The CKC Challenge: Exploring Tools for Collaborative Knowledge Construction

The great success of Web 2.0 is mainly fuelled by an infrastructure that allows web users to create, share, tag, and connect content and knowledge easily. The tools for developing structured knowledge in this manner have started to appear as well. However, there are few, if any, user studies that are aimed at understanding what users expect from such tools, what works and what doesn't. We organized the Collaborative Knowledge Construction (CKC) Challenge to assess the state of the art for the tools that support collaborative processes for creation of various forms of structured knowledge. The goal of the Challenge was to get users to try out different tools and to learn what users expect from such tools /features that users need, features that they like or dislike. The Challenge task was to construct structured knowledge for a portal that would provide information about research. The Challenge design contained several incentives for users to participate. Forty-nine users registered for the Challenge; thirty three of them participated actively by using the tools. We collected extensive feedback from the users where they discussed their thoughts on all the tools that they tried. In this paper, we present the results of the Challenge, discuss the features that users expect from tools for collaborative knowledge constructions, the features on which Challenge participants disagreed, and the lessons that we learned

Survey of tools for collaborative knowledge construction and sharing

The fast growth and spread of Web 2.0 environments have demonstrated the great willingness of general Web users to contribute and share various type of content and information. Many very successful web sites currently exist which thrive on the wisdom of the crowd, where web users in general are the sole data providers and curators. The Semantic Web calls for knowledge to be semantically represented using ontologies to allow for better access and sharing of data. However, constructing ontologies collaboratively is not well supported by most existing ontology and knowledge-base editing tools. This has resulted in the recent emergence of a new range of collaborative ontology construction tools with the aim of integrating some Web 2.0 features into the process of structured knowledge construction. This paper provides a survey of the start of the art of these tools, and highlights their significant features and capabilities

Towards an ontology modeling tool. A validation in software engineering scenarios.

Ontology creation and management related processes are very important to define and develop semantic services. Ontology Engineering is the research field that provides the mechanisms to manage the life cycle of the ontologies. However, the process of building ontologies can be tedious and sometimes exhaustive. OWL VisMod is a tool designed for developing ontological engineering based on visual analytics concep tual modeling for OWL ontologies life cycle management, supporting both creation and understanding tasks. This paper is devoted to evaluate OWL VisMod through a set of defined tasks. The same tasks also will be done with the most known tool in Ontology Engineering, Protégé, in order to compare the obtained results and be able to know how is OWL VisMod perceived for the expert users. The comparison shows that both tools have similar acceptation scores, but OWL VisMod presents better feelings regard ing user’s perception tasks due to the visual analytics influence

Using Emotional Intelligence in Personalized Adaptation

Damjanovic, V. & Kravcik, M. (2007). Using Emotional Intelligence in Personalized Adaptation. In V. Sugumaran (Ed.), Intelligent Information Technologies: Concepts, Methodologies, Tools, and Applications (pp. 1716-1742). IGI Publishing.The process of training and learning in Web-based and ubiquitous environments brings a new sense of adaptation. With the evelopment of more sophisticated environments, the need for them to take into account the user’s traits, as well as the user’s devices on which the training is executed, has become an important issue in the domain of building novel training and learning environments. This chapter introduces an approach to the realization of personalized adaptation. According to the fact that we are dealing with the stereotypes of e-learners, having in mind emotional intelligence concepts to help in adaptation to the e-learners real needs and known preferences, we have called this system eQ. It stands for the using of the emotional intelligence concepts on the Web.PROLEARN - Network of Excellence in Professional Learnin

An incremental hybridisation of heterogeneous case studies to develop an ontology for capability engineering

An analysis of perspectives for “capability engineering” has been conducted by the INCOSE UK Capability Working Group (CWG). This paper is a continuation of this study led by the CWG ontology work stream that aims to develop a single shared ontology for the concept of capability engineering to enable semantic interoperability and to support a formal and explicit specification of a shared conceptualisation. Case study material from the different domains of rail, defence and information services was used. The ontology development was executed in three phases; (1) pre-analysis, (2) ontology modelling and (3) post-analysis. The pre-analysis involved literature reviews, requirements specification, systems engineering process utilisation; and resource identification i.e. examination of the case study material. The ontology modelling phase comprised information extraction and classification in addition to modelling and code representation using a mark-up tool, MS Excel and Protégé. The post-analysis involved validation workshops through using expert focus groups

Ontology of core data mining entities

In this article, we present OntoDM-core, an ontology of core data mining entities. OntoDM-core defines themost essential datamining entities in a three-layered ontological structure comprising of a specification, an implementation and an application layer. It provides a representational framework for the description of mining structured data, and in addition provides taxonomies of datasets, data mining tasks, generalizations, data mining algorithms and constraints, based on the type of data. OntoDM-core is designed to support a wide range of applications/use cases, such as semantic annotation of data mining algorithms, datasets and results; annotation of QSAR studies in the context of drug discovery investigations; and disambiguation of terms in text mining. The ontology has been thoroughly assessed following the practices in ontology engineering, is fully interoperable with many domain resources and is easy to extend

Constructing a Multilingual E-Learning Ontology through Web Crawling and Scraping

The emergence of digital technologies has transformed the landscape of education, driving the exploration of innovative methods to improve the efficiency and effectiveness of university e- learning. This study focuses on leveraging network management principles in combination with web crawling trends to propose a novel approach: a web crawling and scraping-driven method for constructing a multilingual ontology tailored specifically for university e-learning. The primary goal of this research is to create a comprehensive and continuously updated knowledge repository by systematically gathering and extracting information from a wide range of online sources. By incorporating multilingual capabilities into the proposed ontology, the aim is to transcend language barriers and establish a globally accessible and inclusive e-learning environment. This approach recognizes the intricate relationship between technology and education, highlighting the potential of automated data retrieval and ontology construction in reshaping the future of university e-learning. This research contributes significantly to the rapidly growing field of educational technology by introducing a forward-thinking paradigm. It empowers both educators and learners with a versatile and personalized learning experience that transcends cultural and linguistic boundaries. As the digital era continues to evolve, this approach serves as a beacon of innovation, exemplifying the transformative power of integrating cutting-edge technology with pedagogical efforts. In essence, this study presents a groundbreaking approach to enhance university e- learning by harnessing the capabilities of web crawling, scraping, and multilingual ontology construction. It emphasizes the importance of adapting to the ever-evolving digital landscape to provide an inclusive and accessible education experience for learners worldwide. Ultimately, this research represents a significant step forward in the ongoing effort to revolutionize education through the integration of advanced technology and pedagogical innovation