Visualizing Research Digital Libraries with Open Standards

Large-scale research Digital Libraries (DLs) contain a large array of potentially useful metadata. Yet, many popular DLs do not provide a convenient way to navigate the metadata or to visualize classification schema in the user session. For example, in the broad world of Management Information Systems (MIS) research, a high-level overview of MIS topics and their inter-relationships would be useful to navigate a MIS DL before zooming in on a specific article. To address this obstacle, this paper describes a prototype, the Technical Report Visualizer System (TRV), which uses a wide variety of open standards to show DL classification metadata in the navigation interface. The system captures MIS article metadata from the Open Archives Initiative (OAI) compliant arXiv e-Print archive at Cornell University. The OAI Protocol for Metadata Harvesting (OAI-PMH) is used to collect the topic metadata; the articles\u27 Association for Computing Machinery\u27s (ACM) Computing Classification System codes. We display the topic metadata in a Java hyperbolic tree and make use of XML conceptual product and implementation product standards and specifications, such as the Dublin Core and BiblioML bibliographic metadata sets, XML Topic Maps, Xalan and Xerces, to link user navigation activity to the abstracts and full text contents of the articles. We discuss the flexibility and convenience of XML standards and link this effort to related digital library visualization approaches. Keywords

Supporting Methodology Transfer in Visualization Research with Literature-Based Discovery and Visual Text Analytics

[ES] La creciente especialización de la ciencia está motivando la rápida fragmentación de disciplinas bien establecidas en comunidades interdisciplinares. Esta descom- posición se puede observar en un tipo de investigación en visualización conocida como investigación de visualización dirigida por el problema. En ella, equipos de expertos en visualización y un dominio concreto, colaboran en un área específica de conocimiento como pueden ser las humanidades digitales, la bioinformática, la seguridad informática o las ciencias del deporte. Esta tesis propone una serie de métodos inspirados en avances recientes en el análisis automático de textos y la rep- resentación del conocimiento para promover la adecuada comunicación y transferen- cia de conocimiento entre estas comunidades. Los métodos obtenidos se combinaron en una interfaz de análisis visual de textos orientada al descubrimiento científico, GlassViz, que fue diseñada con estos objetivos en mente. La herramienta se probó por primera vez en el dominio de las humanidades digitales para explorar un corpus masivo de artículos de visualización de propósito general. GlassViz fue adaptada en un estudio posterior para que soportase diferentes fuentes de datos representativas de estas comunidades, mostrando evidencia de que el enfoque propuesto también es una alternativa válida para abordar el problema de la fragmentación en la investigación en visualización

Computational Tradespace Exploration, Analysis, and Decision-Making: A Proposed Framework for Organizational Self-Assessment

The ability to assess technical feasibility, project risk, technical readiness, and realistic performance expectations in early-phase conceptual design is a challenging mission-critical task for large procurement projects. At present, there is not a well-defined framework for evaluating current practices of organizations performing computational trade studies. One such organization is the US Army Ground Vehicle Systems Center (GVSC). When defining requirements and priorities for the next-generation autonomy-enabled ground vehicle system, GVSC is faced with the challenge of an increasingly complex programmatic tradespace due to emerging complexities of ground vehicle systems. This thesis aims to document and evaluate tradespace processes, methods, and tools within GVSC. A systematic review of the literature was conducted to investigate existing gaps, limitations, and potential growth opportunities related to tradespace activities reflecting the greater body of knowledge observed in the literature. Following this review, an interview-based study was developed through which a series of interviews with GVSC personnel was conducted and subsequently benchmarked against the baseline established in the literature. In addition to characterizing the current practices of tradespace exploration and analysis within GVSC, the analysis of the collected interview data revealed current capability gaps, areas of excellence, and potential avenues for improvement within GVSC. Through this thesis, other organizations can perform similar self-assessments to improve internal capabilities with respect to tradespace studies

Visualizing the knowledge domain of multimodal discourse analysis (2009-2019): A bibliometric review

Different from traditional discourse analysis, multimodal discourse analysis (MDA), a systematic analysis of different semiotic modes, utilizing language, images, sounds in a discourse, emphasizes the coordination of both dynamic and static semiotic resources. This study presents the status quo and development trend of the research field through an objective, systematic, and comprehensive review of relevant publications available from the Web of Science Core Collection. Analysis techniques including a descriptive statistical method and a bibliometric method are used. The study quantitatively analyzes the publications in terms of general characteristics, geographical distribution, high-cited representatives, and topic discovery and distribution to illustrate the development and trend of MDA. The research findings are as follows: (1) In the past 10 years or so, international MDA research has presented a significant growth trend, with flourishing research output, interest and diversification of presented subjects; (2) New topics are constantly emerging, with research topics mainly focusing on the development of visual grammar, gesture, digital technologies, conference presentations, metonymy and metaphor, etc.; (3) Research focuses mainly on multimodality, semiotics, conversation analysis, critical discourse analysis etc.; (4) The article also listed a series of important and highly influential literature, countries, journals and authors on MDA during different periods. It is hoped that this paper can provide a reference for the further study of MDA

Knowledge Mapping Analysis of Rural Landscape Using CiteSpace

This study visualizes and quantifies extant publications of rural landscape research (RLR) inWeb of Science using CiteSpace for a wide range of research topics, from a multi-angle analysis of the overall research profile, while providing a method and approach for quantitative analysis of massive literature data. First, it presents the number of papers published, subject distribution, author network, the fundamental condition of countries, and research organizations involved in RLR through network analysis. Second, it identifies the high-frequency and high betweenness-centrality values of the basic research content of RLR through keyword co-occurrence analysis and keyword time zones. Finally, it identifies research fronts and trending topics of RLR in the decade from 2009 to 2018 by using co-citation clustering, and noun-term burst detection. The results show that basic research content involves protection, management, biodiversity, and land use. Five clearer research frontier pathways and top 20 research trending topics are extracted to show diversified research branch development. All this provides the reader with a general preliminary grasp of RLR, showing that cooperation and analysis involving multiple disciplines, specialties, and angles will become a dominant trend in the field

Scientometric Analysis of Technology & Innovation Management Literature

The management of technology and innovation has become an attractive and promising field within the management discipline. Therefore, much insight can be gained by reviewing the Technology & Innovation Management (TIM) research in leading TIM journals to identify and classify the key TIM issues by meta-categories and to identify the current trends. Based on a comprehensive scientometric analysis of 5,591 articles in 10 leading TIM specialty journals from 2005 to 2014, this research revealed several enlightening findings. First, the United States is the major producer of TIM research literature, and the greatest number of papers was published in Research Policy. Among the researchers in the field, M. Song is the most prolific author. Second, the TIM field often plays a bridging role in which the integration of ideas can be grouped into 10 clusters: innovation and firms, new product development (NPD) and marketing strategy, project management, patenting and industry, emerging technologies, science policy, social networks, system modeling and development, business strategy, and knowledge transfer. Third, the connectivity among these terms is highly clustered and a network-based perspective revealed that six new topic clusters are emerging: NPD, technology marketing, patents and intellectual property rights, university-industry cooperation, technology forecasting and roadmapping, and green innovation. Finally, chronological trend analysis of key terms indicates a change in emphasis in TIM research from information systems/technologies to the energy sector and green innovation. The results of the study improve our understanding of the structure of TIM as a field of practice and an academic discipline. This insight provides direction regarding future TIM research opportunities

iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources

The advancement of the computational biology field hinges on progress in three fundamental directions – the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources–data, software tools and web-services. The iTools design, implementation and resource meta - data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu

Temporal and geographical research trends of antimicrobial resistance in wildlife - A bibliometric analysis

Antimicrobial resistance (AMR) is a complex and global problem. Despite the growing literature on AMR in the medical and veterinary settings, there is still a lack of knowledge on the wildlife compartment. The main aim of this study was to report the global trends in AMR research in wildlife, through a bibliometric study of articles found in the Web of Science database. Search terms were "ANTIMICROBIAL" OR "ANTIBIOTIC" AND "RESISTANT" OR "RESISTANCE" and "WILDLIFE" "MAMMAL" "BIRD" "REPTILE" "FERAL" "FREE RANGE". A total of 219 articles were obtained, published between 1979 and 2019. A rising interest in the last decades towards this topic becomes evident. During this period, the scientific literature was distributed among several scientific areas, however it became more multidisciplinary in the last years, focusing on the "One Health" paradigm. There was a geographical bias in the research outputs: most published documents were from the United States, followed by Spain, Portugal and the United Kingdom. The most productive institutions in terms of publication number were located in Portugal and Spain. An important level of international collaboration was identified. An analysis of the main keywords showed an overall dominance of "AMR", "E. coli", "genes", "prevalence", "bacteria", "Salmonella spp." and "wild birds". This is the first study providing a global overview of the spatial and temporal trends of research related to AMR in wildlife. Given the growth tendency over the last years, it is envisaged that scientific production will expand in the future. In addition to offering a broad view of the existing research trends, this study identifies research gaps both in terms of geographical incidence and in relation to unexplored subtopics. Unearthing scientific areas that should be explored in the future is key to designing new strategic research agendas in AMR research in wildlife and to inform funding programs.info:eu-repo/semantics/publishedVersio

Social Network and Content Analysis of the North American Carbon Program as a Scientific Community of Practice

The North American Carbon Program (NACP) was formed to further the scientific understanding of sources, sinks, and stocks of carbon in Earth's environment. Carbon cycle science integrates multidisciplinary research, providing decision-support information for managing climate and carbon-related change across multiple sectors of society. This investigation uses the conceptual framework of com-munities of practice (CoP) to explore the role that the NACP has played in connecting researchers into a carbon cycle knowledge network, and in enabling them to conduct physical science that includes ideas from social science. A CoP describes the communities formed when people consistently engage in shared communication and activities toward a common passion or learning goal. We apply the CoP model by using keyword analysis of abstracts from scientific publications to analyze the research outputs of the NACP in terms of its knowledge domain. We also construct a co-authorship network from the publications of core NACP members, describe the structure and social pathways within the community. Results of the content analysis indicate that the NACP community of practice has substantially expanded its research on human and social impacts on the carbon cycle, contributing to a better understanding of how human and physical processes interact with one another. Results of the co-authorship social network analysis demonstrate that the NACP has formed a tightly connected community with many social pathways through which knowledge may flow, and that it has also expanded its network of institutions involved in carbon cycle research over the past seven years