, which are the focus of this study. Systematic reviews published on knowledge management and agile methodologies have significantly contributed to detailed and deep discussions surrounding these issues. Nevertheless, we realised that there was a gap between these two areas that needed further clarification. Therefore, the objective of this study was to raise the main topics that emerge from knowledge management in agile methodologies. The research method used in this paper is based on a systematic review. We reviewed studies of knowledge management and agile methodologies, published in major software engineering journals and conference proceedings. The search strategy identified 2879 studies, of which 25 were selected as primary studies. The main topics were taken from these 25 works and, in order for them to be discussed; meta-analysis techniques were used to group these topics. The main discussion generated around these analyses was the preferential use of tacit knowledge, instead of explicit knowledge, and its influence on agile projects. This situation has implications for communication, human and social factors, software development cycle and artifacts, tools for knowledge management and knowledge representation forms.

Knowledge Management in Agile Software Projects: A Systematic Review

This book presents a collection of research papers focusing on issues emerging from the interaction of information technologies and organizational systems. In particular, the individual contributions examine digital platforms and artifacts currently adopted in both the business world and society at large (people, communities, firms, governments, etc.). The topics covered include: virtual organizations, virtual communities, smart societies, smart cities, ecological sustainability, e-healthcare, e-government, and interactive policy-making (IPM).The book offers a multidisciplinary perspective on a variety of information systems topics. It is also particularly relevant to information systems practitioners such as IS managers, business managers and policy makers. The content is based on a selection of the best papers (original double-blind peer-reviewed contributions) presented at the annual conference of the Italian chapter of AIS, which was held in Milan, Italy in December 2013.

From Information to Smart Society: Environment, Politics and Economics

The notion of knowledge artifact has rapidly gained popularity in the fields of general knowledge management and more recently knowledge-based systems. The main goal on this paper is to propose and discuss a methodology for the design and implementation of knowledge-based systems founded on knowledge artifacts. We advocate that the systems built according to this methodology can be effective to convey the flow of knowledge between different communities of practice. Our methodology has been developed from the ground up, i.e. we have built some concrete systems based on the abstract notion of knowledge artifact and synthesized our methodology based on reflections upon our experiences building these systems. In this paper, we also describe the most relevant systems we have built and how they have guided us to the synthesis of our proposed methodology.

Design issues for knowledge artifacts

Supporting Knowledge Maintenance Through Knowledge Artifacts

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Design issues for knowledge artifacts

Supporting Knowledge Maintenance Through Knowledge Artifacts