A Semantic-Based Architecture for Managing Knowledge-Intensive Organizations: The ARISTOTELE Platform (original) (raw)
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During the past few years, various organisations embraced the Enterprise 2.0 paradigms, providing their employees with new means to enhance collaboration and knowledge sharing in the workplace. However, while tools such as blogs, wikis, and principles like free-tagging or content syndication allow user-generated content to be more easily created and shared in the enterprise, in spite of some social issues, these new practices lead to various problems in terms of knowledge management. In this chapter, we provide an approach based on Semantic Web and Linked Data technologies for (1) integrating heterogeneous data from distinct Enterprise 2.0 applications, and (2) bridging the gap between raw text and machine-readable Linked Data. We discuss the theoretical background of our proposal as well as a practical case-study in enterprise, focusing on the various add-ons that have been provided to the original information system, as well as presenting how public Linked Open Data from the Web can be used to enhance existing Enterprise 2.0 ecosystems.
A Knowledge-Engine Architecture for a Competence Management Information System
This paper describes the ongoing project to develop a knowledge-engine architecture that is being specified and developed by a Portuguese software development company called Shortcut. The primary goal of this work is create an architecture suitable for use, initially, in a Competence Management System (CMS) but also scalable for later use in more generic forms of Knowledge Management Systems (KMS). In general, Knowledge Management (KM) initiatives promote the management, i.e. the creation, storage and sharing, of knowledge assets within an organization. The practical focus of our work is to support the management of employees' competencies through using a KM approach to create a web based CMS based on a structured content management infrastructure. The system is designed using an ontology-driven framework that incorporates expert annotations which integrate aspects of less tangible knowledge, such as contextual information with more structured knowledge such as that stored in databases, procedures, manuals, books and reports. The theoretical focus of the work is on the representation of competence-based knowledge resources, such as human capital, skills, heuristics acquired during project development, best practices and lessons-learned. This work should contribute for improving the understanding and analysis of the collective knowledge, skills and competencies that are created through problem solving in day-to-day activities and could act as a meeting point for issues around problem solving in complex organizations and context-based information retrieval.
People who belong to an organization own common knowledge that, with time, grows, evolves and is transferred from one person to another. As it happens in an ecosystem, each individual has his own work environment and personal goals, but also interacts with others, using common knowledge and contributing to its improvement. According to this vision, we have created a knowledge management environment equipped with a set of tools to better support cooperation by working along two main directions: the first one relies on establishing a community driven central repository enhanced with Semantic Web technologies, which allows information to be organized according to its semantic structure by exploiting classification, information extraction, and semantic filtering techniques. The second direction relies on enriching users' everyday work environment – including emails, web browsers, RSS aggregators, and desktops – by providing tools that exploit contextual information, directing more relevant information where it is needed and adding value to the information as it is generated and shared. The system we describe in this paper on the one hand opens up corporate knowledge even to individuals who are normally unwilling to use a traditional KM system and, on the other hand, makes access much easier to those users who are already willing to share, leading to a healthier knowledge ecosystem which grows through seamless cross fertilization.
Semantic Web Technologies in Knowledge Management
Knowledge management is a big challenge especially in large organisations. Knowledge resides in many different forms: as explicit knowledge in documents and processes and as tacit knowledge in people and procedures and in many different forms between these two extremes. The vision of the Semantic Web is to offer more intelligent services by facilitating machine understanding of web content. Ontologies are an important building block in Semantic Web. An ontology describes the concepts, their relationships and properties within their domain, and it can be utilised both to offer automatic infering and interoperability between applications. This is an appropriate vision for knowledge management, too. This paper describes how Semantic Web ontologies can be utilised in a research organisation to create a common language to describe its knowledge. The same ontology can be utilised to manage projects, people, documents and products. With a common ontology, information that is spread out in many different applications and documents can be viewable in a way that is easy to understand and navigate. The ontology makes it possible to search both knowledge content and experts who are linked to different topics, thereby bridging the gap between the tacit and explicit knowledge.