Our thinking on data issues of management importance in refereed publications that go deeper than our short stories.
Dataspace = From Big Data to Better Data
Dataspace solves today's data and data analytics productivity problem. Dataspace ...
- is a shift from Big Data (high cost) to Better Data (higher returns) - providing the right data with relevant information content and quality (think: food labels for ingredients and nutritional value), and all in the right quantity
- is a peer-to-peer data communications network - not storage - and with data sovereignty protection so that you can exchange data and maintain control of the rights to your data at all times
- is a just-in-time, on-demand data supply chain of data products, like cross-organizational digital twins, to turbo-charge old apps or create new super-apps, such as product carbon footprint (PCF) tracking, battery pass, and material traceability for next level quality
What is a dataspace: Dataspace Top 10 2-pager, link
Why important:
(a) Our C-level 1-pager: From strategy to operations, link
(b) 3 initiatives for strategy: Schlueter Langdon, C., and C. Hort., 2022. How data sovereignty enables the next future of automotive – part 1. White Paper (2022-04-15), T-Systems, Frankfurt, link
(c) 3 steps for operations: Schlueter Langdon, C., and C. Hort. 2023. Winning with dataspaces like Catena-X: From Big Data to Better Data - part 2. White Paper (2023-04-18), T-Systems, Frankfurt, link
"Economics of Data" series: From symptoms to root cause to first solutions and dataspaces
“Data is information's ore” (Peter Drucker 1992) and has to be extracted, refined, mined for any value to emerge: Our series starts bottom up to lay out the challenges systematically … from “data is broken” (story #1) … to why (story #2) … to first solutions including data factories for data products (story #5) to dataspaces – what’s a dataspace (story #6)?
Peter Drucker. 1992. Be Data Literate - Know What to Know. The Wall Street Journal (1992-12-03), link
1. Data is broken: The data productivity crisis, link
2. Data: How to measure it? link
3. Data: Quantity or quality? link
4. Refining raw data for less bias, link
5. Data factories for data products, link
6. Dataspace, sovereignty, supermarket: An interview in IT Director, link
Dataspace use cases
Catena-X: First collaborative, open data ecosystem for the automotive industry, see "Data Move People"
Case study: RealLab Hamburg mobility super-app, see "Data Move People"
Industry & mobility (including Umati - Universal machine technology interface by VDW, the association of German machine tool factories):
Schlueter Langdon, C., and K. Schweichhart. 2022. Dataspaces: First Applications in Mobility and Industry. In: Otto, B. et al. (eds.). Dataspaces – Part IV Solutions & Applications. Springer Nature, Switzerland, link
Dataspace core technology & interoperability
Drees, H., S. Pretzsch, B. Heinke, D. Wang, and C. Schlueter Langdon. 2022. Dataspace Mesh: Interoperability of Mobility Dataspaces. Technical Paper ID 280, 14th ITS Europe Congress, Toulouse, link
What is data sovereignty: Lauf, F., S. Scheider, J. Bartsch, P. Herrmann, M. Radic, M. Rebbert, A. T. Nemat, C. Schlueter Langdon, R. Konrad, A. Sunyaev, and S. Meister. 2022. Linking Data Sovereignty and Data Economy: Arising Areas of Tension. Best Paper Award at the 17th International Conference on Wirtschaftsinformatik (WI22), link
The world’s first dataspace: Drees, H., D. O. Kubitza, J. Lipp, S. Pretzsch, and C. Schlueter Langdon. 2021. Mobility Dataspace – First Implementation and Business Opportunities. Technical Paper ID 909, 27th ITS World Congress, Hamburg, link
Data as a product
Staebler, M, F. Koester, and C. Schlueter Langdon. 2023. Towards solving ontological dissonance using network graphs. Proceedings of 29th Americas Conference on Information Systems, Panama (forthcoming)
Emerging data value chain: Schlueter Langdon, C., and R. Sikora. 2020. Creating a Data Factory for Data Products. In: Lang, K. R., J. J. Xu et al. (eds). Smart Business: Technology and Data Enabled Innovative Business Models and Practices. Springer Nature, Switzerland: 43-55, link
Data factory example: Sikora R., and C. Schlueter Langdon. 2019. Marketing to “Minorities”: Mitigating Class Imbalance Problems with Majority Voting Ensemble Learning. Frontiers of Marketing Data Science Journal (Fall): 27-33, link
Crosby, L., and C. Schlueter Langdon. 2019. Data as a Product to be Managed. Marketing News, American Marketing Association (October 10th), link
Data events
- Hub.Berlin: A minister, CEOs, startups – data for sustainability solutions, link
- Google new region Berlin: Better digital transformation and sovereignty, link
- Hannover Fair: Catena-X Dataspace goes live with Cofinity-X and beta phase, link
- ITS World Congress Los Angeles: IDSA & Gaia-X goes USA, link
- Market-X by Gaia-X Vienna: Launching GX clearing house services, link
- Data Natives Berlin: Telekom, IBM and IDSA on stage, link
A selection from our R&D
- NPM – National Platform Future of Mobility and Telekom, link
- A human digital twin with data sovereignty: Say hello to "DaWID", link
- Treat data like cars, link
- Video - Digital twin speeds it up – for example, a brake, link
- Space race to the future neighbourhood, link
- Video - Fleet capacity utilization with heatmap analytics, link
- T-Systems as pioneer: Implementing IDS, link
- 3 steps: AI best practice from experts, link
- 3 key learnings from data best practice, link
- From IoT to internet of production: In 100 days, link
