Understanding research dynamics

Rexplore leverages novel solutions in data mining, semantic technologies and visual analytics, and provides an innovative environment for exploring and making sense of scholarly data. Rexplore allows users: 1) to detect and make sense of important trends in research; 2) to identify a variety of interesting relations between researchers, beyond the standard co-authorship relations provided by most other systems; 3) to perform fine-grained expert search with respect to detailed multi-dimensional parameters; 4) to detect and characterize the dynamics of interesting communities of researchers, identified on the basis of shared research interests and scientific trajectories; 5) to analyse research performance at different levels of abstraction, including individual researchers, organizations, countries, and research communities

The Evidence Hub: harnessing the collective intelligence of communities to build evidence-based knowledge

Conventional document and discussion websites provide users with no help in assessing the quality or quantity of evidence behind any given idea. Besides, the very meaning of what evidence is may not be unequivocally defined within a community, and may require deep understanding, common ground and debate. An Evidence Hub is a tool to pool the community collective intelligence on what is evidence for an idea. It provides an infrastructure for debating and building evidence-based knowledge and practice. An Evidence Hub is best thought of as a filter onto other websites — a map that distills the most important issues, ideas and evidence from the noise by making clear why ideas and web resources may be worth further investigation. This paper describes the Evidence Hub concept and rationale, the breath of user engagement and the evolution of specific features, derived from our work with different community groups in the healthcare and educational sector

Ritual performances and collective intelligence: theoretical frameworks for analyising activity patterns in Cloudworks

This paper provides an overview of emerging activity patterns on Cloudworks, a specialised site for sharing and debating ideas as well as resources on teaching, learning and scholarship in education. It provides an overview of activities such as 'flash debates', 'blended workshops' and 'open reviews' and seeks to situate dialogic interchanges and structures of involvement within the following theoretical frameworks: a) Goffman's notions of 'face-work' and 'ritual performance�; and b) and secondly, notions of collective intelligence. The paper argues that these perspectives can offer a unique contribution to the study and analysis of sociality (Bouman et al, 2007) bounded in the context of technologically mediated networked learning, with wider implications for understanding matters of participation, self-representation, reflection and expansion in education

A Cultural Heritage Forum Celebrating Technological Innovation at Station X

We aim to encourage and support public participation in heritage through the development of Cultural Heritage Forums, a kind of cultural web portal that enables active participation of communities of interest in a way that complements rather than replaces visits to physical cultural institutions. The cultural heritage forum described here (Station X) is concerned with promoting an understanding of technology innovation in the areas of computing and cryptography. We propose a number of scenarios concerning how the forum can be designed, drawing on our earlier work in using knowledge modelling and text analysis to support the exploration of digital resources

From open content to open thinking

So far Open Educational Resources (OER) research has focused on the objective to 'open' education by making accessible free educational resources to the world. In the latest years the movement has matured, and a growing amount of OER have been made available by universities, researchers and scholars through several portals. Nonetheless, the level of adoption of OERs into common teaching practices remains quite low. In this paper we suggest that one of the main barriers to OER's adoption is the lack of 'opening up' to people's thinking around OERs and we propose Cohere, a tool which aims at making this thinking visible and exportable in ways that support the emergence of 'collective intelligence' around OERs research. Accessing Collective Intelligence (CI) around OERs is presented as a medium to know and understand what people think, how people design and use OERs thus increasing the easy of re-use of OER in learning and research practices

Forecasting the Spreading of Technologies in Research Communities

Technologies such as algorithms, applications and formats are an important part of the knowledge produced and reused in the research process. Typically, a technology is expected to originate in the context of a research area and then spread and contribute to several other fields. For example, Semantic Web technologies have been successfully adopted by a variety of fields, e.g., Information Retrieval, Human Computer Interaction, Biology, and many others. Unfortunately, the spreading of technologies across research areas may be a slow and inefficient process, since it is easy for researchers to be unaware of potentially relevant solutions produced by other research communities. In this paper, we hypothesise that it is possible to learn typical technology propagation patterns from historical data and to exploit this knowledge i) to anticipate where a technology may be adopted next and ii) to alert relevant stakeholders about emerging and relevant technologies in other fields. To do so, we propose the Technology-Topic Framework, a novel approach which uses a semantically enhanced technology-topic model to forecast the propagation of technologies to research areas. A formal evaluation of the approach on a set of technologies in the Semantic Web and Artificial Intelligence areas has produced excellent results, confirming the validity of our solution

Rexplore: unveiling the dynamics of scholarly data

Rexplore is a novel system that integrates semantic technologies, data mining techniques, and visual analytics to provide an innovative environment for making sense of scholarly data. Its functionalities include: i) a variety of views to make sense of important trends in research; ii) a novel semantic approach for characterising research topics; iii) a very fine-grained expert search with detailed multi-dimensional parameters; iv) an innovative graph view to relate a variety of academic entities; iv) the ability to detect and explore the main communities within a research topic; v) the ability to analyse research performance at different levels of abstraction, including individual researchers, organizations, countries, and research communities

Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page