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IVM 2018 - 4th International Workshop on Information Value Management - Cha...

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Hotel Vila Galé Santa Cruz

Rua São Fernando, 5

9100-173 Santa Cruz

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4th International Workshop on Information Value Management - Challenges in an Area of Digitalisation and Big Data - IVM 2018

21 - 24 March, 2018 - Funchal, Madeira, Portugal
In conjunction with the 20th International Conference on Enterprise Information Systems - ICEIS 2018

CO-CHAIRS

Mouzhi Ge
Masaryk University
Czech Republic

Brief Bio
Dr. Mouzhi Ge is a Research Fellow at the e-Business and Web Science Research Group in the Universitaet der Bundeswehr Munich in Germany. Before joining Universitaet der Bundeswehr Munich, he had been working as an IT Manager in the Oxbridge Investment Ltd. in UK and as a research scientist in the Technical University Dortmund in Germany. During 2011, he is also a visiting researcher in the University of Milano-Bicocca in Italy. His research interests are mainly focused on data quality management, recommender systems and semantic technologies.

Markus Helfert
Dublin City University
Ireland

Brief Bio
Dr. Markus Helfert is Director of the Business Informatics Group at Dublin City University, and a Senior Lecturer in Information Systems at the School of Computing, Dublin City University (Ireland). He is senior academic at Lero - The Irish Software Research Centre. He is a research affiliate at The Open Government Institute at Zeppelin University in Germany. His research interests include Information Management, Innovation, Cloud Computing, Service Science, Enterprise Architecture and Open Data and Smart Cities. Currently he advises several small and medium sized Enter prise in relation to Innovation and IT Management. Markus Helfert has authored more than 200+ academic articles, journal and book contributions and has presented his work at international conferences. He is member of international programme committees and reviewer and associate editor of several IS journals. Dr. Helfert has received national and international grants from agencies such as European Union (FP7; H2020), Science Foundation Ireland and Enterprise Ireland. Prior to his appointment at Dublin City University, he held a research position at the Institute of Information Management at the University of St. Gallen. Dr. Helfert holds a PhD from the University of St. Gallen (Switzerland), an MSc from the University of Mannheim (Germany) and a BSc from Napier University in Scotland (UK).

SCOPE

Recent advances in technology such as Internet of Things, Analytics and Big Data lead not only a technology revolution but also offer a magnitude of business benefits. With the arrival of Industry 4.0, the Big Data created within the Internet of Things is so enormous that it cannot be fully processed in conventional databases. Thus new challenges in an area of Digitalisation and Big Data have created opportunities to explore the information value using data analytics. In order to drive the next horizon of operational effectiveness, Big Data solutions are used to optimize business processes and reduce decision-making time etc.. Given the complex nature of the information, Big Data and IoT are demanded to address the interaction and flexibility issues among the new intelligent objects. By providing increasing access to Data and advanced capabilities to analyse large amounts of data we need to re-examine the value contribution of insights and impacts these technologies offer to business. With this workshop we aim to provide an international forum that explores various business benefits of data and information. Information creates not only value in financial terms but also in terms of operational and strategic advantages. Thus exploring the value of information and its management is crucial to the success of world-leading organizations. The value of information can be determined by its importance to and the impact information has on the business operations such as decision making, strategy development or optimizing supply chains. However, the issue of how to manage the value of information is still challenging and research so far could only address limited aspects. It has been argued that if information result in enhanced business value, the focus needs to shift from project based cost/benefit analysis to managing the overall value creation of information. Furthermore, over the last decade a move from solely technical aspects to a combination of multiple contextual factors such as technology, sector, organizational culture, and management style can be observed. The information systems literature has consistently emphasized the need for alignment of information systems with organizational goals and strategies and its impact on organizational performance. One of the key challenges and subject of continuous debate focuses on how to achieve, measure, increase and manage information and the value it creates to organisations. It has been concern to researchers and management for many years and the difficulty in measuring less tangible benefits has been emphasized. With this workshop we aim to go beyond traditional IT productivity and cost evaluations; we view information as a crucial asset that creates value to an organizations, and thus needs to be managed accordingly for optimal business value. In this workshop, we aim to provide a platform for discussing approaches, models, results and case studies or experience reports addressing a broad range of issues related to Information Value Management. Research challenges include how to determine the Value of Information and its impact on business performance, managing Data and Information Quality, capturing and maintaining Information Assets, and designing and improving Information Manufacture System. Papers can include and discuss various research methods and can be based on case studies, quantitative and quantitative methods, design science as well as experimental and simulation. In addition practical oriented research and experience reports are encouraged.


TOPICS OF INTEREST
Topics of interest include, but are not limited to:

  • Big Data Value
  • Master Data Management
  • Big Data Quality Assessment
  • Determining Information Value
  • Specifying and Measuring the Benefits from Information
  • Data and Information Quality
  • Information Value Chains
  • Optimising Information Value
  • Information Lifecycle Concepts
  • Modelling and Visualising Information Manufacturing Systems
  • Information Risk Management
  • Data Integration and Value Creation
  • Analytical IS and Value Creation

Information Value Management in following areas includes:

  • Industry 4.0
  • Digital Retail
  • Smart Energy
  • Smart Transport
  • Smart Homes
  • Smart Tourism
  • Digital Factory
  • Safety Critical Systems
  • Digital Defense
  • Public Safety and Security


Important Dates

Conference

Regular Papers
Paper Submission: October 18, 2017
Authors Notification: December 19, 2017
Camera Ready and Registration: January 4, 2018

Position Papers
Paper Submission: November 22, 2017
Authors Notification: January 11, 2018
Camera Ready and Registration: January 24, 2018

Workshops
Workshop Proposal: November 3, 2017
Paper Submission: January 11, 2018
Authors Notification: January 25, 2018
Camera Ready and Registration: February 2, 2018

Doctoral Consortium
Paper Submission: January 15, 2018
Authors Notification: January 26, 2018
Camera Ready and Registration: February 7, 2018

Special Sessions
Special Session Proposal: November 3, 2017
Paper Submission: January 11, 2018
Authors Notification: January 25, 2018
Camera Ready and Registration: February 2, 2018

Tutorials
Tutorial Proposal: January 30, 2018

Demos
Demo Proposal: January 30, 2018

Panels
Panel Proposal: January 30, 2018

Open Communications
Paper Submission: January 15, 2018
Authors Notification: January 26, 2018
Camera Ready and Registration: February 7, 2018


Keynote Lectures

Decision Guidance Systems and Applications to Manufacturing, Power Grids, Supply Chain and IoT
Alexander Brodsky, George Mason University, United States

Available soon
Plamen Angelov, Lancaster University, United Kingdom

Available Soon
Salvatore Distefano, Università degli Studi di Messina, Italy


Decision Guidance Systems and Applications to Manufacturing, Power Grids, Supply Chain and IoT




Alexander Brodsky
George Mason University
United States



Brief Bio
Alex Brodsky is Professor in the department of Computer Science and Director of the Masters of Science Degree in Information Systems at George Mason University. He teaches classes in Database Management and Decision Guidance Systems, graduated 15 PhD students and currently advises other four. Alex’s current research interests include Decision Support, Guidance and Optimization (DSGO) systems; and DSGO applications, including to Energy, Power, Manufacturing, Sustainability and Supply Chain. He earned his Ph.D. and prior degrees in Computer Science and/or Mathematics from the Hebrew University of Jerusalem.
Alex has published over 115 refereed papers, including five that received Best Paper Awards, in scholarly peer-reviewed journals, books and conference/workshop proceedings. For his research work related to DSGO systems, Alex received a National Science Foundation (NSF) CAREER Award, NSF Research Initiation Award, and funding from the Office of Naval Research (ONR), National Aeronautics and Space Administration (NASA), National Institute of Standards and Technology (NIST), and Dominion Virginia Power.
Alex serves/ed in leadership roles in research conferences, including as Conference Chair of IEEE International Conference on Tools with Artificial Intelligence (ICTAI-2017); Program Chair of IEEE International Conference on Tools with Artificial Intelligence (ICTAI-2013); Program Co-chair of the IEEE ICDE workshop on Data-Driven Decision Guidance and Support Systems (DGSS 2012, and DGSS 2013); General Vice Co-chair of the IEEE International Conference on Data Engineering (ICDE 2012); and Conference Chair of the Fifth International Conference on Principles and Practice of Constraint Programming (CP99).
Prior to joining Mason in 1993, Alex worked at IBM T.J. Watson Research Center, at Israel Aircraft Industries and was an R&D officer in the Computer Division of Communications, Electronics and Computer Corps, Israel Defense Forces. He also has start-up and commercialization experience, and is a member of ACM, IEEE, INFORMS and INSTICC.


Abstract
Decision Support Systems (DSS) are widely used to support organizational and personal decision-making in diverse areas such as engineering systems, finance, business, economics and public policy. They are becoming increasingly critical with the information overload from the Internet. While the scope of DSS is broad, Decision Guidance Systems (DGS) are a class of DSS geared to elicit knowledge from domain experts and provide actionable recommendations to human decision-makers, with the goal of arriving at the best possible course of action.
Currently, the practice of building Decision Guidance (DG) Systems resembles developing database applications decades ago before the invention of the relational Database Management Systems (DBMS). DG applications are typically one-off and hard-wired to specific problems; require significant interdisciplinary expertise to build; are highly complex and costly; and are not extensible, modifiable, or reusable. Therefore, a paradigm shift for the development of DG systems is needed. The key idea is to introduce and develop Decision Guidance Management Systems (DGMS), which would allow fast and easily-extensible development of DG applications, similar to easy development of DB applications using DBMS.
In this talk I will overview research toward this goal, including the recently developed Unity DGMS, and exemplify its use in the area of manufacturing, energy and power. I will also discuss ideas on how to use the emerging DGMS technology to translate the potential and multibillion dollar investment in Internet of Things (IoT) into business value, e.g., through (1) better predictability of demand and inventory visibility, (2) better tracking and efficiency of equipment and operating assets (3) accelerated innovation and product support, (4) improved alignment and collaboration among business functions and (5) sustainability and quality through visibility to energy and resource consumption.

Keynote Lecture




Plamen Angelov
Lancaster University
United Kingdom



Brief Bio
Dr Plamen Angelov, is a Reader in Computational Intelligence and coordinator of the Intelligent Systems Research at Infolab21, Lancaster University, UK. He is a Senior Member of the IEEE and Chair of two Technical Committees (TC); TC on Standards, Computational Intelligence Society and TC on Evolving Intelligent Systems, Systems, Man and Cybernetics Society. He is also a member of the UK Autonomous Systems National TC, of the Autonomous Systems Study Group, NorthWest Science Council, UK and of the Autonomous Systems Network of the Society of British Aerospace Companies. He is a very active academic and researcher who authored or co-authored over 150 peer reviewed publications in leading journals (50+) peer-reviewed conference proceedings, a patent, a research monograph, a number of edited books, and has an active research portfolio in the area of computational intelligence and autonomous system modelling, identification, and machine learning. He has internationally recognised pioneering results into on-line and evolving methodologies and algorithms for knowledge extraction in the form of human-intelligible fuzzy rule-based systems and autonomous machine learning. Dr. Angelov is also a very active researcher leading projects funded by EPSRC, ASHRAE-USA, EC FP6 and 7, The Royal Society, Nuffield Foundation, DTI/DBIS, MoD, industry (BAE Systems, 4S Information Systems, Sagem/SAFRAN, United Aircraft Corporation and Concern Avionica, NLR, etc.). His research contributes to the competitiveness of the industry, defence and quality of life through projects, such as the ASTRAEA project - a £32M (phase I and £30M phase II) programme, in which Dr. Angelov led projects on Collision Avoidance (£150K, 2006/08), and Adaptive Routeing (£75K; 2006/08). The work on this project was recognised by 'The Engineer Innovation and Technology 2008 Award in two categories: i) Aerospace and Defence and ii) The Special Award. Other examples of research that has direct impact on the competitiveness of UK industry and quality of life are the BAE Systems-funded project on Sense and Avoid (principal investigator, £66K; 2006/07), BAE funded project on UAS Passive Sense, Detect and Avoid Algorithm Development (£24K consultancy, a part of ASTRAEA-II, 2009), the BAE Systems-funded project (co-investigator, £44K, 2008) on UAV Safety Support, EC-funded project (€1.3M, co-investigator) on Safety (and maintenance) improvement trough automated flight data Analysis, the Ministry of Defence funded projects ('Multi-source Intelligence: STAKE: Real-time Spatio-Temporal Analysis and Knowledge Extraction through Evolving Clustering', £30K, principal investigator, 2011 and Assisted Carriage: Intelligent Leader-follower algorithms for ground platforms, £42K, 2009 which developed unmanned ground-based vehicle prototype taken further by Boeing-UK in a demonstrator programme in 2009-11), so called 'innovation vouchers by the North-West Development Agency-UK and Autonomous Vehicles International Ltd. (£10K, 2010, principal investigator), MBDA-led project on Algorithms for automatic feature extraction and object classification from aerial images (£56K, 2010) funded by the French and British defence ministries. Dr. Angelov is also the founding Editor-in-Chief of the Springer's journal on Evolving Systems and serves as an Associate Editor of several other international journals. He also Chairs annual conferences organised by IEEE, acts as Visiting Professor (2005, Brazil; 2007, Germany; 2010, Spain) regularly gives invited and plenary talks at leading companies (Ford, The Dow Chemical, USA; QinetiQ, BAE Systems, Thales, etc.) and universities (Michigan, USA; Delft, the Netherlands; Leuven, Belgium, Linz, Austria, Campinas, Brazil, Wolfenbuettel, Germany, etc). More information can be found at www.lancs.ac.uk/staff/angelov.



Keynote Lecture




Salvatore Distefano
Università degli Studi di Messina
Italy



Brief Bio
Salvatore Distefano is an Associate Professor at University of Messina, Italy, and Fellow Professor at Kazan Federal University, head of the Social and Urban Computing Group and of the Cisco Innovation Center in Kazan. He was formerly an Assistant Professor at Politecnico di Milano (2011-2015). In 2001 he got the master degree in Computer Engineering from University of Catania, and then, in 2006, he received the PhD degree on Computer Science and Engineering from University of Messina.
He authored and co-authored more than 170 scientific papers and contributions to international journals, conferences and books.
He took part to several national and international projects, such as Reservoir, Vision (EU FP7), SMSCOM (EU FP7 ERC Advanced Grant), Beacon, IoT-Open.EU (EU H2020).
He is a member of international conference committees and he is in the editorial boards of IEEE Transactions on Dependable and Secure Computing, International Journal of Performability Engineering, Journal of Cloud Computing, International Journal of Engineering and Industries, International Journal of Big Data, International Journal of Computer Science & Information Technology Applications, International Journal of Distributed Sensor Networks.
He has also acted as guest editors for special issues of the Journal of Risk and Reliability, Journal of Performability Engineering, ACM Performance Evaluation Review and IEEE Transactions on Dependable and Secure Computing
His main research interests include non-Markovian modelling; performance and reliability evaluation; dependability; Quality of Service/Experience; Service Level Agreement; Parallel and Distributed Computing, Grid, Cloud, Autonomic, Volunteer, Crowd, Edge, Fog Computing; Internet of Things; Smart Cities; Swarm and collective intelligence; Big Data; Software and Service Engineering. During his research activity, he contributed to the development of several tools such as WebSPN, ArgoPerformance, GS3 and Stack4Things.
He is also one of the co-founder of the SmartMe.io start up, a spin-off of the University of Messina established in 2017.


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Rua São Fernando, 5

9100-173 Santa Cruz

Portugal

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