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Tag: Databooster

A New Opportunity: Open Innovation for “Construction & Data Science”

The construction industry has been undergoing a digital transformation, with data science playing an increasingly important role in improving efficiency, reducing costs, and enhancing safety. However, to fully realize its potential, it’s essential to promote open innovation and collaboration between data scientists and construction experts. 

For this purpose, the first open innovation workshop on “Construction & Data Science” was recently held in Zurich, Switzerland, bringing together 40 participants from both fields to explore the intersection of construction and data science. 

Findings

To improve cooperation between the construction industry and data science, the workshop formulated central key findings:

  • Focus on creating structured data sets across projects, teams, and companies and move away from managing data in CAD systems.
  • Don’t wait for new standards to be defined, learn to combine information from different sources and standards by mapping it.
  • Consider using other ways of pulling data from CAD tools, like Speckle or an IFC-based modeling tool like Blender.
  • Engage in open source or open data projects and learn from others, especially in rapidly evolving technology.

Check out sites like www.opensource.construction/ to proactively work towards changing the status quo and improving the industry.

The summary is also nicely put together in the Linkedin post by opensource.construction’s President, Maximilian Vomhof.

The Event
The workshop aimed to identify potential problems and solutions in this area and to promote open innovation and collaboration between data scientists and construction experts. In this blog post, you will find a report on the insights gained from the workshop and highlight the importance of open innovation in these industries.

The workshop was organized jointly by opensource.construction, bauen digital Schweiz, and the data innovation alliance at Amstein + Walthert in Oerlikon. After a short introduction to the Databooster program, the passive part for the participants was over!

The workshop was structured according to the double diamond framework from design thinking, which consists of four stages: discover, define, develop, and deliver. After the four groups got to know each other, they explored the problem space at the intersection of construction and data science or data engineering. In this phase, the focus was on generating a wide range of ideas and potential solutions by asking “why” questions and understanding the workings of the construction industry as a data scientist – essentially, “falling in love” with the problem.

At this workshop, “love” was certainly in the air, with many questions generated. Of these, five problems were identified as most relevant:

  • Optimized building scans
  • Open-source door planning configurator
  • Linked product data
  • GIS data linked with building laws
  • Open data environment for storing and linking element-independent information

In the second part of the workshop, powerful teams were formed around the ideas generated. They not only focused on potential solutions but also on related business cases, which added a practical, pragmatic dimension to the ideation process.

One of the solutions produced was standardization, particularly in the light of data formats. However, it was agreed that establishing standards and achieving consensus could take a long time – a luxury that the construction industry simply doesn’t have. It was essential to identify quick and effective solutions that could be implemented without major delay.

Despite the apero long being ready, the teams were still deeply engaged in finding innovative solutions that could be launched swiftly. The teams agreed to follow up on their ideas and continue pushing for change, possibly using the Innovation Booster Databooster, something we are particularly happy to hear. 

In conclusion, we believe that the Innovation Booster Databooster initiative is a valuable resource for teams to develop and implement their solutions generated using the double diamond design thinking structure. We look forward to seeing how these ideas will shape the future of construction and data science!

Expert Group Meeting – Natural Language Processing: Speech Processing

This Expert Meeting will take place at the ZHAW premises in Lagerstrasse 45, 8004 Zurich in room ZL O3.01 on the third floor (online participation is also possible for those who prefer this option) on Wednesday, May 10 from 17:30-19:00. After the meeting, there will be an apéro so that you can carry on your discussions and get to know each other.

We have the following two talks confirmed:

End-to-end ASR for Swiss German at Microsoft: A Transducer Approach
Oscar Koller, Applied Scientist at Microsoft

Automatic speech recognition (ASR) for Swiss German is a challenging task due to the lack of a standardized writing system and the high regional variability of the dialects. In this talk, we present our work on developing end-to-end ASR models for Swiss German at Microsoft using transducer architectures. We show that transducers outperform hybrid models by over 20% in word error rate on a multi-dialectal corpus of Swiss German speech. We also compare our models to Whisper, a state-of-the-art sequence-to-sequence model for low-resource ASR, and find that transducer models achieve comparable results with much smaller model size and training time. Finally, we discuss how end-to-end models produce transliterations of Swiss German words instead of standard German translations affecting the readability and usability of the output and propose solutions to this problem.

Revolutionizing Natural Interaction with Swiss German: A Glimpse into the Future of Conversational AI
Claudio Paonessa and Yanick Schraner, Researchers at FHNW

Get ready for a glimpse into the future of natural interaction with computer systems in Swiss German! We leveraged the latest advancements in speech-to-text and text-to-speech technology to create an engaging and interactive experience that showcases the results of our cutting-edge research.

Exploring the Acceptance of Intelligent Voice Assistants in Home Care Applications: Opportunities and Obstacles [10 mins presentation, 10 mins discussion]
Edith Birrer, Researcher at iHomeLab – HSLU (Hochschule Luzern)

In the scope of co-creation sessions, care workers provided insights on applications and on concerns about Intelligent Voice Assistants (IVA) in the home of their clients or patients. The sessions focused on the potential to support the care documentation process by IVA. Participants’ expectations and worries spanned from the ability to handle dialects, to confidentiality issues, to integration in existing care documentation systems. However, there is a general openness toward the idea to employ IVA as means to improve the quality of care. The challenge foreseen for using IVA is to become as time efficient as care documentation systems in place. Alternatively, as suggested by participants, IVA could complement existing processes or even create new ones in the care context.

If you want to join, please fill in the following registration form by April 27: https://forms.gle/PmRQENtY8aybJeby5
Please note that the registration form includes information for the SwissNLP General Assembly which is co-located.

Industrieforum 2025

Am 9. Mai trifft sich die Industrie 4.0-Community zur Jubiläumsausgabe in Brugg-Windisch. Zusammen mit rund 300 Teilnehmenden aus der verarbeitenden Industrie begrüssen wir neben 25 Ausstellern in der Experten-Expo unseren diesjährigen Keynote-Speaker, Thomas Zurbuchen, bis Ende 2022 Head of Science bei der NASA. Er wird mit Weitblick aus mehreren Raumfahrt-Missionen die Learnings zur Digitalisierung, Daten und Innovation für die Industrie aufzeigen.

Daneben zeigen weitere Expertinnen und Experten digitale und innovative Lösungsansätze für aktuelle Herausforderungen, wagen einen Blick in die Zukunft und abgerundet wird der Tag mit einem Reality-Check zu Industrie 4.0-Cases aus den zehn Ausgaben des «Industrieforum 2025» ab.

Auf der offiziellen Webseite finden Sie mehr Informationen.

Smart Maintenance Insights – Online Session

Am 27. April 2023 laden wir Sie sehr herzlich zu unseren Smart Maintenance Insights ein.

In Zusammenarbeit mit der data innovation alliance veranstaltet Easyfairs zum dritten Mal einen Online-Event kostenfrei.

Rund um das Fokusthema “Was bleibt nach dem Hype: Reale Smart Maintenance cases in der Umsetzung”, erwarten Sie zwei hochwertige Referate, welche Wissenschaft und Praxis zusammenbringen.

Bringen Sie sich auf das smarte Level und reservieren Sie sich einen kostenlosen Platz an unserer Online-Session vom 27. April 2023 von 10:00 – 11:00 Uhr.

Experts, Experts, Experts…

The Data Innovation Alliance’s second Expert Day in March 2023 was a hub of activity as experts from four key areas – Smart Maintenance, NLP & AI Technology, Spatial Data, and Smart Services – gathered to share their insights and mingle with researchers and industry professionals. The event kicked off with leaders from each Expert Group pre-discussing their plans for 2023, generating a wealth of innovative ideas for joint events and initiatives, and paving the way for exciting collaborations in the (near) future.

But that’s not all! The NLP and Digital Health groups are teaming up to bring you joint events that will revolutionize the way we approach data. And with the next Expert Day set for August 2023, featuring four expert groups once again, get ready for even more ground-breaking discussions and initiatives, organized jointly with other Innovation Boosters. Keep an eye on our events calendar for more information.

While the keynote speech may not have met expectations in terms of insights, it set the stage for what was to come – dynamic discussions and collaborations in the expert group break sessions. To ensure everyone had access to the wealth of information shared, short summaries of the discussions were written by participants in each room.

In short, the second Expert Day was a superb success, bringing together a diverse group of experts to debate their ideas and shape the future of data innovation.

Smart Services for Sustainability – Circular Servitization by Jürg Meierhofer

The Smart Services for Sustainability – Circular Servitization discussion was a dynamic conversation among highly experienced individuals from different industries. They explored how value is created in business ecosystems, focusing on both individual and organizational perspectives.

It was inspiring to have diverse industry representatives in the same room and to create a common understanding. Departing from economic value creation, the group extended its scope to ecological factors. An intense discussion arose about how environmental value can be created without negatively impacting economic value. Statements that economic value creation is still the predominant requirement were made, meaning that in many cases, even a slight reduction of economic value for the sake of ecological value would be treated with suspicion. As sustainability becomes increasingly relevant and regulations loom, the balance between economic and ecological value may shift in the near future.

Overall, the Smart Services for Sustainability – Circular Servitization discussion was thought-provoking and left participants eager to continue exploring the intersection of business and sustainability.

Spatial Data by Reik Leiterer

In a room buzzing with ideas, each data expert chimed into the discussion about the creation of a platform that would benefit cantons, individuals, and service providers. There was a shared understanding that it might not be possible to cater to everyone’s needs and that a simpler visualization and analytics approach may be the way forward. However, some uncertainties still remained, such as identifying where the necessary data is available and how it can be integrated, setting limits, and ensuring that data is not misinterpreted. Despite these challenges, the group remained enthusiastic about the potential benefits of the platform and is looking forward to overcoming these obstacles.

NLP & AI Technology by Lina Scarborough

The group opened the floor with how chatbots are great to answer questions, but what happens when users don’t know where to begin asking questions? This is a common issue in legal situations where the average client may not have the necessary background to understand what information is needed. Retrieval augmented language models like KATIE have emerged as a solution to this problem. These models use grounded reasoning and promote a chain of thought to handle complex queries and create a context for users who may not know what subset of questions to ask.

With the rise of machine-generated text, it’s becoming more difficult to distinguish between human and machine-generated content. While probabilistic token selection and frameworks like SCARECROW can help scrutinize machine-generated text, it can still be difficult, to nigh impossible, to identify. However, ChatGPTZero, an app that uses watermarking to create a statistical fingerprint in the sampling method, claims to be able to detect whether an essay is written by ChatGPT or a human – for instance, ChatGPT generally makes redundancy errors whereas humans make grammatical mistakes. This approach hopes to maintain the integrity of human-generated content in the face of increased machine-generated text.

The discussion then flowed into a lively and engaging presentation on how AI technology can make the tricky SQL “minefield” as easy to navigate as a soccer player scoring a goal – literally, by demonstrating SQL prompts on the soccer World Cup!

Smart Maintenance by Melanie Geiger

The five use case presentations highlighted the versatility of data technology in different applications, showcasing how it can be adapted to meet various needs. With input data ranging from domain knowledge to error log data, these use cases demonstrated how AI models can process and analyze complex data sets to provide valuable insights and decision support.

One of the key themes that emerged was the use of AI for diverse condition-based maintenance, specifically anomaly detection and fault diagnosis. By leveraging ML algorithms, these use cases were able to detect potential issues and predict equipment failures for timely maintenance and preventing downtime.

The highlight of the event was not only the apèro treats, but the opportunity to engage with the 60 participants and learn about their projects, challenges, solutions, and ideas for collaboration. Many attendees seemed to share this sentiment, as numerous participants were still engrossed in conversation at the end of the event, and some discussions had to be continued elsewhere. Those who wish to follow up on these conversations have the option to do so at SDS2023. On a more lowkey note, maybe you wanted to add someone on LinkedIn and send them a message. Here you go, this is your reminder!

Our conclusion of the event: the Alliance has many experts in various subtopics of data-driven value creation, but only together we can move faster.

SATW – Jahreskongress 2023

Versorgungssicherheit – technische Souveränität

Corona, Klimawandel, Krieg in der Ukraine. Verschiedene Krisen in letzter Zeit, die immer noch andauern, haben gezeigt, dass es nur wenig braucht, um die «Just in time»-Maxime ins Stolpern zu bringen. Es stellen sich wichtige Fragen darüber, wie es um unsere Versorgungssicherheit in vielen Bereichen steht und wie technisch souverän die Schweiz sein sollte. Dabei ist die Technik sehr oft sehr stark gefragt.

Am SATW-Jahreskongress suchen wir Antworten. Einerseits für «Energie»: So hat das Szenario einer Strommangellage Fragen rund um Versorgungssicherheit beim Umbau des Energiesystems in der Schweiz wieder vermehrt in den Fokus gerückt. Wie steht es um diese im Bereich Energieversorgung? Wie können wir diese kurz- und langfristig verbessern? Ist dies überhaupt nötig? Und anderseits für «Daten – künstliche Intelligenz»: Wie technisch souverän kann die Schweiz sein? Welche Abhängigkeiten von internationalen Playern müssen wir eingehen?

Seien Sie dabei. Der SATW-Jahreskongress richtet sich an Fachleuten aus Wissenschaft, Wirtschaft und von Behördenseite und ist kostenlos.

Finden Sie alle Informationen und die Anmeldung auf der offiziellen Webseite!

Project Day

The Innovation Booster Databooster is organizing the second Project Day, where previously supported innovation teams will present their projects and their developments in 2021/2022 to companies and interested partners.

These innovation teams and companies will share their insights and lessons learned: AI-Bridge, ascentys-ESG, DNEXT, endaprime, eraneos, maxon motors, peerdom, rewoso, TEK, ZHAW together with Tamedia and NZZ.

The presentation and discussion will address topics like sustainability and ESG measuring, Smart Services for complex energy systems, AI and Industry 4.0, Responsible AI, Data-based governance and organizations, data visualization for patients.

Schedule:
13:00 Registration
13:30 Welcome
13:40 Innovation Project Presentations + discussion + future thinking
15:30 Coffee break
16:00 Innovation Project Presentations + discussion
16:30 Summary
17:00 Apero

To register please use the form below. Seats are limited, early registration is recommended!

Service Event “Eating, Learning, Netzworking” – The digital ship

Key Speaker

Dr. sc. ETH Nikolas Schaal
Projectmanager Digital Shiptec AG

Shiptec is Switzerlands largest professional shipyard. I will present our digital solutions for captain and ship owner. Clear benefits as well as future plans are presented.



Please register using the form below. You can also find all information in the flyer!

Clinical Data Reuse – Promises or Problems?

Program

Welcome
Yana Yoncheva, IB Digital Health Nation & Dr. Gundula Heinatz Bürki, IB Databooster

Clinical Data Reuse – Promises or Problems? by Prof. Dr. Thomas Bürkle, Applied University of Bern, Professor for medical informatics

This part of the webinar will introduce in the topic of clinical data reuse with examples from large hospital environments e.g. integrating routine data into cancer registry or for research purposes and using genetic data for drug therapy decision support.
On a technical level, the tasks of integration and interoperability on technical, semantical and workflow level will be discussed and a critical retrospective of achievements and drawbacks will be presented.

Thomas Bürkle joined Bern University of Applied Sciences (BFH) as a professor for medical informatics in 2014. He teaches various medical informatics and interoperability subjects in Bachelor and Master level in Biel/Bienne and Zurich. His research interests include clinical decision support, information processing in intensive care, data reuse, workflow support and evaluation of healthcare IT. He was or is responsible for the research projects “Spital der Zukunft” and “Digi-care” (BFH-part).

Health Data Repository for Data Driven Clinical Research by Dr. Sebastiano Caprara, Balgrist University Hospital, Lead Digital Medical Unit

A paradigm shift toward electronic health records, and extension of these to include clinical research
datasets, is rapidly gaining momentum but requires effective interlinking of patient data. The main goal of the Health Data Repository – HDR – project is to develop a digital platform at the Balgrist University Hospital that can be modularly integrated in the flow of medical and research data within a hospital local digital environment, focusing on structured clinical data and research cohorts. The first step of our data integration approach aims at data harmonization between the hospital and its different departments. The HDR API (Application Programming Interface) layer is able to connect to multiple clinical IT systems, extract relevant data, map it to a target standard, and de-identify the data for research purposes. When queried from clinical systems, the data is mapped to standardized models, aligning it with ongoing national and international efforts in terms of terminology.
We aim to leverage standard data models and ontologies to improve research quality and facilitate academic collaborations, but we are also preparing the clinical IT infrastructure to facilitate the integration of innovative digital tools and data-driven medicine results in daily clinical processes.

Dr. Sebastiano Caprara received his PhD degree at the ETH Zurich with focus on machine learning and predictive models providing solutions for preoperative planning of spinal fusion surgery. He is currently leading the Health Data Repository project at the Balgrist University Hospital and establishing the Digital Medicine Unit. He is part of the digitalSwitzerland initiative representing Balgrist in the Digital Health Committee.

Q&A and Closing

Open Innovation Workshop «Construction & Data Science»

Bauen digital Schweiz / buildingSMART Switzerland, die data Innovation alliance sowie opensource.construction führen einen Open Innovation Workshop mit dem Thema «Construction & Data Science» durch. Dieser bringt Top- Expert:innen aus der Baubranche und der Data Science Community zusammen.

Der Workshop adressiert eine aktuelle Herausforderung in der Bauindustrie: die Datenqualität. Daten müssen über die gesamte Wertschöpfungskette, d.h. von Akquisition, Planung, Erstellung bis hin zum Betrieb durchgängig verfügbar sein und so strukturiert werden, dass mit aktuellen Ansätzen aus den Bereichen Data Analysis, Machine Learning und Artficial Intelligence Mehrwerte geschaffen werden können. 

Der Workshop bietet den Teilnehmern die Gelegenheit, disziplinübergreifende Projekte zu identifizieren und kreative Lösungsansätze zu entwickeln. Dafür werden zunächst die Herausforderungen in der Bauindustrie entlang einem typischen Projektablauf und einer Einführung zu den involvierten Stakeholdern erläutert. Die Teilnehmer aus der Bauindustrie bringen erste Ideen mit, die als Ankerpunkte für die Diskussion in kleinen Gruppen dienen und disziplinübergreifend weiterentwickelt werden. In einem Pitch werden die besten Vorschläge ausgewählt. Diese erhalten die Möglichkeit, im Rahmen des Innovation Booster Databooster die Ideen hin zu einem Projekt zu konkretisieren, dabei werden die Teams methodisch und finanziell mit bis zu CHF 25‘000 unterstützt.