Grammar of Dynamic Knowledge for Collaborative Knowledge Engineering and Representation

Constructive discussion must lead to a shared understanding. This understanding is commonly expressed as text; however, for the purposes of collaborative research, the tools of knowledge engineering/knowledge representation look more appropriate. The problem with them is that, to the present day, they are developed largely for the tasks that imply fixed relations between things and their properties, termed here as static. However, collaborative research often deals with fields of knowledge that represent changing environments where these relations cannot be considered fixed, and the tools to capture scenarios of evolution (i.e. the dynamic tools of knowledge engineering) are far from that evolved as static ones, mainly due to the lack of strict logical or mathematical foundation for representation of dynamic knowledge. This chapter presents an attempt to formulate a unified grammar to encode the knowledge of changing environments in any field of science.

Building Collaborative Ontologies

The chapter describes the research performed within the KOMET (Knowledge and cOntent structuring via METhods of collaborative ontology design) project, which was aimed at developing a new paradigm for knowledge structuring. By knowledge structure, the authors define the main domain concepts and relations between them in a form of graph, map, or diagram. The approach considers the specifics of individual cognitive style. Two stages of research have been completed: research into correlations between the expert's individual cognitive style and the peculiarities of expert's subject domain ontology development; and study of correlations between the expert's individual cognitive style and the group ontology design (including the design performed in groups consisting of experts either of similar or of different cognitive styles). The results of this work can be applied to organizing collaborative ontology design (especially for research and learning purposes), data structuring, and other group analytical work. Implications for practice are briefly delineated.

Collaborative Seabed-Habitat Mapping

This chapter discusses the uncertainties associated with sediment data, which are a commonly neglected obstacle in collaborative seabed-habitat mapping, complicating harmonization. Standardization of these data, although an important prerequisite in the harmonization of surrogate-based habitat maps, is not enough to achieve full map uniformity. Through time and between research institutes, data have been acquired, described, analyzed, and classified using a range of methods and protocols. The effects of differing error margins and indicative meanings remain hidden for most end users in environmental science and policy. The interpolation required to generate full-coverage data products from sedimentological point data creates additional uncertainty. Finally, small-scale habitat heterogeneity not captured by even the densest sampling places limits on the usability of sediment-based surrogates as well. Despite these limitations, there is much room for improvement when it comes to using surrogates in habitat mapping. Multiple visualizations generated from merged digital sediment datasets with flexible querying protocols are especially promising.

International Funding and Collaboration in Sea Level Rise Research

International collaboration and research funding in Sea Level Rise (SLR) research are investigated in this chapter. SLR can be taken as a paradigmatic research area to study the international scientific collaboration and research funding efforts because it is affecting the whole planet and is an interdisciplinary research area involving disciplines belonging to the geosciences but also the life sciences, technology sciences, and social sciences. The aim of the chapter is to identify the main stakeholders in the topic, institutions, and countries; analyze overlapping efforts; identify possible research gaps; and to study the role played by the funding agencies. Bibliometrics and a social network analysis approach are applied. Co-occurrence networks of keywords, affiliations, and funding agencies among scientific papers in Thomson Reuters' Web of Science Core Collection in the SLR topic are analyzed. Conclusions show that international scientific collaboration is common in SLR, but international co-financing is less frequent.

Examining Trust in Collaborative Research Networks

Ian McHarg's “The Theory of Creative Fitting” describes the collaborative integration of data into knowledge products for use in ecological architecture developments. In McHarg's system, the provenance of data layers and trust in their creators are vital to the creation of knowledge, ideas recently described as being “urgent and relevant.” This chapter begins with these ideas and explores provenance propagation and data publication. Provenance propagation has been a topic under discussion by the World Wide Web Consortium, while data publication has been a focus of the global marine science community. From these projects, the issue of uniquely identifying individuals in a distributed, collaborative network has emerged. Possible implications of this problem are discussed, as are technical solutions to the problem. The principles described within this chapter are illustrated by examples of uncertainty propagation in chained Web Processing Service networks and data publication activities at the British Oceanographic Data Centre.

Relationship between Senior and Junior Researcher

The professional development of a young researcher is mainly influenced by the organizational culture and the relationship with academic colleagues, especially mentors. This chapter presents the results of a qualitative study conducted on a sample of 16 researchers employed in three Slovenian public universities. The study examines the senior-junior researcher relationship, as the relationship between mentor and mentee, the nature of their cooperation, and how new knowledge is generated and transmitted. In-depth semi-structured interviews and content analysis for structuring qualitative data was used. The results indicate that the professional development of junior researchers is based mostly on their independent work where the mentor guidance is only occasional. Despite the development of information and communication technology, and in particular the Social Web tools, the mentorship in the framework of higher education institutions is still based on a face-to-face relationship.

Reconciling Knowledge and Collaborative E-Research

The aim of this chapter is to analyze the mechanisms and the philosophical background behind collaborative e-research in the perspective of defining simple and useful models that can be used in developing Web-based tools to support such activities. In its simplest form, collaboration refers to the interaction between humans. This is problematic, as the interaction between the subject and the outer world is always uncertain. To address this issue, a framework is proposed here, where metaphysics and epistemology are confronted, clearing up concepts as objectivity, subjectivity, opinions, or facts. The limits of “knowing,” of being aware of the knowledge we have, and of the possible transmission of knowledge are highlighted through comparison of science and other domains. A new vision becomes urgent and can be addressed through a “deliteralization” of knowledge grounded on “representation” since this is the projection of knowledge and the source of cultures.

Persistence of Knowledge across Layered Architectures

In this chapter, a model demonstrating methods for integration of semantic technologies within observational data services is described. Implementation of the model captures knowledge about data provenance where it is best understood and also enables its persistence across architectural layers through the use of standards-based technologies. Domain experts can build upon the semantic layer to create meaningful ontologies. Brokering services can utilize the ontologies for automated mediation of terms and translation between standards-based technologies. Research communities will be enabled to operate within their own framework, utilizing their familiar, specialized terminology and tools. The role of communities of practice is explored relating to knowledge management across layered architectures. Implementation of semantic technologies within Web-based data and brokering services will minimize the operational barriers to data discovery and access and provide mechanisms that enable the formation of collaborative environments that will facilitate repeatable, well-documented research.

Beyond Learning

The chapter analyzes the theme of collaboration in scientific research through Web 2.0 IT tools and a constructivist approach to knowledge, learning, and e-learning. It analyzes, in particular, the case of Sulcis CCS Summer School. Organized by ENEA, Sotacarbo, and the University of Cagliari, the school provided information and materials on technological aspects of Carbon Capture and Storage (CCS). This work might become the model for a new approach to education and research thanks to collaborative learning using the LMS Moodle. In this case study, the construction of knowledge moves from a teacher-centered model to one based on a community of practice. This model is naturally a “prototype,” an experiment in progress, that needs to be refined through further experiences.

Maps, Graphs, and Annotations as Boundary Objects in Knowledge Networks, Distributed Cognition, and Collaborative E-Research

Scientific communities tend to speciate in tribes that evolve their culture so that after some time they do not have the same understanding of the same terms or concepts. Tacit knowledge, that is the knowledge that cannot be expressed or formalized, complicates this even more. Since we cannot fully know what a concept refers to, we would have limitations in developing IT systems to support collaborative and distributed cognition activities and knowledge networks trying to map knowledge between paradigms. To address this, the authors propose to switch to another perspective where knowledge is kept implicit and the referential communication function (iconic signification) is exploited instead. In this perspective, they develop a specific virtual research environment named COLLA-ANT, which, albeit being still a prototype and needing more use cases, has proved successful in addressing the above-mentioned issues.