On the 28th of April 2020 we held our Swiss Alliance for Data-Intensive Services Match-Making event. Due to the current situation we hosted the meeting on an online platform, finding matches virtually.
Through the Match-Making events we want to provide a platform for our members to come together to share their project ideas and challenges and to find appropriate partners. The Alliance is an excellent place to do this with all the various expertise our members have. This event also gives start-ups the opportunity to communicate and to match with our members.
This time, we were joined in our conference platform by some 20 participants from academia and the industry. Four academic institutions and four companies pitched their ideas within a three-minute time frame. We got to hear about a wide range of inspiring projects, from data ethics to language analysis, law and sustainability, all with their own unique and interesting vision.
We then broke out into different rooms hosted by each pitcher respectively, where the participants could do a quick deep dive into the topics in order to get a better understanding of where the pitchers needed help or what kind partnerships they were looking for.
The event was a success, there were some concrete plans for further collaborations. We hope that some fruitful partnerships were matched and that we can share a success story in the near future.
If you have a project where you need collaborators or partners, please send an mail to Gundula to set up a Call for Participation. We look forward to continuing mixing and matching!
The main part of the meeting consisted in an update regarding the work for the new “Data Ethics Codex” of the Alliance. Markus Christen clarified that the Codex is actually a whole “bundle” of the following documents:
– Codex Overview Poster – A “Foundation” document outlining structure and values – A “Recommendation” document that includes the concrete recommendations including cases outlining how one can implement those recommendations – A “Implementation guide” outlining how the Codex can be integrated into the business processes of companies – A “Background” document providing further information for interested persons like e.g. relation of the Codex to other codes.
Members of the expert group provided final input to the “Foundation” and “Recommendation” document that now will be finalized. Members of the expert group will provide input to the case descriptions that will be finalized in the next 4-6 weeks.
A graphics designer is currently working on a standardized graphics language that will be used for all documents. It also has been decided that the documents (with exception of the “Background” document that will only be available in English) will be made available in German, English, French and Italian. The documents will be made public using a Common Creative License (non-commercial use only, no changes allowed).
The dissemination is planned for fall 2020. The expert group is currently evaluating optimal dissemination channels.
Other points discussed in the meeting were the following:
Data Ethics training: Christian Hauser presents his idea of creating a data ethics training. This should be realized in an Innsuisse funded project in cooperation with companies. SBB is already on board.
How to set up a data board: Karin Lange reports about the Mobiliar attempts to collect knowledge and best practices on how to set up a data board in companies (e.g. whom to involve, which questions to discuss, …). First contacts have been made (SAP, Swisscom, Cornelia Diethelm).
Common activity of “Data Ethics” Expert Group and “Data Sharing” Expert Group of the Alliance: The Data Ethics Expert Group will make contact to the data sharing group for exploring potential collaborations.
Data Ethics and Data Sharing for fighting against COVID-19: Michele Loi gave a short pitch about the moral issues in data-based approaches for fighting COVID-19 (in particular contact tracing). What are the ethical issues for or against such attempts, and what would be ethical requirements for creating such solutions? He argues that the collected expertise of our group is exceptionally suited to discuss this issue. It is planned to perform a survey within the Expert Group for collecting the most important issues around this topic.
ExoLabs’ mission is to provide unique data products as well as software as a service in the field of Earth observation (EO). As a value-added services (VAS) provider, we turn satellite, airborne and drone data into meaningful information our clients can trust and act upon. ExoLabs was founded in 2017 as a spin-off of the Remote Sensing Laboratories of the University of Zurich.
Forest Monitoring based on data from airborne laser scanning and commercial satellite missions
Why is it good that ExoLabs exists?
The increasing demand for data, improvements in technology, the evolution of spatial and temporal high-resolution data, and the awareness of satellite-based products has led to a growth of the EO market. However, many potential users of EO products lack the expertise to gather, process and analyze the required data for their specific needs. In addition, the increasing data availability poses new challenges to the traditional way of data analysis relying on individual computers. These barriers of required expert knowledge and big data processing abilities and facilities prevent many potential users from exploiting the wealth of EO data. In this context, ExoLabs is providing expert solutions for user specific needs based on EO data. To overcome big data challenges, we exploit machine learning algorithms and utilize cloud computing facilities to carry out advanced data analysis on local to global scales.
Who could profit from your services and products?
Earth is changing. And changes in environmental conditions, in particular, affect most of the world’s population. Accordingly, not only policymakers but also industry need to adapt to these changes and need to develop strategies to monitor environmental processes. For this it is essential to know where on Earth changes occur or will occur, what kind of changes will happen and to what extent the changes take place.
Can you give specific examples?
Mining companies strive to explore new and monitor existing sites, insurance companies need to evaluate claims, and financial service companies have to check on potential investment locations and monitor their assets. Furthermore, for commodity traders as well as the tourism sector information that is as up-to-date and spatially accurate as possible is indispensable. In the energy sector, and in Switzerland of course especially related to hydropower, reliable and quantifiable information on natural resources (i.e. snow and the water contained therein) are essential for efficient water management. For all these markets, we provide satellite-based and objective data, from daily updated maps of snow depths, to weekly crop monitoring, to time series analyses, to map changes in land cover and land use in the past decades.
ExoLabs’ crop monitoring based on freely available satellite data.
What are customized end-to-end solutions? Who are your customers?
With our intelligent software solutions and data products we improve business intelligence through tailored solutions and seamless user experience. Our customers can decide if they want to have access to ready-to-use data products (via their preferred API), if they want to have a configurable cloud computing environment to enhance these data products with their own data, or if they want to get the source code to freely integrate the software into their existing infrastructure. For all these services, we provide comprehensive consulting and service – and very important, we always inform about the limitations of Earth observation services (i.e. inaccuracies/uncertainties), because unfortunately the power of Earth observation is often over-sold. Our clients include global leaders in tourism and insurance, national and international research institutions, federal authorities and Swiss companies from the energy sector.
Daily snow depth monitoring.
What is the future of your services and products?
In the future, we will make the various methods and applications that we have developed and will continue to develop in the individual projects available to customers on a uniform platform. This will create synergies in data management and processing costs and thus also lead to cost reductions for customers.
In what ways could your research help the world?
In the context of the United Nations’ sustainable development goals (SDGs), we can achieve an impact with our products in many areas. In particular our environmental products, such as the daily snow monitoring, enable positive impacts in the areas of renewable energy (e.g. hydropower assets – SDG 7, 9), food supply (e.g. water management for agriculture – SDG 2, 13, 15) or decision support for adaptation strategies to climate change (e.g. winter tourism – SDG 13) by providing comprehensive and quantifiable information on a global scale.
GIF: Snow depth assessment to improve water management for hydro power.
DEEP – Deep learning for snow-monitoring: What can it do? How can it help?
Reliable information on the spatial distribution of snow in mountain ranges are critical for risk assessment, outdoor activities, and water resource management. These water resources from snowmelt are indispensable as they provide drinking water, supply crop production and generate hydroelectric power worldwide. Accurate estimates of snow quantities in space and time are the most important unsolved problem in mountain hydrology. In the Innosuisse project Deep Snow, we aim to develop – together with the ETHZ EcoVision Lab, the SLF, MountaiNow and Outdooractive – novel snow products for Switzerland based on multiple EO datasets and deep learning algorithms. Our objective is to provide seamless, timely information on snow cover, snow depth and snow water equivalent on a daily basis in a high spatial resolution (20 m pixel spacing) via multiple data services and outperforming current standards (weekly information with 1 km pixel spacing) and enable new market opportunities. These include improved outdoor safety standards, hydropower production planning and real-time snow risk assessment among others.
Snow monitoring: left – current standards (weekly updated), right – ExoLabs solution (daily updated)
The 8th meeting of the expert group “Blockchain Technology in Supply Chain Management” was split into two parts.
During the first part, the members were informed about how the future of the expert group will look like since the current program will expire at the end of 2020. First, it was emphasized that the Swiss Alliance for Data-Intensive Services will continue with the current format. Secondly, the current topic leaders explained that there is a new format called “NTN Innovation Booster”. The booster aims at promoting science-based innovation in collaboration with companies, universities, and society. This should happen by creating design thinking workshops for companies, customers and experts. The result of the workshops is the creation and development of ideas, which will be reviewed by a consortium. If an idea is promising the consortium will fund it and its further development will be supported. The current topic leaders elaborated that they applied for an innovation booster called “Decentralised Value Chains”, which promotes areas such as self-sovereign identities, economy of things and cross-company processes.
For the second part, we invited Thomas Locher and Sebastian Obermeier to present their paper called “When Can a Distributed Ledger Replace a Trusted Third Party?”. The paper examines on an abstract level how distributed ledgers work and dissect them by identifying key components. Moreover, they identify two fundamental criteria that must be met for ledger-based use cases. They continued by examining currently well-known use cases such as inter-bank payments, supply chains management or microgrid energy trading accordingly to those fundamental criteria and explained, to which extent the use cases meet them. After their presentation, the expert groups discussed the presentation and the paper’s results. The diverse experiences and opinions of the expert groups enlivened the discussion. Overall, it helped everybody to gain a better understanding of distributed ledger and the role of trust within them.
The meeting was concluded with an apéro, where further ideas were exchanged.
The conference focused on two themes: predictive maintenance & smart services. We gained insights on how to create and improve smart maintenance, and how valuable it can be to integrate different data sources in this process.
The switch to smart (micro) services is the new big thing and shows that Industry 4.0 is growing and maturing. Smart micro services provide people with tools to get their jobs done better, faster, with less errors and more efficiency – in many different industrial areas, be it national infrastructure, wind-made electricity or technical facility management. It’s all about data, and new technologies to transmit data will bring groundbreaking, applicable innovations.
At the conference the experts presented many practical examples of predictive maintenance, such as a smartphone-app which supports the technical facility management or smart services from the asset management perspective. Industry 4.0 is happening right now and it is already changing the ways we work and optimize our processes.
In addition to all the innovative projects, the focus during the conference has always been on connecting to the real life of individuals, how smart services can make it easier for them and how they can create real added value.
The speakers and their topics:
Dr. Lilach Goren Huber from the ZHAW School of Engineering discussed the notion of intelligent maintenance as an R&D process, needed for the implementation of data-driven algorithms for early fault detection, diagnosis and prognosis. Through a concrete use case of machine learning based fault detection and diagnosis in wind turbines, she explained what some of the typical challenges are that data scientists face on their way to develop intelligent maintenance algorithms, and how these can be overcome using novel methods in applied research.
It was exciting and refreshing to witness the curiosity and readiness of many of the participants towards implementing smart maintenance solutions in their companies.
Yvan Jacquat from GradeSens and Dr. Marc Tesch from LeanBI showed how Plug & Play applications in the area of condition monitoring and predictive maintenance already are possible today– with E2E solutions (from wireless sensors to data analysis) in sophisticated applications, such as robotic and wind turbines.
Nevertheless, some applications are still too complex for pure Plug & Play applications. Here, however, impressive use cases demonstrated that predictive maintenance can nevertheless create a high benefit. Such projects are also worthwhile and demonstrably successful. The journey towards complete Plug & Play continues.
Noser Engineering AG talked about the technical facility management, which they developed together with their partners from Nose Design AG and Sigren Engineering AG.
Severin Zahler, Software Engineer for Noser Engineering, has given a live demo with all the functions and advantages of the mobile application.
Dr. Shaun West from Hochschule Luzern held a presentation based on use cases that showed multi-actor or partner value creation. The CAT case based on a 2010 video of their platform, which helps worksite managers to operate and support maintenance.
Dr. West used a Vodafone/coffee use case to show how an OEM could support their dealers and restaurants with Industry 4.0-based services, a thought-provoking use case when designing Smart Services because of the way it focuses on the problems that individuals really have and where they need support.
Dr. Bernd Reimann from Hexagon elaborated on the “why? what? how? and whereto?” of some of the technologies developed and provided by Hexagon and its Innovation Hub that expedite digital transformation such as edge, connectivity, cloud, mobile, and AI.
Several real-world examples of this transformational journey have been presented, starting with R&D projects and leading towards smart services (and interesting findings on the way).
Reto Amstad from Siemens Digital Enterprise Services demonstrated individualized dashboards for different people to help them to get their jobs done in a very simple form. The approach of Siemens shows the integration of lean with digital in the Smart Factory environment.
By combining lean and digital, he showed how it is possible to improve productivity while reducing costs. The application of lean thinking (small agile projects) focused on actual problems and to build micro-services within a broader framework is highly effective. Siemens was using Mindscape in the use case example with integration into the MES; however, any Industry 4.0 platform would be able to support the analytics.
Many thanks to our members and experts for sharing their experience with the audience, especially ZHAW and HSLU for all scientific insights, Hexagon, Lean BI & GrandeSens, Noser Engineering and Siemens for the practical examples. And a big thank you to Easyfairs for making the Smart Maintenance Conference 2020 possible!
Everywhere we read and hear about digitization. But what is behind it? How does it create concrete value for customers and the company and which technologies are relevant when and how? To share knowledge and skills, we offer the well attended course CAS Data Product Design / Smart Service Engineering. To strengthen the conceptual skills acquired in the course, we are very happy that we can conduct an intensive two-day workshop in the highly inspiring spaces of the Mobiliar Forum Thun. Many thanks to Mobiliar for enabling this and to Ina Goller for the multiple moderation of the workshop.
The buzz word “digitization” has become an everyday term. Over the last few years, it has expanded into broad areas of society and the economy. As a result of digitization, large amounts of data have accumulated, e.g. from processes, from systems for managing customers (CRM) and resources (ERP), or from customer behavior on the Web or in social media. More recently, more and more data has been generated about networked products and systems. Behind this are technological drivers such as the cost-effective and broad availability of connectivity based on the Internet of Things (IoT), sensors and actuators or advanced analytics.
Against the background of these promising technological innovations, the focus on customer benefits is often neglected. Digitization projects often only aim to automate and increase the efficiency of processes. Customers benefit only indirectly from this. However, digitalization can have a direct impact on customer benefits and create better or new customer experiences if it is appropriately designed. However, the targeted collection and processing of data plays an important role. A successful implementation of data-based approaches must be designed from the customer’s point of view and at the same time exploit the potential of the new technologies.
□ Prior to the meeting, Christoph, Markus, Tom and Michele met to discuss the proposed changes to the data ethics codex. We have received 22 feedbacks, including 19 written feedbacks, 3 live interviews, and 18 feedbacks from companies within Alliance.
□ Our meeting was hosted by Peter Kolbe of SBB CFF FSS, in a building that is integrated within the structure of the Bern main station, where we could see trains moving on railways on the other side from our windows.
□ Peter Kolbe started the meeting by sharing with us some projects of SBB CFF FSS for using big data, the ethical issues they raise, and the procedures they set up to discuss these. Their ethics assessment workflow is (very roughly):
› 1. Describe the idea
› 2. Check the validity of the research questions (value for the company)
› 3. Privacy – legal check
› 4. Communication – check for added customer value, reputational consequences
□ We also discussed the question of an ethics of responsibility vs. a more utilitarian ethics and their impact on the companies’ ways of dealing with data.
□ We then presented a summary view of how we will modify the codex based on the feedback received.
□ Christian Hauser of HTW Chur presented his plan for a course to develop ethical motivation for companies. He asked the company representatives at the meeting to help him to identify those key figures in a company that could implement ethics if adequately motivated. The idea of this course will be developed as a project in the course of next year.
□ Another educational element was solicited by Karin Lange of Mobiliar: to develop case studies as teaching materials to explain the ethical codex in a practical way. It was discovered that some case studies have been developed already by Bruno Frischher of Luzern University of Applied science. Next year, Karin Lange, Michele Loi and Jean Gabriel Piguet will form a group to develop the case study further.
□ Beside the already mentioned educational projects, our plans for the next year are:
› Organizing and running the SDS conference in data scientist. We have already found a keynote for robust and trustworthy (ethical) AI, namely prof. Krishna P. Gummadi of the The Max Planck Institute For Software Systems of Saarbrücken
› Writing an implementation guide for our ethical codex, after running some implementation workshops with members of the Alliance, in the first quarter of 2020.
› Organizing an outreach event, which could be on the topic of the ethics of open data.
› Organizing an event on “how to set up a data ethics board” involving companies that have, or plan to build, one such ethics board.