You can't always sketch what you want: Understanding Sensemaking in Visual Query Systems

Visual query systems (VQSs) empower users to interactively search for line charts with desired visual patterns, typically specified using intuitive sketch-based interfaces. Despite decades of past work on VQSs, these efforts have not translated to adoption in practice, possibly because VQSs are largely evaluated in unrealistic lab-based settings. To remedy this gap in adoption, we collaborated with experts from three diverse domains---astronomy, genetics, and material science---via a year-long user-centered design process to develop a VQS that supports their workflow and analytical needs, and evaluate how VQSs can be used in practice. Our study results reveal that ad-hoc sketch-only querying is not as commonly used as prior work suggests, since analysts are often unable to precisely express their patterns of interest. In addition, we characterize three essential sensemaking processes supported by our enhanced VQS. We discover that participants employ all three processes, but in different proportions, depending on the analytical needs in each domain. Our findings suggest that all three sensemaking processes must be integrated in order to make future VQSs useful for a wide range of analytical inquiries.Comment: Accepted for presentation at IEEE VAST 2019, to be held October 20-25 in Vancouver, Canada. Paper will also be published in a special issue of IEEE Transactions on Visualization and Computer Graphics (TVCG) IEEE VIS (InfoVis/VAST/SciVis) 2019 ACM 2012 CCS - Human-centered computing, Visualization, Visualization design and evaluation method

Design Fiction Diegetic Prototyping: A Research Framework for Visualizing Service Innovations

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Purpose: This paper presents a design fiction diegetic prototyping methodology and research framework for investigating service innovations that reflect future uses of new and emerging technologies. Design/methodology/approach: Drawing on speculative fiction, we propose a methodology that positions service innovations within a six-stage research development framework. We begin by reviewing and critiquing designerly approaches that have traditionally been associated with service innovations and futures literature. In presenting our framework, we provide an example of its application to the Internet of Things (IoT), illustrating the central tenets proposed and key issues identified. Findings: The research framework advances a methodology for visualizing future experiential service innovations, considering how realism may be integrated into a designerly approach. Research limitations/implications: Design fiction diegetic prototyping enables researchers to express a range of ‘what if’ or ‘what can it be’ research questions within service innovation contexts. However, the process encompasses degrees of subjectivity and relies on knowledge, judgment and projection. Practical implications: The paper presents an approach to devising future service scenarios incorporating new and emergent technologies in service contexts. The proposed framework may be used as part of a range of research designs, including qualitative, quantitative and mixed method investigations. Originality: Operationalizing an approach that generates and visualizes service futures from an experiential perspective contributes to the advancement of techniques that enables the exploration of new possibilities for service innovation research

National Center for Biomedical Ontology: Advancing biomedicine through structured organization of scientific knowledge

The National Center for Biomedical Ontology is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists, funded by the National Institutes of Health (NIH) Roadmap, to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create new software tools so that scientists can use ontologies to annotate and analyze biomedical data, (3) to provide a national resource for the ongoing evaluation, integration, and evolution of biomedical ontologies and associated tools and theories in the context of driving biomedical projects (DBPs), and (4) to disseminate the tools and resources of the Center and to identify, evaluate, and communicate best practices of ontology development to the biomedical community. Through the research activities within the Center, collaborations with the DBPs, and interactions with the biomedical community, our goal is to help scientists to work more effectively in the e-science paradigm, enhancing experiment design, experiment execution, data analysis, information synthesis, hypothesis generation and testing, and understand human disease

Detection of Communities within the Multibody System Dynamics Network and Analysis of Their Relations

Multibody system dynamics is already a well developed branch of theoretical, computational and applied mechanics. Thousands of documents can be found in any of the well-known scientific databases. In this work it is demonstrated that multibody system dynamics is built of many thematic communities. Using the Elsevier’s abstract and citation database SCOPUS, a massive amount of data is collected and analyzed with the use of the open source visualization tool Gephi. The information is represented as a large set of nodes with connections to study their graphical distribution and explore geometry and symmetries. A randomized radial symmetry is found in the graphical representation of the collected information. Furthermore, the concept of modularity is used to demonstrate that community structures are present in the field of multibody system dynamics. In particular, twenty-four different thematic communities have been identified. The scientific production of each community is analyzed, which allows to predict its growing rate in the next years. The journals and conference proceedings mainly used by the authors belonging to the community as well as the cooperation between them by country are also analyzed

Exploring scholarly data with Rexplore.

Despite the large number and variety of tools and services available today for exploring scholarly data, current support is still very limited in the context of sensemaking tasks, which go beyond standard search and ranking of authors and publications, and focus instead on i) understanding the dynamics of research areas, ii) relating authors ‘semantically’ (e.g., in terms of common interests or shared academic trajectories), or iii) performing fine-grained academic expert search along multiple dimensions. To address this gap we have developed a novel tool, Rexplore, which integrates statistical analysis, semantic technologies, and visual analytics to provide effective support for exploring and making sense of scholarly data. Here, we describe the main innovative elements of the tool and we present the results from a task-centric empirical evaluation, which shows that Rexplore is highly effective at providing support for the aforementioned sensemaking tasks. In addition, these results are robust both with respect to the background of the users (i.e., expert analysts vs. ‘ordinary’ users) and also with respect to whether the tasks are selected by the evaluators or proposed by the users themselves

Towards a Cloud-Based Service for Maintaining and Analyzing Data About Scientific Events

We propose the new cloud-based service OpenResearch for managing and analyzing data about scientific events such as conferences and workshops in a persistent and reliable way. This includes data about scientific articles, participants, acceptance rates, submission numbers, impact values as well as organizational details such as program committees, chairs, fees and sponsors. OpenResearch is a centralized repository for scientific events and supports researchers in collecting, organizing, sharing and disseminating information about scientific events in a structured way. An additional feature currently under development is the possibility to archive web pages along with the extracted semantic data in order to lift the burden of maintaining new and old conference web sites from public research institutions. However, the main advantage is that this cloud-based repository enables a comprehensive analysis of conference data. Based on extracted semantic data, it is possible to determine quality estimations, scientific communities, research trends as well the development of acceptance rates, fees, and number of participants in a continuous way complemented by projections into the future. Furthermore, data about research articles can be systematically explored using a content-based analysis as well as citation linkage. All data maintained in this crowd-sourcing platform is made freely available through an open SPARQL endpoint, which allows for analytical queries in a flexible and user-defined way.Comment: A completed version of this paper had been accepted in SAVE-SD workshop 2017 at WWW conferenc

Analysis in Web 3D Environments of Thematic Research Networks on Immersive Learning through Variation of Clustering Criteria

Este projeto tem como objetivo desenvolver uma ferramenta de visualização 3D baseada na web que proporciona uma compreensão global do campo de Aprendizagem Imersiva. As redes temáti- cas são uma abordagem bem estabelecida para lidar com esses desafios. Portanto, foi realizada uma revisão sistemática da literatura para extrair métodos e critérios de clustering em redes temáticas. A metodologia empregada neste estudo é a pesquisa de Design Science Research, que envolveu o desenvolvimento e a avaliação iterativos da ferramenta de visualização. Entre- vistas com especialistas foram realizadas para identificar os requisitos, e métodos rigorosos, in- cluindo gravação, análise e transcrição das entrevistas, foram aplicados para verificar a relevância da pesquisa. A ferramenta utiliza uma abordagem de visualização de node-link para visualizar estratégias, práticas e artigos associados à aprendizagem imersiva. Além disso, oferece uma var- iedade de funcionalidades de filtragem, permitindo que os usuários filtrem por estratégias, práticas, autores, instituições e outros. Além disso, a ferramenta incorpora várias funcionalidades de clus- tering, como detecção de comunidades usando o algoritmo de Louvain, com variação de critérios de clustering , como associação de temas e de artigos, citação de artigos, co-citação e outros. Os usuários também podem controlar a estrutura da rede modificando o tamanho das clustering, o número e as cores das comunidades. A ferramenta apresenta métodos exploratórios de redes temáticas para navegar no ambiente. Ao combinar redes temáticas com capacidades de clustering e filtragem, essa ferramenta tem como objetivo fornecer uma compreensão global do campo cien- tífico. Sua integração única de tecnologias Web e 3D, juntamente com métodos exploratórios, a diferencia das ferramentas de visualização existentes. Os poderosos algoritmos de clustering da ferramenta, oferecendo critérios diversos para entender as relações conceituais, têm o potencial de ter um impacto significativo na comunidade de aprendizagem imersiva. Ela é projetada para servir como um artefato inovador que aprimora as capacidades analíticas de pesquisadores, educadores e estudantes na área.This project aims to develop a Web-based 3D visualization tool that provides a global understanding of the field of Immersive Learning. Thematic networks are a well-established approach for addressing such challenges. Therefore, a systematic literature review was conducted to extract clustering methods and criteria in thematic networks. The methodology employed in this study is Design Science research, which involved iterative development and evaluation of the visualization tool. Expert interviews were conducted to identify requirements, and rigorous methods, including recording, analyzing, and transcribing interviews, were applied to ascertain the research's relevance. The tool utilizes a node-link visualization approach to represent immersive learning strategies, practices, and associated papers. Additionally, it offers a range of filtering functionali- ties, allowing users to filter by strategies, practices, authors, institutions, and more. Furthermore, the tool incorporates various clustering functionalities, such as community detection using the Louvain Algorithm, with variable clustering criteria such as theme and paper association, paper citation, co-citation, and others. Users can also control the network's structure by modifying clus- ter size, number, and community colors. The tool features thematic networks exploratory methods for navigating the environment. By combining thematic networks with clustering and filtering capabilities, this tool aims to provide a global understanding of the scientific field. Its unique integration of Web and 3D technologies, along with exploratory methods, distinguishes it from existing visualization tools. The tool's powerful clustering algorithms, offering diverse criteria for understanding concept relationships, have the potential to make a significant impact in the immersive learning community. It is designed to serve as an innovative artifact that enhances the analytical capabilities of researchers, educators, and students in the field

Exploring Large Document Repositories with RDF Technology: The DOPE Project

This thesaurus-based search system uses automatic indexing, RDF-based querying, and concept-based visualization of results to support exploration of large online document repositories