2,169 research outputs found

    HEALTH GeoJunction: place-time-concept browsing of health publications

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    <p>Abstract</p> <p>Background</p> <p>The volume of health science publications is escalating rapidly. Thus, keeping up with developments is becoming harder as is the task of finding important cross-domain connections. When geographic location is a relevant component of research reported in publications, these tasks are more difficult because standard search and indexing facilities have limited or no ability to identify geographic foci in documents. This paper introduces <it><smcaps>HEALTH</smcaps> GeoJunction</it>, a web application that supports researchers in the task of quickly finding scientific publications that are relevant geographically and temporally as well as thematically.</p> <p>Results</p> <p><it><smcaps>HEALTH</smcaps> GeoJunction </it>is a geovisual analytics-enabled web application providing: (a) web services using computational reasoning methods to extract place-time-concept information from bibliographic data for documents and (b) visually-enabled place-time-concept query, filtering, and contextualizing tools that apply to both the documents and their extracted content. This paper focuses specifically on strategies for visually-enabled, iterative, facet-like, place-time-concept filtering that allows analysts to quickly drill down to scientific findings of interest in PubMed abstracts and to explore relations among abstracts and extracted concepts in place and time. The approach enables analysts to: find publications without knowing all relevant query parameters, recognize unanticipated geographic relations within and among documents in multiple health domains, identify the thematic emphasis of research targeting particular places, notice changes in concepts over time, and notice changes in places where concepts are emphasized.</p> <p>Conclusions</p> <p>PubMed is a database of over 19 million biomedical abstracts and citations maintained by the National Center for Biotechnology Information; achieving quick filtering is an important contribution due to the database size. Including geography in filters is important due to rapidly escalating attention to geographic factors in public health. The implementation of mechanisms for iterative place-time-concept filtering makes it possible to narrow searches efficiently and quickly from thousands of documents to a small subset that meet place-time-concept constraints. Support for a <it>more-like-this </it>query creates the potential to identify unexpected connections across diverse areas of research. Multi-view visualization methods support understanding of the place, time, and concept components of document collections and enable comparison of filtered query results to the full set of publications.</p

    Collaborative tagging : folksonomy, metadata, visualization, e-learning, thesis

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    Collaborative tagging is a simple and effective method for organizing and sharing web resources using human created metadata. It has arisen out of the need for an efficient method of personal organization, as the number of digital resources in everyday lives increases. While tagging has become a proven organization scheme through its popularity and widespread use on the Web, little is known about its implications and how it may effectively be applied in different situations. This is due to the fact that tagging has evolved through several iterations of use on social software websites, rather than through a scientific or an engineering design process. The research presented in this thesis, through investigations in the domain of e-learning, seeks to understand more about the scientific nature of collaborative tagging through a number of human subject studies. While broad in scope, touching on issues in human computer interaction, knowledge representation, Web system architecture, e-learning, metadata, and information visualization, this thesis focuses on how collaborative tagging can supplement the growing metadata requirements of e-learning. I conclude by looking at how the findings may be used in future research, through using information based in the emergent social networks of social software, to automatically adapt to the needs of individual users

    Visualization for Recommendation Explainability: A Survey and New Perspectives

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    Providing system-generated explanations for recommendations represents an important step towards transparent and trustworthy recommender systems. Explainable recommender systems provide a human-understandable rationale for their outputs. Over the last two decades, explainable recommendation has attracted much attention in the recommender systems research community. This paper aims to provide a comprehensive review of research efforts on visual explanation in recommender systems. More concretely, we systematically review the literature on explanations in recommender systems based on four dimensions, namely explanation goal, explanation scope, explanation style, and explanation format. Recognizing the importance of visualization, we approach the recommender system literature from the angle of explanatory visualizations, that is using visualizations as a display style of explanation. As a result, we derive a set of guidelines that might be constructive for designing explanatory visualizations in recommender systems and identify perspectives for future work in this field. The aim of this review is to help recommendation researchers and practitioners better understand the potential of visually explainable recommendation research and to support them in the systematic design of visual explanations in current and future recommender systems.Comment: Updated version Nov. 2023, 36 page

    Casual Information Visualization on Exploring Spatiotemporal Data

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    The goal of this thesis is to study how the diverse data on the Web which are familiar to everyone can be visualized, and with a special consideration on their spatial and temporal information. We introduce novel approaches and visualization techniques dealing with different types of data contents: interactively browsing large amount of tags linking with geospace and time, navigating and locating spatiotemporal photos or videos in collections, and especially, providing visual supports for the exploration of diverse Web contents on arbitrary webpages in terms of augmented Web browsing

    Using online communications technologies and communities of practice to strengthen researcher-decision maker partnerships

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    Successful knowledge transfer is all about relationships. As anyone who has conducted research with non-academic partners knows, it takes a considerable amount of time and effort for these relationships to be fruitful. The great benefit of placing this work within the context of a community of practice is that it gives researchers and decision makers a structure within which to interact. This study explored ways in which a community of practice framework can be used to develop and nurture relationships between researchers and decision makers. Further, it investigated how these communities of practice can be supported by online communications technologies. Its major contribution is the development, testing and refinement of a checklist of six ways that researchers can connect with decision makers in communities of practice, both in person and online. This checklist provides concrete, practical suggestions on how to develop an effective community of practice. Items in the checklist are based on both the academic literature on knowledge transfer and communities of practice, and the author’s experience as part of an academic research unit focused on conducting collaborative research with community and government partners. Each item in the checklist was validated through interviews with members of two communities of practice. While the initial checklist had five items, a sixth was added following analysis of the interviews. This checklist is generalizable, in that it can help guide any kind of community of practice, not just those in which members work on early childhood development issues, nor those communities in which researchers and decision makers interact. It is a valuable contribution to knowledge transfer methods at a time when both interest levels and efforts to improve knowledge implementation are widespread. The final checklist reads as follows: A community of practice should: 1. provide opportunities for regular interaction between community members; 2. allow members to participate at varying levels that can change over time; 3. provide both public and private spaces for interaction; 4. document its goals, activities and outcomes, in order to develop a knowledge repository; 5. identify and document the value of the community itself; and 6. enlist the guidance of a technology champion in order to use online communications technologies effectively
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