Mapping heterogeneous research infrastructure metadata into a unified catalogue for use in a generic virtual research environment

Virtual Research Environments (VREs), also known as science gateways or virtual laboratories, assist researchers in data science by integrating tools for data discovery, data retrieval, workflow management and researcher collaboration, often coupled with a specific computing infrastructure. Recently, the push for better open data science has led to the creation of a variety of dedicated research infrastructures (RIs) that gather data and provide services to different research communities, all of which can be used independently of any specific VRE. There is therefore a need for generic VREs that can be coupled with the resources of many different RIs simultaneously, easily customised to the needs of specific communities. The resource metadata produced by these RIs rarely all adhere to any one standard or vocabulary however, making it difficult to search and discover resources independently of their providers without some translation into a common framework. Cross-RI search can be expedited by using mapping services that harvest RI-published metadata to build unified resource catalogues, but the development and operation of such services pose a number of challenges. In this paper, we discuss some of these challenges and look specifically at the VRE4EIC Metadata Portal, which uses X3ML mappings to build a single catalogue for describing data products and other resources provided by multiple RIs. The Metadata Portal was built in accordance to the e-VRE Reference Architecture, a microservice-based architecture for generic modular VREs, and uses the CERIF standard to structure its catalogued metadata. We consider the extent to which it addresses the challenges of cross-RI search, particularly in the environmental and earth science domain, and how it can be further augmented, for example to take advantage of linked vocabularies to provide more intelligent semantic search across multiple domains of discourse

Semantic enrichment of knowledge sources supported by domain ontologies

This thesis introduces a novel conceptual framework to support the creation of knowledge representations based on enriched Semantic Vectors, using the classical vector space model approach extended with ontological support. One of the primary research challenges addressed here relates to the process of formalization and representation of document contents, where most existing approaches are limited and only take into account the explicit, word-based information in the document. This research explores how traditional knowledge representations can be enriched through incorporation of implicit information derived from the complex relationships (semantic associations) modelled by domain ontologies with the addition of information presented in documents. The relevant achievements pursued by this thesis are the following: (i) conceptualization of a model that enables the semantic enrichment of knowledge sources supported by domain experts; (ii) development of a method for extending the traditional vector space, using domain ontologies; (iii) development of a method to support ontology learning, based on the discovery of new ontological relations expressed in non-structured information sources; (iv) development of a process to evaluate the semantic enrichment; (v) implementation of a proof-of-concept, named SENSE (Semantic Enrichment kNowledge SourcEs), which enables to validate the ideas established under the scope of this thesis; (vi) publication of several scientific articles and the support to 4 master dissertations carried out by the department of Electrical and Computer Engineering from FCT/UNL. It is worth mentioning that the work developed under the semantic referential covered by this thesis has reused relevant achievements within the scope of research European projects, in order to address approaches which are considered scientifically sound and coherent and avoid “reinventing the wheel”.European research projects - CoSpaces (IST-5-034245), CRESCENDO (FP7-234344) and MobiS (FP7-318452

Toward a Model of Intercultural Warrant: A Case of the Korean Decimal Classification\u27s Cross-cultural Adaptation of the Dewey Decimal Classification

I examined the Korean Decimal Classification (KDC)\u27s adaptation of the Dewey Decimal Classification (DDC) by comparing the two systems. This case manifests the sociocultural influences on KOSs in a cross-cultural context. I focused my analysis on the changes resulting from the meeting of the two cultures, answering the main research question: “How does KDC adapt DDC in terms of underlying sociocultural perspectives in a classificatory form?” I took a comparative approach and address the main research question in two phases. In Phase 1, quantities of class numbers were analyzed by edition and discipline. The main class with the most consistently high number of class numbers in DDC was the social sciences, while the main class with the most consistently high number of class numbers in KDC was technology. The two main classes are expected to differ in semantic contents or specificities. In Phase 2, patterns of adaptations were analyzed by examining the class numbers, captions, and hierarchical relations within the developed adaptation taxonomy. Implementing the taxonomy as a coding scheme brings two comparative features of classifications: 1) semantic contents determined by captions and quantity of subordinate numbers; and 2) structural arrangement determined by ranks, the broader category, presence and the order of subordinate numbers. Surveying proper forms of adaptation resulted in the development of an adaptation taxonomy that will serve as a framework to account for the conflicts between and harmonization of multiple social and cultural influences in knowledge structures. This study has ramifications in theoretical and empirical foundations for the development of “intercultural warrant” in KOSs

From Social Tagging to Social Hierarchies: Sharing Deeper Structural Knowledge in Web 2.0

Social tagging systems, such as del.icio.us, have helped users find and reuse information by sharing individuals’ structural knowledge, i.e., the knowledge of relationships among documents and concepts. Besides being an Internet phenomenon, social tagging can help organizations manage their intranet document repositories. The structural knowledge embedded in tags is flat, shallow, and often ambiguous however. We develop a theoretical model to argue for potential benefits of sharing deeper structural knowledge in an electronic document repository through personal document hierarchies. Based on the theoretical model, we design a “social hierarchies” system. Deployment and exploratory study confirm the benefits of sharing personal hierarchies in a collaborative knowledge work environment and suggest future research directions

Mapping the relationship between knowledge management and information architecture

Includes bibliographical references (leaves 106-115).This dissertation defines knowledge in terms or traditional epistemological ideals and as a strategic resource. Knowledge management is defined in terms or the ability or organizations to manage knowledge as a strategic resource in order to gain all advantage from it. In the knowledge management framework, knowledge is presented as a continuum consisting of tacit, implicit and explicit knowledge. Tacit and implicit knowledge is managed through the acknowledgement of the social nature of knowledge. One method to achieve this is communities of practice. On the other end of the spectrum, explicit knowledge is very close in nature and character to information. Due to the expansion of available information resources the design and structure of information (explicit knowledge) for effective retrieval has become very important. Information architecture is a field that specializes in the design and structure of information for effective retrieval. Traditional information architecture tools such as metadata and subject classification address some of the issues, but experience difficulty in heterogeneous environments such as the Internet. Topic maps are considered as a possible solution to the concerns of metadata classification and subject based classification. Due to the extent and nature of the information recorded in a topic map, it becomes an information resource in itself. Topic maps also act as an enabling technology for knowledge management as it maps the complex relationships between concepts and include a range of information resources. The conclusion of this dissertation is the representation of a conceptual model based on the themes developed in this dissertation. The main advantage of the conceptual model is the clear and direct link between knowledge management and information architecture