Kawa Nazemi; Dirk Burkhardt; Lukas Kaupp; Till Dannewald; Matthias Kowald; Egils Ginters
In: Egils Ginters; Mario Arturo Ruiz Estrada; Miquel Angel Piera Eroles (Ed.): ICTE in Transportation and Logistics 2019, pp. 82–89, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-39688-6.
Mobility, transportation and logistics are more and more influenced by a variety of indicators such as new technological developments, ecological and economic changes, political decisions and in particular humans' mobility behavior. These indicators will lead to massive changes in our daily live with regards to mobility, transportation and logistics. New technologies will lead to a different mobility behavior with new constraints. These changes in mobility behavior and logistics require analytical systems to forecast the required information and probably appearing changes. These systems have to consider different perspectives and employ multiple indicators. Visual Analytics provides both, the analytical approaches by including machine learning approaches and interactive visualizations to enable such analytical tasks. In this paper the main indicators for Visual Analytics in the domain of mobility transportation and logistics are discussed and followed by exemplary case studies to illustrate the advantages of such systems. The examples are aimed to demonstrate the benefits of Visual Analytics in mobility.
Dirk Burkhardt; Kawa Nazemi; Egils Ginters
In: Egils Ginters; Mario Arturo Ruiz Estrada; Miquel Angel Piera Eroles (Ed.): ICTE in Transportation and Logistics 2019, pp. 319–327, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-39688-6.
In the domain of mobility and logistics, a variety of new technologies and business ideas are arising. Beside technologies that aim on ecologically and economic transportation, such as electric engines, there are also fundamental different approaches like central packaging stations or deliveries via drones. Yet, there is a growing need for analytical systems that enable identifying new technologies, innovations, business models etc. and give also the opportunity to rate those in perspective of business relevance. Commonly adaptive systems investigate only the users' behavior, while a process-related supports could assist to solve an analytical task more efficient and effective. In this article an approach that enables non-experts to perform visual trend analysis through an advanced process support based on process mining is described. This allow us to calculate a process model based on events, which is the baseline for process support feature calculation. These features and the process model enable to assist non-expert users in complex analytical tasks.
Kawa Nazemi; Dirk Burkhardt
Forschungstag 2019 der Hessischen Hochschulen für Angewandte Wissenschaften (HAW), Frankfurt, Germany, 2019.
Im Rahmen des Vorhabens soll mit „AVARTIM“ ein softwaregestützter Prozess zum Erkennen und Bewerten von Trends, Markt- und Technologiesignalen entwickelt werden, um den Prozess des Innovations- und Technologiemanagements nachhaltig zu unterstützen. Dabei soll im Rahmen des Vorhabens eine Infrastruktur an der Hochschule Darmstadt aufgebaut werden, die modular ist und somit auf technologische Veränderungen schnell reagieren kann. Die zu entwickelnde Infrastruktur dient hierbei als Vorlaufforschung und Ausgangstechnologie sowohl für den industriellen Einsatz durch und mit den KMU Partnern als auch zur Beantragung von Verbundvorhaben.
Kawa Nazemi; Dirk Burkhardt
In: George Bebis; Richard Boyle; Bahram Parvin; Darko Koracin; Daniela Ushizima; Sek Chai; Shinjiro Sueda; Xin Lin; Aidong Lu; Daniel Thalmann; Chaoli Wang; Panpan Xu (Ed.): Advances in Visual Computing, pp. 283–294, Springer International Publishing, Cham, 2019, ISBN: 978-3-030-33723-0.
Tags: Artificial Intelligence, Data Analytics, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, maschine learning, Visual analytics| | |
Visual Analytics provides with a combination of automated techniques and interactive visualizations huge analysis possibilities in technology and innovation management. Thereby not only the use of machine learning data mining methods plays an important role. Due to the high interaction capabilities, it provides a more user-centered approach, where users are able to manipulate the entire analysis process and get the most valuable information. Existing Visual Analytics systems for Trend Analytics and technology and innovation management do not really make use of this unique feature and almost neglect the human in the analysis process. Outcomes from research in information search, information visualization and technology management can lead to more sophisticated Visual Analytics systems that involved the human in the entire analysis process. We propose in this paper a new interaction approach for Visual Analytics in technology and innovation management with a special focus on technological trend analytics.
Dirk Burkhardt; Kawa Nazemi; Arjan Kuijper; Egils Ginters
In: 5th International Conference of the Virtual and Augmented Reality in Education (VARE2019), pp. 11–19, CAL-TEK SRL, Rende, Italy, 2019, ISBN: 978-88-85741-41-6, (Nominated for Best Paper Award).
The awareness of market trends becomes relevant for a broad number of market branches, in particular the more they are challenged by the digitalization. Trend analysis solutions help business executives identifying upcoming trends early. But solid market analysis takes their time and are often not available on consulting or strategy discussions. This circumstance often leads to unproductive debates where no clear strategy, technology etc. could be identified. Therefore, we propose a mobile visual trend analysis approach that enables a quick trend analysis to identify at least the most relevant and irrelevant aspects to focus debates on the relevant options. To enable an analysis like this, the exhausting analysis on powerful workstations with large screens has to adopted to mobile devices within a mobile behavior. Our main contribution is the therefore a new approach of a mobile knowledge cockpit, which provides different analytical visualizations within and intuitive interaction design.
Egils Ginters; Dirk Burkhardt; Kawa Nazemi; Yuri Merkuryev
In: 5th International Conference of the Virtual and Augmented Reality in Education (VARE 2019), pp. 20–27, CAL-TEK SRL, Rende, Italy, 2019, ISBN: 978-88-85741-41-6.
Virtual and augmented reality (VR / AR) applications have successfully overcome the critical part of the Gartner curve. Investments are made and new products entering the economy. However, a very small percentage of society have also heard about AR glasses, mainly linking these with potential identity threats and personal data breaches. The authors dealt with the design of application of AR to improve golf skills by improving the putting technique. The above solution is complicated by requiring complex object recognition, tracking and advanced AR software designing.
Kawa Nazemi; Dirk Burkhardt
Presented at OpenRheinMain Conference (ORM2019), 13 September 2019, Darmstadt, Germany, 2019.
Through coupling of Data Mining, Visual Analytics and Business Analytics techniques, we created a novel solution for strategic market analysis with focus on early trend recognition. As fundament, we are able to consider a variety of text data, as for instance research publications available from a number of (open access) digital libraries, reports and other data from companies, web data about markets as well as news from companies or social media data etc. In an advanced and unified processing pipeline, the information is extracted and mined for a variety of analytical purposes. Via an interactive analysis user-interface, domain experts are able to analysis strong and weak signals in perspective of upcoming trends.
Kawa Nazemi; Dirk Burkhardt
In: 2019 23rd International Conference Information Visualisation (IV), pp. 191-200, 2019, ISSN: 2375-0138, (Best Paper Award).
Tags: Data Mining, Data Models, Data Visualization, emerging trend identification, Hidden Markov models, Information visualization, Market research, Patents, Trend Analytics, Visual analytics, visual business analytics, Visualization| | |
The awareness of emerging technologies is essential for strategic decision making in enterprises. Emerging and decreasing technological trends could lead to strengthening the competitiveness and market positioning. The exploration, detection and identification of such trends can be essentially supported through information visualization, trend mining and in particular through the combination of those. Commonly, trends appear first in science and scientific documents. However, those documents do not provide sufficient information for analyzing and identifying emerging trends. It is necessary to enrich data, extract information from the integrated data, measure the gradient of trends over time and provide effective interactive visualizations. We introduce in this paper an approach for integrating, enriching, mining, analyzing, identifying and visualizing emerging trends from scientific documents. Our approach enhances the state of the art in visual trend analytics by investigating the entire analysis process and providing an approach for enabling human to explore undetected potentially emerging trends.
Visual Trend Analytics in Digital Libraries Miscellaneous
Contribution at ASIS&T European Chapter Seminar on Information Science Trends: Search Engines and Information Retrieval., 2019.
The early awareness of upcoming trends in technology enables a more goal-directed and efficient way for deciding future strategic directions in enterprises and research. Possible sources for this valuable information are ubiquitously and freely available in the Web, e.g. news services, companies’ reports, social media platforms and blog infrastructures. To support users in handling these information sources and to keep track of the newest developments, current information systems make intensively use of information retrieval methods that extract relevant information out of the mass amount of data. The related information systems are commonly focused on providing users with easy access to information of their interest and deal with the access to information items and resources , but they neither provide an overview of the content nor enable the exploration of emerging or decreasing trends for inferring possible future innovations. The gathering and analysis of this continuously increasing knowledge pool is a very tedious and time-consuming task and borders on the limits of manual feasibility. The interactive overview on data, the continuous changes in data, and the ability to explore data and gain insights are sufficiently supported by Visual Analytics and information visualization approaches, whereas the appliance of such approach in combination with trend analysis are rarely propagated. In fact, these so-called early signals require not only an analysis through machine learning techniques to identify emerging trends, but also human interaction and intervention to adapt the parameters used to their own needs . There are two main aspects to consider in the analysis process: 1) which data reveal very early trends and 2) how can human be involved in the analysis process .
Udo Bleimann; Dirk Burkhardt; Bernhard Humm; Robert Loew; Stefanie Regier; Ingo Stengel; Paul Walsh (Ed.)
CEUR-WS.org, Aachen, Germany, Vol. 2348 , 2019, ISSN: 1613-0073, (urn:nbn:de:0074-2348-5).
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In today's world, which has recently seen fractures and isolation forming among states, international and interdisciplinary collaboration is an increasingly important source of progress. Collaboration is a rich source of innovation and growth. It is the goal of the Collaborative European Research Conference (CERC 2019) to foster collaboration among friends and colleagues across disciplines and nations within Europe. CERC emerged from a long-standing cooperation between the Cork Institute of Technology, Ireland and Hochschule Darmstadt - University of Applied Sciences, Germany. CERC has grown to include more well-established partners in Germany (Hochschule Karlsruhe and Fernuniversität Hagen), United Kingdom, Greece, Spain, Italy, and many more.
CERC is truly interdisciplinary, bringing together new and experienced researchers from science, engineering, business, humanities, and the arts. At CERC researchers not only present their findings as published in their research papers. They are also challenged to collaboratively work out joint aspects of their research during conference sessions and informal social events and gatherings.
To organize such an event involves the hard work of many people. Thanks go to the international program committee and my fellow program chairs, particularly to Prof Udo Bleimann and Prof Ingo Stengel for supporting me in the review process. Dirk Burkhardt and Dr Robert Loew put a great effort into setting up the website and conference management system and preparing the conference programme and proceedings. Many of my colleagues from Hochschule Darmstadt were invaluable for local organization. Thanks also to Hochschule Darmstadt and the Research Center for Applied Informatics (FZAI) for financial support.
Kawa Nazemi; Dirk Burkhardt
In: ICTE in Transportation and Logistics 2018 (ICTE 2018), 149 , pp. 138-150, 2019, ISSN: 1877-0509.
Mobility, logistics and transportation are emerging fields of research and application. Humans’ mobility behavior plays an increasing role for societal challenges. Beside the societal challenges these areas are strongly related to technologies and innovations. Gathering information about emerging technologies plays an increasing role for the entire research in these areas. Humans’ information processing can be strongly supported by Visual Analytics that combines automatic modelling and interactive visualizations. The juxtapose orchestration of interactive visualization enables gathering more information in a shorter time. We propose in this paper an approach that goes beyond the established methods of dashboarding and enables visualizing different databases, data-sets and sub-sets of data with juxtaposed visual interfaces. Our approach should be seen as an expandable method. Our main contributions are an in-depth analysis of visual task models and an approach for juxtaposing visual layouts as visual dashboards to enable solving complex tasks. We illustrate our main outcome through a case study that investigates the area of mobility and illustrates how complex analytical tasks can be performed easily by combining different visual interfaces.
Dirk Burkhardt; Kawa Nazemi
In: ICTE in Transportation and Logistics 2018 (ICTE 2018), 149 , pp. 515-524, 2019, ISSN: 1877-0509.
The impact of the electromobility has next to the automotive industry also an increasing impact on the transportation and logistics domain. In particular the today’s starting switches to electronic trucks/scooter lead to massive changes in the organization and planning in this field. Public funding or tax reduction for environment friendly solutions forces also the growth of new mobility and transportation services. However, the vast changes in this domain and the high number of innovations of new technologies and services leads also into a critical legal uncertainty. The clarification of a legal status for a new technology or service can become cost intensive in a dimension that in particular startups could not invest. In this paper we therefore introduce a new approach to identify and analyze legal conflicts based on a business model or plan against existing laws. The intention is that an early awareness of critical legal aspect could enable an early adoption of the planned service to ensure its legality. Our main contribution is distinguished in two parts. Firstly, a new Norm-graph visualization approach to show laws and legal aspects in an easier understandable manner. And secondly, a Visual Legal Analytics approach to analyze legal conflicts e.g. on the basis of a business plans. The Visual Legal Analytics approach aims to provide a visual analysis interface to validate the automatically identified legal conflicts resulting from the pre-processing stage with a graphical overview about the derivation down to the law roots and the option to check the original sources to get further details. At the end analyst can so verify conflicts as relevant and resolve it by advancing e.g. the business plan or as irrelevant. An evaluation performed with lawyers has proofed our approach.
Kawa Nazemi; Dirk Burkhardt
In: A. G. Bruzzone; Egils Ginters; E. G. Mendívil; J. M. Guitierrez; F. Longo (Ed.): The 4th International Conference of the Virtual and Augmented Reality in Education, I3M, 2018, ISBN: 978-88-85741-21-8.
Interactive visualization and visual analytics systems enables solving a variety of tasks. Starting with simple search tasks for outliers, anomalies etc. in data to analytical comparisons, information visualizations may lead to a faster and more precise solving of tasks. There exist a variety of methods to support users in the process of task solving, e.g. superimposing, juxtaposing or partitioning complex visual structures. Commonly all these methods make use of a single data source that is visualized at the same time. We propose in this paper an approach that goes beyond the established methods and enables visualizing different databases, data-sets and sub-sets of data with juxtaposed visual interfaces. Our approach should be seen as an expandable method. Our main contributions are an in-depth analysis of visual task models and an approach for juxtaposing visual layouts as visual interfaces to enable solving complex tasks.
Dirk Burkhardt; Kawa Nazemi
In: The 4th International Conference of the Virtual and Augmented Reality in Education, I3M, 2018, ISBN: 978-88-85741-21-8.
Laws or in general legal documents regulate a wide range of our daily life and also define the borders of business models and commercial services. However, legal text and laws are almost hard to understand. From other domains it is already known that visualizations can help understanding complex aspects easier. In fact, in this paper we introduce a new approach to visualize legal texts in a Norm-graph visualization. In the developed Norm-graph visualization it is possible to show major aspects of laws and make it easier for users to understand it. The Norm-graph is based on semantic legal data, a so called Legal-Concept-Ontology.
In: Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization, pp. 187–190, ACM, Singapore, Singapore, 2018, ISBN: 978-1-4503-5784-5.
The increased utilisation of adaptive visualisation techniques in commercial software requires design principles that provide guidance on how to design user interfaces that change their appearance during runtime. To contribute to the ongoing adaptive user interface (AUI) research, the development of a model is proposed that enables the methodological development of design principles for AUIs. The adoption of the conceptual framework of design-science is proposed for that purpose. Following the framework, the literature of AUI research (to identify observed user behaviour) as well as the literature of human factors (to explain the observed behaviour) have been reviewed. Design principles are built based on this knowledge. This thesis can contribute to an quality improvement of AUI systems.
In: W Karwowski; T Ahram (Ed.): Intelligent Human Systems Integration: Proceedings of the International Conference on Intelligent Human Systems Integration (IHSI 2018): Integrating People and Intelligent Systems. Advances in Intelligent Systems and Computing (AISC 722), pp. 180–190, Springer International Publishing, Cham, 2018, ISBN: 978-3-319-73888-8.
Visual Analytics enables solving complex and analytical tasks by combining automated data analytics methods and interactive visualizations. The complexity of tasks, the huge amount of data and the complex visual representation may overstrain the users of such systems. Intelligent and adaptive visualizations system show already promising results to bridge the gap between human and the complex visualization. We introduce in this paper a revised version of layer-based visual adaptation model that considers the human perception and cognition abilities. The model is then used to enhance the most popular Visual Analytics model to enable the development of Intelligent Visual Analytics systems.
Dirk Burkhardt; Sachin Pattan; Kawa Nazemi; Arjan Kuijper
In: Procedia Computer Science, 104 , pp. 539 - 547, 2017, ISSN: 1877-0509, (ICTE 2016, Riga Technical University, Latvia).
A new approach for classifying users’ search intentions is described in this paper. The approach uses the parameters: word frequency, query length and entity matching for distinguishing the user's query into exploratory, targeted and analysis search. The approach focuses mainly on word frequency analysis, where different sources for word frequency data are considered such as the Wortschatz frequency service by the University of Leipzig and the Microsoft Ngram service (now part of the Microsoft Cognitive Services). The model is evaluated with the help of a survey tool and few machine learning techniques. The survey was conducted with more than one hundred users and on evaluating the model with the collected data, the results are satisfactory. In big data applications the search intention analysis can be used to identify the purpose of a performed search, to provide an optimal initially set of visualizations that respects the intended task of the user to work with the result data.
Dirk Burkhardt; Kawa Nazemi
In: Korinna Bade; Matthias Pietsch; Susanne Raabe; Lars Schütz (Ed.): Technologische Trends im Spannungsfeld von Beteiligung – Entscheidung – Planung, pp. 29–38, Shaker Verlag, Aachen, Germany, 2017, ISBN: 978-3844054392.
Politische und gesellschaftliche Prozesse werden durch Informationen sehr stark geprägt, wie auch die jüngsten Ereignisse aufzeigen. Diese Informationen können, trotz enormer Fortschritte, nicht immer aus den sehr großen, heterogenen und verteilten Daten entnommen werden. „Big Data“ stellt somit auch in der öffentlichen Verwaltung eine immer größere Herausforderung dar. Sowohl durch eine umfangreiche Erhebung von Statistiken, als auch durch Dokumente wie Berichte und Studien, wachsen in Behörden die zu bewältigenden Informationsaufgaben. Darüber hinaus spielt die Berücksichtigung von Bürgermeinungen, vor allem auf kommunaler Ebene, eine immer größere Rolle. Eine Auswertung ohne moderne Informationstechnik ist dabei kaum mehr möglich. Damit aber aus diesen Daten tatsächlich die relevanten Informationen extrahiert werden, bedarf es Informationsvisualisierung und Visual Analytics Systeme die sehr detaillierte, aber dennoch einfache und schnelle Analysen für den Menschen erlauben. Dies stellt aber sehr hohe Anforderungen an die visuellen Systeme, da sie gleichzeitig auch den Nutzer und dessen Fähigkeiten berücksichtigen müssen.
Kawa Nazemi; Dirk Burkhardt; Arjan Kuijper
In: Journal of Computer Science Technology Updates, 4 , 2017.
Tags: Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, User behavior, User Interactions, User Interface, User modeling, User-centered design, Visual analytics| | |
Visual information search systems support different search approaches such as targeted, exploratory or analytical search. Those visual systems deal with the challenge of composing optimal initial result visualization sets that face the search intention and respond to the search behavior of users. The diversity of these kinds of search tasks require different sets of visual layouts and functionalities, e.g. to filter, thrill-down or even analyze concrete data properties. This paper describes a new approach to calculate the probability towards the three mentioned search intentions, derived from users’ behavior. The implementation is realized as a web-service, which is included in a visual environment that is designed to enable various search strategies based on heterogeneous data sources. In fact, based on an entered search query our developed search intention analysis web-service calculates the most probable search task, and our visualization system initially shows the optimal result set of visualizations to solve the task. The main contribution of this paper is a probability-based approach to derive the users’ search intentions based on the search behavior enhanced by the application to a visual system.
Springer International Publishing, Studies in Computational Intelligence 646, 2016, ISBN: 978-3-319-30815-9.
This book introduces a novel approach for intelligent visualizations that adapts the different visual variables and data processing to human's behavior and given tasks. Thereby a number of new algorithms and methods are introduced to satisfy the human need of information and knowledge and enable a usable and attractive way of information acquisition. Each method and algorithm is illustrated in a replicable way to enable the reproduction of the entire "SemaVis" system or parts of it. The introduced evaluation is scientifically well-designed and performed with more than enough participants to validate the benefits of the methods. Beside the introduced new approaches and algorithms, readers may find a sophisticated literature review in Information Visualization and Visual Analytics, Semantics and information extraction, and intelligent and adaptive systems. This book is based on an awarded and distinguished doctoral thesis in computer science.
Kawa Nazemi; Martin Steiger; Dirk Burkhardt; Jörn Kohlhammer
Information Visualization and Policy Modeling Book Chapter
In: Big Data: Concepts, Methodologies, Tools, and Applications, Information Science Reference, IGI Global, Hershey PA, USA, 2016, ISBN: 978-1-466-69840-6, (reprint).
Policy design requires the investigation of various data in several design steps for making the right decisions, validating, or monitoring the political environment. The increasing amount of data is challenging for the stakeholders in this domain. One promising way to access the “big data” is by abstracted visual patterns and pictures, as proposed by information visualization. This chapter introduces the main idea of information visualization in policy modeling. First abstracted steps of policy design are introduced that enable the identification of information visualization in the entire policy life-cycle. Thereafter, the foundations of information visualization are introduced based on an established reference model. The authors aim to amplify the incorporation of information visualization in the entire policy design process. Therefore, the aspects of data and human interaction are introduced, too. The foundation leads to description of a conceptual design for social data visualization, and the aspect of semantics plays an important role.
Dirk Burkhardt; Kawa Nazemi; Egils Ginters
In: Procedia Computer Science. 2015 International Conference Virtual and Augmented Reality in Education, 75 , pp. 66 - 74, 2015, ISSN: 1877-0509.
E-Participation and the engagement of citizens in politics are on the agenda in many countries. Therefore, a number of project and programs were initiated that aim at finding creative and effective solutions for involving citizens. One intended aspect is the provision of transparency that enables citizens to analyze socio-economical indicators and serves as basement for initial data storing for e-participation scenarios simulation. A beyond going step is to consider citizens’ opinions in the policy making process. Unfortunately this will only be possible; if a significant number of citizens know what concrete aspect should be realized. The growth and establishment of social media nowadays allow most people to discuss political ideas and critics virtually and anonymously achieving higher credibility of the data usable for policy making. However, the major barrier is the different topical languages, the representatives’ role and weak visualization of the results. This article dealt with a best-practice piloting approach for discussing and realizing innovative solutions with a variety of stakeholders from different domains. The core of this paper is how to deal and manage the different perspective on development process, to aim on designing a common set of requirements and development procedure. The methodology is practically and beneficial applied as social media integration solution in the EC FP7 FUPOL research project.
Kawa Nazemi; Reimond Retz; Dirk Burkhardt; Arjan Kuijper; Jörn Kohlhammer; Dieter W. Fellner
Visual Trend Analysis with Digital Libraries Inproceedings
In: Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business., pp. 14:1–14:8, ACM, Graz, Austria, 2015, ISBN: 978-1-4503-3721-2.
The early awareness of new technologies and upcoming trends is essential for making strategic decisions in enterprises and research. Trends may signal that technologies or related topics might be of great interest in the future or obsolete for future directions. The identification of such trends premises analytical skills that can be supported through trend mining and visual analytics. Thus the earliest trends or signals commonly appear in science, the investigation of digital libraries in this context is inevitable. However, digital libraries do not provide sufficient information for analyzing trends. It is necessary to integrate data, extract information from the integrated data and provide effective interactive visual analysis tools. We introduce in this paper a model that investigates all stages from data integration to interactive visualization for identifying trends and analyzing the market situation through our visual trend analysis environment. Our approach improves the visual analysis of trends by investigating the entire transformation steps from raw and structured data to visual representations.
Dirk Burkhardt; Kawa Nazemi; Mohsen Parisay; Jörn Kohlhammer
In: International Journal of Digital Society (IJDS), 5 (3), pp. 915–923, 2015, ISSN: 2040-2570.
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Public authorities normally consider statistical data about indicators in their decision makings. Such valid kind of data allows an objective observation about indicator developments over time. In case of a significant deviation from the normal indicator level, it is difficult to understand the reasons for upcoming problems. In this article we present an approach that allows an enhanced information gathering through an improved information overview about the depending aspects to such an indicator by considering governmental data-sources that provide also other types of data than just statistics. Even more, our approach integrates a system that allows generating explanations for Open Government Data, especially to specific indicators, based on Linked-Open Data and shows it in graphical form to enable a fast overview gathering. This allows decision-makers to get hints for unexpected reasons of concrete problems that may influence an indicator.
Dirk Burkhardt; Kawa Nazemi; Jörn Kohlhammer
Policy Modeling Methodologies Book Chapter
In: Public Affairs and Administration: Concepts, Methodologies, Tools, and Applications, IGI Global, 2015, ISBN: 978-1-466-68358-7, (reprint).
The process to develop sustainable public policies is done by public authorities ensuring the involvement of all stakeholders. ICT is rarely included in most of the today's applied policymaking processes. Other process definitions with a focus on ICT inclusion in policy modeling still exist, but they are not well defined. This chapter gives an overview of the existing policy modeling process types and explains their major foci and how they consider ICT and the practical process in public authorities. Afterwards, based on these descriptions, the general requirements on a new ICT-oriented policy modeling process that allows the inclusion of ICT into a valid and useful process for public authorities is given.