Established in 1968, the Hawaii International Conference on System Sciences (HICSS) today is one of the top global conferences in the field of Information Systems and Information Technology. Organized by the University of Hawaii, the conference provides a highly interactive environment for top scholars from academia and the industry from over 60 countries to exchange ideas and discuss latest research. HICSS built a special reputation for being the "place to be" to discuss the latest and upcoming topics in the field.
All conference track consists of minitracks that emphasize discussion and interaction in a workshop-like way. Our minitrack on "Data Spaces for Sustainability and Resilience in Manufacturing" is part of the long-standing Internet and the Digital Economy track.
All papers presented at the HICSS are archived and disseminated through ScholarSpace (open access). They are also made available in the digital library of the Association for Information Systems (AIS). According to the AIS, HICSS ranked second in citation ranking among 18 Information Systems conferences, ranked third in value among 13 Management Information Systems conferences, and ranked second in conference rating among 11 IS conferences.
Industry has a particular responsibility to shape the transformation from our current economy into an ecologically and socially sustainable one. Additionally, the COVID-19 pandemic demonstrates how unexpected events can disrupt entire global logistics chains in short time. The resulting demand for change, combining sustainability and resilience aspects, poses enormous challenges for industrial production.
At the same time, the ongoing digitalization and networking of industrial value chains – summarized as the fourth industrial revolution or Industry 4.0 – offer new opportunities and capabilities to reach these objectives. We see sustainability as a driver of structural change: In parallel to our current digital transformation, we need a sustainability transformation of today’s value creation and production models into future-proof resilient approaches.
The objective of this minitrack is to foster a discussion how new information & communication systems can foster sustainability and resilience in the next generation of production systems. Data-enriched views on processes and an increasing information capability (in real-time, complete, distributed) are the underlying principles of improving the efficiency of processes and avoiding waste over the complete life cycle of products and industrial assets. Refer to the Technical Background Section below for a deeper discussion of the corresponding information architecture.
In this minitrack, we aim to provide a forum for researchers and practitioners to discuss novel approaches in dealing with sustainability through resilient information systems and connected data spaces. Particularly, we invite submissions that discuss cross-organizational aspects of data sharing, e.g., to enable analyzing issues of sustainability and resilience across entire value chains. Areas of focus and interest of this minitrack include, but are not limited to:
The objective of this minitrack is to explore how new information & communication systems can foster sustainability and resilience in the next generation of production systems. A main driver of this vision are digital twins (digital shadows), i.e. task- and context-dependent, purpose-driven, aggregated, multi-perspective, and persistent datasets. Digital twins provide multi-modal views with task-specific granularity provide high performance, low latency, security, and privacy at the same time. They enable radically new kinds of production and engineering applications.
Data-enriched views on processes and an increasing information capability (in real-time, complete, distributed) are the underlying principles of improving the efficiency of processes and avoiding waste over the complete life cycle of products and industrial assets. A main enabler in this regard is cross-company data spaces. They link classic “data silos” even across company boundaries. Supported by a combination of optimization, simulation, artificial intelligence and machine learning, new insights can be created. Sustainable production models utilize these data spaces to make information transparency a central part of their value proposition. In this way, they foster organizational decision making for more sustainable value creation.
Digital twins could become "sustainability twins", i.e. digital models that are networked with the real products, and provide information about performance, repair requirements, and possibilities for more efficient use. The sustainability twin continuously improves operations, adapts the product or asset to the performance actually required, and provides important insights for a more sustainable engineering of the next product generation. Process mining and corresponding data analytics are a core enabler in this regard.
Reducing resource consumption and making existing production setups more efficient are just the beginning. We also need new business models enabled by these data spaces, which focus on prosperity with resource recovery instead of conventional growth with just less resource consumption. While increasing efficiency of existing systems is undisputedly important, a true dual paradigm shift is required: Digitization and sustainability must either move into the center of the value proposition, or sustainability must be generated from a digital value creation structure itself. An example for the former are digital platforms for second-hand goods, an example for the latter "as-a-service" models, where value creation shifts from the production of a good to its usage stage.
These new production and business models achieve sustainability and resilience with value co-creation and value sharing in cross-company, open ecosystems. This requires data not just on final products, but also on semi-finished goods, raw materials, production processes, transportation, usage, and disposal or refurbishment. While building a data space enabling this visibility is technically feasible today, it is difficult to motivate all actors to share the data required – all too often, a lack of willingness to share and use data is preventing best-case scenarios. Corresponding governance structures are an essential component of sustainable business models – but there still is little knowledge how to define and utilize such governance structures fostering openness and data sovereignty.
With our minitrack, we aim to provide a forum for researchers and practitioners to discuss novel approaches in dealing with sustainability through resilient information systems and connected data spaces. Particularly, we invite submissions that discuss cross-organizational aspects of data sharing, e.g., to enable analyzing issues of sustainability and resilience across entire value chains.
We refer to some of recent papers by the minitrack organizers for more background about the topics that we aim to discuss in this minitrack.
Becker, F., Bibow, P., Dalibor, M., Jarke, M. et al. (2021). A conceptual model for digital shadows in industry and its application. Proceedings of the International Conference on Conceptual Modeling. Springer, 271-281. https://doi.org/hg45
Brauner, P., Brillowski, F., Dammers, H., Königs, P., Kordtomeikel, F., Petruck, H., Schaar, A. K., Schmitz, S., Steuer-Dankert, L., Mertens, A., Gries, T., Leicht-Scholten, C., Nagel, S., Nitsch, V., & Ziefle, M. (2020, July). A Research Framework for Human Aspects in the Internet of Production–An Intra-company Perspective. In International Conference on Applied Human Factors and Ergonomics (pp. 3-17). Springer, Cham. https://doi.org/hhn8
Brauner, P., Dalibor, M., Jarke, M., Kunze, I., Koren, I., Lakemeyer, G., Liebenberg, M., Michael, J., Pennekamp, J., Quix, C., Rumpe, B., van der Aalst, W., Wehrle, K., Wortmann, A., & Ziefle, M. (2022). A Computer Science Perspective on Digital Transformation in Production. ACM Transactions on Internet of Things. https://doi.org/hg56
Cappiello, C., Gal, A., Jarke, M., & Rehof, J. (2020). Data ecosystems: sovereign data ex-change among organizations (Dagstuhl Seminar 19391). Dagstuhl Reports, 9(9), 66-134. https://doi.org/hhk5
ElMaraghy, H., Monostori, L., Schuh, G., & ElMaraghy, W. (2021). Evolution and future of manufacturing systems. CIRP Annals, 70(2), 635-658. https://doi.org/gn4t4r
ElMaraghy, H. A., Youssef, A. M., Marzouk, A. M., & ElMaraghy, W. H. (2017). Energy use analysis and local benchmarking of manufacturing lines. Journal of Cleaner Production, 163, 36-48. https://doi.org/10.1016/j.jclepro.2015.12.026
Galizia, F. G., ElMaraghy, W., ElMaraghy, H., Bortolini, M., & Mora, C. (2019). The evolution of molds in manufacturing: from rigid to flexible. Procedia Manufacturing, 33, 319-326. https://doi.org/10.1016/j.promfg.2019.04.039
Liebenberg, M., & Jarke, M. (2020). Information Systems Engineering with Digital Shadows: Concept and Case Studies. In: Dustdar S., Yu E., Salinesi C., Rieu D., Pant V. (eds) Advanced Information Systems Engineering. CaiSE 2020. Lecture Notes in Computer Science, Vol. 12127. Springer, Cham. https://doi.org/hhph
Otto, B., & Jarke, M. (2019). Designing a multi-sided data platform: findings from the Inter-national Data Spaces case. Electronic Markets, 29(4), 561-580. https://doi.org/ggqvq9
Piller, F.,T., et al. (2022). Industry 4.0 and sustainability: How digital business models foster sustainability in industry. Position paper of the German Stakeholder Platform Industrie 4.0. Berlin: 2020. https://doi.org/hhk6
Piller, F., Falk, S. et al. (2020). Ten propositions on the future of digital business models for Industry 4.0 in the post-corona economy. Position paper of the German Stakeholder Platform Industrie 4.0. Berlin: 2020. https://doi.org/hhpq
Van Dyck, M., Lüttgens, D., Piller, F., & Diener, K. (2021). Positioning strategies in emerging industrial ecosystems for Industry 4.0. Proceedings of the 54th Hawaii International Conference on System Sciences, January 2021; 6153-6162. https://doi.org/10.24251/HICSS.2021.743
All submissions must conform to the HICSS format (i.e., double-column, no more than ten pages, etc.). When submitting your paper, make sure that you select the right minitrack with the Internet and the Digital Economy track. Please kindly refer to the official HICSS website for detailed author guidelines and all updated dates.
The submission system opens on April 15 and closes on June 15, 2022.HICSS-56 Author Instructions
This minitrack is supported by the Cluster of Excellence “Internet of Production”, funded by the DFG (German Research Council, Project ID 390 621 612).
In the interdisciplinary research cluster Internet of Production (IoP) at RWTH Aachen University, about 100 researchers on all career levels from mechanical and plastics engineering, material science, humanities, management, and computer science have been working on the vision of a new level of cross-domain collaboration along the entire product life cycles from engineering, operations, and usage. The IoP pursues a vision of a connected industry, in which processes, factories, and even organizations can learn from each other by sharing experiences and knowledge.