508,657 research outputs found

    From principles to action: Applying the National Research Council's principles for effective decision support to the Federal Emergency Management Agency's watch office

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    AbstractThe National Research Council (NRC) proposed six principles for effective decision support in its 2009 report Informing Decisions in a Changing Climate. We structured a collaborative project between the Federal Emergency Management Agency Region R9 (FEMA R9), the Western Region Headquarters of the National Weather Service (WR-NWS), and the Climate Assessment of the Southwest (CLIMAS) at the University of Arizona around the application of the NRC principles. The goal of the project was to provide FEMA R9's Watch Office with climate information scaled to their temporal and spatial interests to aid them in assessing the potential risk of flood disasters. We found that we needed specific strategies and activities in order to apply the principles effectively. By using a set of established collaborative research approaches we were better able to assess FEMA R9's information needs and WR-NWS's capacity to meet those needs. Despite our diligent planning of engagement strategies, we still encountered some barriers to transitioning our decision support tool from research to operations. This paper describes our methods for planning and executing a three-party collaborative effort to provide climate services, the decision support tool developed through this process, and the lessons we will take from this deliberate collaborative process to our future work and implications of the NRC principles for the broader field of climate services

    POSTER: Towards Collaboratively Supporting Decision Makers in Choosing Suitable Authentication Schemes

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    In spite of the the issues associated with them, text passwords are the predominant means of user authentication today. To foster the adoption of alternative authentication schemes, Renaud et al. (2014) proposed the ACCESS (Authentication ChoiCE Support System) framework. In prior work, we presented the first implementation of this abstract framework as a decision support system. In this work, we report on the current progress of expanding our prototype implementation into a collaborative authentication research platform. In addition to a decision support system, this platform also includes an interface to systematically access all the information in the knowledge base and collaborative features to facilitate the process of keeping the data for the decision support system current

    UX Challenges in GDSS : An Experience Report

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    In this paper we present a user experience report on a Group Decision Support System. The used system is a Collaborative framework called GRoUp Support (GRUS). The experience consists in three user tests conducted in three different countries. While the locations are different, all three tests were run in the same conditions: same facilitator and tested process. In order to support the end-users. we teach the system in two different ways: a presentation of the system, and a video demonstrating how to use it. The main feedback of this experience is that the teaching step for using Collaborative tools in mandatory. The experience was conducted in the context of decision-making in the agriculture domain.Laboratorio de Investigación y Formación en Informática Avanzad

    Multicriteria Decision Analysis and Group Decision-Making to Select Stand-Level Forest Management Models and Support Landscape-Level Collaborative Planning

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    Forest management planning is a challenge due to the diverse criteria that need to be considered in the underlying decision-making process. This challenge becomes more complex in joint collaborative management areas (ZIF) because the decision now may involve numerous actors with diverse interests, preferences, and goals. In this research, we present an approach to identifying and quantifying the most relevant criteria that actors consider in a forest management planning process in a ZIF context, including quantifying the performance of seven alternative stand-level forest management models (FMM). Specifically, we developed a combined multicriteria decision analysis and group decision-making process by (a) building a cognitive map with the actors to identify the criteria and sub-criteria; (b) structuring the decision tree; (c) structuring a questionnaire to elicit the importance of criteria and sub-criteria in a pairwise comparison process, and to evaluate the FMM alternatives; and (d) applying a Delphi survey to gather actors’ preferences. We report results from an application to a case study area, ZIF of Vale do Sousa, in North-Western Portugal. Actors assigned the highest importance to the criteria income (56.8% of all actors) and risks (21.6% of all actors) and the lowest to cultural services (27.0% of all actors). Actors agreed on their preferences for the sub-criteria of income (diversification of income sources), risks (wildfires) and cultural services (leisure and recreation activities). However, there was a poor agreement among actors on the subcriteria of the wood demand and biodiversity criteria. For 27.0% of all actors the FMM with the highest performance was the pedunculate oak and for 43.2% of all actors the eucalypt FMM was the least preferable alternative. The findings indicate that this approach can support ZIF managers in enhancing forest management planning by improving its utility for actors and facilitating its implementationinfo:eu-repo/semantics/publishedVersio

    Valuing the scholarship of integration and the scholarship of application in the academy for health sciences scholars: recommended methods

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    In the landmark 1990 publication Scholarship Reconsidered, Boyer challenged the 'teaching verses research debates' by advocating for the scholarship of discovery, teaching, integration, and application. The scholarship of discovery considers publications and research as the yardstick in the merit, promotion and tenure system the world over. But this narrow view of scholarship does not fully support the obligations of universities to serve global societies and to improve health and health equity. Mechanisms to report the scholarship of teaching have been developed and adopted by some universities. In this article, we contribute to the less developed areas of scholarship, i.e. integration and application. We firstly situate the scholarship of discovery, teaching, integration and application within the interprofessional and knowledge exchange debates. Second, we propose a means for health science scholars to report the process and outcomes of the scholarship of integration and application with other disciplines, decision-makers and communities. We conclude with recommendations for structural and process change in faculty merit, tenure, and promotion systems so that health science scholars with varied academic portfolios are valued and many forms of academic scholarship are sustained. It is vital academic institutions remain relevant in an era when the production of knowledge is increasingly recognized as a social collaborative activity

    Visualization Literacy and Decision-making in Healthcare

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    The ability of workers in the healthcare industry to analyze, interpret and communicate with health data is critical to decision-making and impacts both health and business outcomes. Optimal decision-making requires having real-time access to information that provides useful insights and that lends itself to collaborative decision-making. Data visualizations have the potential to facilitate decision-making in healthcare when presented as a dashboard. However, dashboards have shown varying results in both effectiveness and adoption. Data or graphical literacy challenges experienced by health team members could complicate strategic decision-making through an inability to correctly interpret or summarize the information presented in a dashboard. One assumption is that visualization literacy and its impact on how people process health data visualizations play a part in the effective interpretation of information to support decision-making. To determine the impact of visualization literacy on the process of decision-making in a healthcare setting, we first developed and deployed a dashboard designed to provide important information for decision-makers on a clinical trial management team. We engaged Project Managers and Medical Managers in the project as key decision-makers on the team. The dashboard was integrated into the normal workflow of a clinical trial management team and designated as the tool used in the workflow to report on the trial status within the organization. Next, we administered a series of assessments to the key decision-makers. The assessments were designed to evaluate numeracy, visualization literacy, and the impact of both on the decision-making ability of participants. Decision-making was assessed using a common workflow scenario supported by visualizations from the deployed dashboard. Additionally, we were interested in exploring indicators related to job satisfaction that was collected during the project period through a formal engagement survey. We performed a general linear model to assess the relationship between the assessments and decision-making. Results of our project show a significant and clear relationship between visualization literacy and decision-making ability and an insignificant relationship between numeracy and decision-making ability. Job satisfaction scores for the participant group obtained through the engagement survey suggest favorable results. However, areas of opportunity for improvement illuminated through the survey included better tools and additional resources to support the execution of tasks, a better workload balance, and improvements in collaboration across departments and functions. The results of this project contribute to the informatics discipline by demonstrating that information obtained from data visualizations produced through the aggregation of multiple sources of data can be effective decision-support tools if they are designed with user skills and abilities in mind. The results of the project suggest an opportunity to develop more useful and usable tools to improve job satisfaction as well as organizational business objectives related to workforce staffing, job competencies, and learning and development initiatives

    Toward cyberinfrastructure to facilitate collaboration and reproducibility for marine integrated ecosystem assessments

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    Author Posting. © The Author(s), 2016. This is the author's version of the work. It is posted here under a nonexclusive, irrevocable, paid-up, worldwide license granted to WHOI. It is made available for personal use, not for redistribution. The definitive version was published in Earth Science Informatics 10 (2017): 85-97, doi:10.1007/s12145-016-0280-4.There is a growing need for cyberinfrastructure to support science-based decision making in management of natural resources. In particular, our motivation was to aid the development of cyberinfrastructure for Integrated Ecosystem Assessments (IEAs) for marine ecosystems. The IEA process involves analysis of natural and socio-economic information based on diverse and disparate sources of data, requiring collaboration among scientists of many disciplines and communication with other stakeholders. Here we describe our bottom-up approach to developing cyberinfrastructure through a collaborative process engaging a small group of domain and computer scientists and software engineers. We report on a use case evaluated for an Ecosystem Status Report, a multi-disciplinary report inclusive of Earth, life, and social sciences, for the Northeast U.S. Continental Shelf Large Marine Ecosystem. Ultimately, we focused on sharing workflows as a component of the cyberinfrastructure to facilitate collaboration and reproducibility. We developed and deployed a software environment to generate a portion of the Report, retaining traceability of derived datasets including indicators of climate forcing, physical pressures, and ecosystem states. Our solution for sharing workflows and delivering reproducible documents includes IPython (now Jupyter) Notebooks. We describe technical and social challenges that we encountered in the use case and the importance of training to aid the adoption of best practices and new technologies by domain scientists. We consider the larger challenges for developing end-to-end cyberinfrastructure that engages other participants and stakeholders in the IEA process.Support for this research was provided by the U. S. National Science Foundation #0955649 with additional support to SB by the Investment in Science Fund at Woods Hole Oceanographic Institution

    Moving Towards Greater Justice: A Community-Based Research Project on Transit Affordability in Toronto

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    This report reflects on a collaborative advocacy research project I undertook in partnership with the Fair Fare Coalition (FFC), a transit activist and advocacy organization in Toronto. The project is a community-based research project on transit affordability involving the participation of low-income Torontonians throughout the city. The purpose was to bring together voices that are usually excluded from official city planning discourses and decision-making processes to highlight some of the frequently unaccounted for "costs" of increasing transit fares in Toronto – for example, on individual and community health and well-being. Through this, the Fair Fare Coalition hoped to build capacity and mobilize knowledge towards advocating for policy measures to increase transit affordability in Toronto. The participatory project's goals and outcomes are twofold. One goal is for the participatory process to culminate in a project deliverable that could be used for advocacy purposes in support of the Fair Fare Coalition's advocacy goals. The second goal is increasing community knowledge-building and mobilization, including ongoing political and advocacy actions. This is to highlight the fact that both the process and outcome are valuable and important. For the purposes of this report, I will contextualize and situate the significance of the FFC project in Toronto, providing background, exploring relevant literature, and explaining the importance of the research methodology. I will then share brief findings from the research, and provide analysis of both the outcomes and process of the research project

    Collaborative Decision Support and Documentation in Chemical Safety with KnowSEC

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    To protect the health of human and environment, the European Union implemented the REACH regulation for chemical substances. REACH is an acronym for Registration, Evaluation, Authorization, and Restriction of Chemicals. Under REACH, the authorities have the task of assessing chemical substances, especially those that might pose a risk to human health or environment. The work under REACH is scientifically, technically and procedurally a complex and knowledge-intensive task that is jointly performed by the European Chemicals Agency and member state authorities in Europe. The assessment of substances under REACH conducted in the German Environment Agency is supported by the knowledge-based system KnowSEC, which is used for the screening, documentation, and decision support when working on chemical substances. The software KnowSEC integrates advanced semantic technologies and strong problem solving methods. It allows for the collaborative work on substances in the context of the European REACH regulation. We discuss the applied methods and process models and we report on experiences with the implementation and use of the system

    Evaluating the Similarity Estimator Component of the TWIN Personality-based Recommender System

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    With the constant increase in the amount of information available in online communities, the task of building an appropriate Recommender System to support the user in her decision making process is becoming more and more challenging. In addition to the classical collaborative filtering and content based approaches, taking into account ratings, preferences and demographic characteristics of the users, a new type of Recommender System, based on personality parameters, has been emerging recently. In this paper we describe the TWIN (Tell Me What I Need) Personality Based Recommender System, and report on our experiments and experiences of utilizing techniques which allow the extraction of the personality type from text (following the Big Five model popular in the psychological research). We estimate the possibility of constructing the personality-based Recommender System that does not require users to fill in personality questionnaires. We are applying the proposed system in the online travelling domain to perform TripAdvisor hotels recommendation by analysing the text of user generated reviews, which are freely accessible from the community website
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