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20th International Conference on Product-Focused Software Process Improvement (PROFES)

作者： Olsson, Helena Holmstrom Bosch, Jan Malmo Univ Dept Comp Sci & Media Technol Malmo Sweden Chalmers Univ Technol Dept Comp Sci & Engn Gothenburg Sweden

ISBN: (纸本)9783030353339;9783030353322

For more than a decade, data driven development has attracted attention as one of the most powerful means to improve effectiveness and ensure value delivery to customers. In online companies, controlled experimentation is the primary technique to measure how customers respond to variants of deployed software. In B2B companies, an interest for data driven development is rapidly emerging and experiments are run on selected instances of the system or as comparisons of previously computed data to ensure quality, improve configurations and explore new value propositions. Although the adoption of data driven development is challenging in general, it is especially so for embedded systems companies and for companies developing on-premise software solutions. Due to complex systems with hardware dependencies, safetycritical functionality and strict regulations, these companies have longer development cycles, less frequent deployments and limited access to data. In this paper, and based on multi-case study research, we explore the specific challenges that embedded systems companies and companies developing onpremise solutions experience when adopting data driven development practices. The contribution of the paper is two-fold. First, we provide empirical evidence in which we identify the key challenges that embedded systems and on-premise software solutions companies experience as they evolve through the process of adopting data driven development practices. Second, we define the key focus areas that these companies need to address for evolving their data driven development adoption process.

关键词： data driven development Online software Embedded systems On-premise solutions Adoption process Challenges

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Toward data driven development in RoboCup 23rd

Toward Data Driven Development in RoboCup

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23rd Annual Robot World Cup International Symposium (RoboCup)

作者： Mellmann, Heinrich Schlotter, Benjamin Strobel, Philipp Humboldt Univ Adapt Syst Grp Unter Linden 6 D-10099 Berlin Germany

ISBN: (纸本)9783030356996;9783030356989

Conducting games in RoboCup incurs high cost in terms of effort, time, and money. The scientific outcome, however, is quite limited and often not very conclusive. Especially, analyzing and drawing conclusions about the performance of complex processes like decision making of an individual robot or the behavior on the team level poses a considerable challenge. Collecting more data during the competition games will help to analyze the performance of algorithms, identify errors and areas for improvement, and make more significant statements regarding the performance of the robots. In this work we investigate the possibilities for collection of the large scale RoboCup data and its analysis. We present a system for automatic recording of synchronized videos of RoboCup games and an application for exploration and annotation of large sets of RoboCup-related data. We also present data sets collected during the competitions in 2018 and an algorithm for visual detection and tracking of robots in the RoboCup videos. A first empirical evaluation shows promising results and demonstrates how such data can be integrated and used to validate robot's behavior.

关键词： data driven development Robot detection Visual robot tracking Camera localization

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Semantic Integration and Interdisciplinary Collaboration in Production Planning: A Graph-Based Approach for Enhanced data Consistency

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Procedia CIRP 2024年 130卷 1364-1371页

作者： Valesko Dausch Joachim Lentes Oliver Riedel Matthias Kreimeyer Institute for Engineering Design and Industrial Design of University of Stuttgart Pfaffenwaldring 9 DE-70569 Stuttgart Germany Fraunhofer Institute for Industrial Engineering Nobelstrasse 12 DE-70569 Stuttgart Germany Institute for Control Engineering of Machine Tools and Manufacturing Units of University of Stuttgart Seidenstrasse 36 DE-70174 Stuttgart Germany

Based on increasing individualization, shorter innovation cycles and integrating services into products complexity in the development of products and production processes increases. In combination with digitalization, this results in an increased need for interdisciplinary work. A high level of data consistency is required to cope with the resulting diverse and complex data structures, leading to the need for a consistent data model that orchestrates information flows. PLM-systems fall short in their ambition of reaching an overarching data management across the product lifecycle. This results in a lot of administrative work in planning instead of value-adding as well as in inconsistencies and incomplete change processes. To improve interdisciplinary collaboration in production planning, goal of this work is to develop a method leading to a comprehensive data model and to show it’s applicability by means of a case study. The steps of the research performed follow the typical circle of action research: diagnosis, planning, action, evaluation, and reflection. The data model resulting of the application of the method uses semantics to make relationships understandable for both humans and machines. This is necessary for downstream automation and the use of artificial intelligence. The three essential steps of the method are, firstly, an as-is modeling of the processes of interest. Then, the process models are used to evaluate the consistency and efficiency of the planning processes. The method is completed by a guideline for setting up the data model. The proposed approach aims to improve efficiency and quality in assembly planning processes, resulting in its importance for industrial companies.

关键词： data driven development knowledge management data continuity method

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The Five Purposes of Value Modeling 46

The Five Purposes of Value Modeling

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46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

作者： Olsson, Helena Holmstrom Bosch, Jan Malmo Univ Dept Comp Sci & Media Technol Malmo Sweden Chalmers Univ Technol Dept Comp Sci & Engn Gothenburg Sweden

ISBN: (纸本)9781728195322

data driven and experimental development practices provide effective means for companies to adopt a customer and market-centric way-of-working. In online companies, controlled experimentation is the primary technique to measure how customers respond to variants of deployed software. Over the recent years, and due to increasing connectivity and data collection from products in the field, these practices are being adopted also in software-intensive embedded systems companies. In these companies, experiments are run on selected instances of the system or as comparisons of previously computed data to ensure value delivery to customers, improve quality and explore new value propositions. However, to utilize the benefits of data-driven and experimental development practices, companies need to define what value factors to optimize for. For highly complex embedded systems with thousands of parameters, and with people at different levels in the organization having different opinions about the value of features, this is a challenging task. In this paper, we report on longitudinal multi-case study research in which we explore value modeling as a technique to help people in development, in product management and on the business level to align interests and agree on value factors. Based on this work, we identify five purposes of value modeling and how this technique helps accelerate critical activities in an organization. The contribution of this paper is three-fold. First, we provide empirical evidence for how value modeling is an effective technique to help companies define what to optimize for. Second, we identify five purposes of value modeling. Third, we identify the key challenges that the case companies experience when applying value modeling.

关键词： value modeling value factors data driven development experimental development customer value

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SMALL data AND SUSTAINABLE development-INDIVIDUALS AT THE CENTER OF data-driven SOCIETIES 9

SMALL DATA AND SUSTAINABLE DEVELOPMENT-INDIVIDUALS AT THE CE...

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ITU Kaleidoscope Conference - Challenges for a data-driven Society (ITU K)

作者： Thinyane, Mamello United Nations Univ Inst Comp & Soc Macau Peoples R China

ISBN: (纸本)9789261242817

At the centre of data-driven societies are individuals and end-users who not only generate data, but also benefit from the outcomes of the data-driven development. Extensive work has been undertaken to understand and explore the challenges and potential impact of data, in particular Big data, for the private as well as the public sectors. Similarly work has been undertaken within the domains of Personal Wormatics and life-logging, which has investigated the role of data, and specifically personal physical activity and health data towards improving the wellbeing of individuals. In this research we investigate the engagement of individuals in the use of data towards the achievement of the sustainable development imperatives as articulated in the 2030 Agenda for Sustainable development. The paper presents: the awareness levels of the participants with regards to the Sustainable development Goals;their attitudes and perceptions around monitoring of social indicators;key considerations associated with data ownership, privacy and confidentiality of data, as well as sharing of data within the data ecosystem. The paper subsequently discusses how these finding could inform the implementation of small data tools to support the active engagement of individuals in data-driven societies.

关键词： Small data Sustainable development data driven development

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Toward Evidence-Based Organizations Lessons from Embedded Systems, Online Games, and the Internet of Things

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IEEE SOFTWARE 2017年第5期34卷 60-66页

作者： Bosch, Jan Olsson, Helena H. Chalmers Univ Gothenburg Sweden Malmo Univ Dept Comp Sci Malmo Sweden

Case studies investigated how companies in three domains transition to data-driven development. The results led to a model of the levels that software-intensive companies move through as they evolve from an opinionbas... 详细信息

关键词： Business data Processing Computer Games data Analysis Decision Making Embedded Systems Internet Of Things Software Engineering Evidence Based Organizations Embedded Systems Online Games Internet Of Things Software Intensive Companies data driven development Decision Making Activities data Analysis Companies data Collection data Analysis Manuals Measurement Decision Making Evidence Based development data driven development data Collection data Analysis Decision Making Stairway To Heaven Software Engineering Software development

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ESAO: Towards data- and Ecosystem-driven R&D 14

ESAO: Towards Data- and Ecosystem-driven R&D

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18th International Software Product Line Conference (SPLC)

作者： Bosch, Jan Chalmers Univ Technol Gothenburg Sweden

ISBN: (纸本)9781450327404

With the increasing rate of change in industry, companies need to manage their internal alignment between strategy, software architecture and organizing R&D as well as with their ecosystem more proactively. Lack of alignment is the root cause of many problems experienced in the software-intensive systems industry. The ESAO model provides a framework for addressing the aforementioned challenges. It provides an internal perspective as well as an ecosystem perspective and for each perspective offers a strategic, architectural and ways of working dimension. ESAO offers tools for each of the dimensions as well as mechanisms for establishing and maintaining alignment.

关键词： Software ecosystems customer data data driven development

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A Rapid development Framework for Multilingual Spoken Dialogue Systems

A Rapid Development Framework for Multilingual Spoken Dialog...

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36th Annual IEEE International Computer Software and Applications Conference (COMPSAC)

作者： Araki, Masahiro Takegoshi, Daisuke Kyoto Inst Technol Dept Informat Sci Kyoto 606 Japan

ISBN: (纸本)9780769547367

We propose a new framework for rapid development of multilingual spoken dialogue systems based on a data modeling driven method. The development process begins with the data model definition in the Groovy programming language, with an extension for implementing spoken dialogue systems, such as the annotation of the target task type and the initiative type of the realized dialogue. Since the data model definition can be inherited from the existing semantic Web schema, the developer can choose the necessary properties from the schema via the GUI interface. By applying the data model definition, our framework generates all the necessary components for a spoken dialogue system based on the model-view-controller (MVC) model. In addition, template prompt entries, which the developer uses to specify the contents of the system utterance, are automatically generated. The fulfilled contents are translated to various languages using a translation Web service. The multilingual speech interaction is realized by an HTML5 speech API specifying only the "lang" attribute of the HTML element. Therefore, to realize a first prototype of a foreign language spoken dialogue system, the developer does not necessarily need knowledge of the target language.

关键词： multilingual spoken dialogue system data driven development

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