Rook is playful data visualization device aiming at the dissemination of air quality data. The Rook unit accesses the database of the Hollandse Luchten (henceforth HL) project, which collects data on air quality in Nord-Holland via a network of sensor kits distributed to the local population and displays it in an interactive way using lights and mist. The eerie and mysterious effect of the colored mist aims at a playful and enticing effect on its users, while, at the same time, spreading awareness on one of the key sustainability issues of the region. People can interact freely with the machine so to explore its working and the data it conveys.This paper aims to contextualize and describe the design process behind the creation of Rook and to propose some reflections on playfulness, citizenship and data visualization.
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During the past two decades the implementation and adoption of information technology has rapidly increased. As a consequence the way businesses operate has changed dramatically. For example, the amount of data has grown exponentially. Companies are looking for ways to use this data to add value to their business. This has implications for the manner in which (financial) governance needs to be organized. The main purpose of this study is to obtain insight in the changing role of controllers in order to add value to the business by means of data analytics. To answer the research question a literature study was performed to establish a theoretical foundation concerning data analytics and its potential use. Second, nineteen interviews were conducted with controllers, data scientists and academics in the financial domain. Thirdly, a focus group with experts was organized in which additional data were gathered. Based on the literature study and the participants responses it is clear that the challenge of the data explosion consist of converting data into information, knowledge and meaningful insights to support decision-making processes. Performing data analyses enables the controller to support rational decision making to complement the intuitive decision making by (senior) management. In this way, the controller has the opportunity to be in the lead of the information provision within an organization. However, controllers need to have more advanced data science and statistic competences to be able to provide management with effective analysis. Specifically, we found that an important skill regarding statistics is the visualization and communication of statistical analysis. This is needed for controllers in order to grow in their role as business partner..
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Full tekst beschikbaar voor gebruikers van Linkedin. Driven by technological innovations such as cloud and mobile computing, big data, artificial intelligence, sensors, intelligent manufacturing, robots and drones, the foundations of organizations and sectors are changing rapidly. Many organizations do not yet have the skills needed to generate insights from data and to use data effectively. The success of analytics in an organization is not only determined by data scientists, but by cross-functional teams consisting of data engineers, data architects, data visualization experts, and ("perhaps most important"), Analytics Translators.
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Visualizing news is increasingly considered an apt way for dealing with two challenges of modern journalism: disclosing big data and presenting complex information in a way that is easy to comprehend. Newsrooms are trying their hand at it, and finding ways to organize the production of information visualizations effectively. This study delves into reported challenges for the production of news visualizations and suggests, in line with findings from the research case studies, that the introduction of information visualization in the media requires a convergence of journalistic and visual thinking skills, a more iterative news production process and a revised view of the function of news per se.
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Depicting news graphically is considered an apt way to deal with two challenges of modern journalism: to disclose big data, and present the news attractively, visually, and fast to grasp. Newsrooms try their hand at it and are figuring out how to organize production of information visualizations effectively. This study delves into reported obstacles and challenges for the production of news visualizations and suggests that enhancing the quality of information visualization in news media, asks for a clear view on what information visualization means for the production of news, rather than only stimulating journalist to acquire new skills
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Learning analytics is the analysis of student data with the purpose of improving learning. However, the process of data cleaning remains underexposed within learning analytics literature. In this paper, we elaborate on choices made in the cleaning process of student data and their consequences. We illustrate this with a case where data was gathered during six courses taught via Moodle. In this data set, only 21% of the logged activities were linked to a specific course. We illustrate possible choices in dealing with missing data by applying the cleaning process twelve times with different choices on copies of the raw data. Consequently, the analysis of the data shows varying outcomes. As the purpose of learning analytics is to intervene based on analysis and visualizations, it is of utmost importance to be aware of choices made during data cleaning. This paper's main goal is to make stakeholders of (learning) analytics activities aware of the fact that choices are made during data cleaning have consequences on the outcomes. We believe that there should be transparency to the users of these outcomes and give them a detailed report of the decisions made.
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The planning and design of an inland container terminal is a complex task due to many interrelated design parameters and interdependent stakeholders. Design tools may support the optimization of technical, economic and logistical values, but this optimization is strongly inhibited by conflicting interests, political and environmental boundaries and strategic stakeholder behavior. The main research question in this contribution is: how can visualization-simulation tools be used in an early stage of complex inter-organizational decision-making on infrastructures in such a way that it enhances the quality and progress of this decision-making? A collaborative design environment was developed for the early phase of inter-organizational decision-making. In the gaming-simulation 'containers a drift', a number of public and private stakeholders try to reach initial agreement on an inland container terminal. A team of process-managers facilitate a collaborative design process and set up a number of ground rules for negotiation. A visualization-simulation tool is used to explore the various technical, economic, political and spatial issues. While negotiating on issues such as location and size of the terminal, small groups of stakeholders interactively draw several terminal layouts. Logistical and economic data, e.g., on ships, containers and costs are entered in a database. The terminal's performance and its dynamic behavior is simulated and assessed. The game was played in three sessions with a total number of 77 students. The evaluation results indicate that the various tools are easy to work with, greatly contribute to the quality and process of negotiation and generate mutual understanding.
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Analyzing historical decision-related data can help support actual operational decision-making processes. Decision mining can be employed for such analysis. This paper proposes the Decision Discovery Framework (DDF) designed to develop, adapt, or select a decision discovery algorithm by outlining specific guidelines for input data usage, classifier handling, and decision model representation. This framework incorporates the use of Decision Model and Notation (DMN) for enhanced comprehensibility and normalization to simplify decision tables. The framework’s efficacy was tested by adapting the C4.5 algorithm to the DM45 algorithm. The proposed adaptations include (1) the utilization of a decision log, (2) ensure an unpruned decision tree, (3) the generation DMN, and (4) normalize decision table. Future research can focus on supporting on practitioners in modeling decisions, ensuring their decision-making is compliant, and suggesting improvements to the modeled decisions. Another future research direction is to explore the ability to process unstructured data as input for the discovery of decisions.
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Through artistic interventions into the computational backbone of maternity services, the artists behind the Body Recovery Unit explore data production and its usages in healthcare governance. Taking their artwork The National Catalogue Of Savings Opportunities. Maternity, Volume 1: London (2017) as a case study, they explore how artists working with ‘live’ computational culture might draw from critical theory, Science and Technology Studies as well as feminist strategies within arts-led enquiry. This paper examines the mechanisms through which maternal bodies are rendered visible or invisible to managerial scrutiny, by exploring the interlocking elements of commissioning structures, nationwide information standards and databases in tandem with everyday maternity healthcare practices on the wards in the UK. The work provides a new context to understand how re-prioritisation of ‘natural’ and ‘normal’ births, breastfeeding, skin-to-skin contact, age of conception and other factors are gaining momentum in sync with cost-reduction initiatives, funding cuts and privatisation of healthcare services.
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Terms like ‘big data’, ‘data science’, and ‘data visualisation’ have become buzzwords in recent years and are increasingly intertwined with journalism. Data visualisation may further blur the lines between science communication and graphic design. Our study is situated in these overlaps to compare the design of data visualisations in science news stories across four online news media platforms in South Africa and the United States. Our study contributes to an understanding of how well-considered data visualisations are tools for effective storytelling, and offers practical recommendations for using data visualisation in science communication efforts.
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