October 15, 2024, by Stefan Keller, OST

Im ersten Vortrag von Pia Bereuter und einem Team der FHNW Muttenz wurde der GeoHarvester vorgestellt. Dabei handelt es sich um einen Proof-of-Concept einer einfach zu bedienenden, mehrsprachigen Online-Suchmaschine für Schweizer Geodienste mit offener API und offenem Quellcode. Der GeoHarvester adressiert das Problem des fehlenden zentralen Zugangs zu Geodiensten in der Schweiz. Die Qualität und Vollständigkeit der Metadaten variiert stark und die Aktualisierung der Indizes ist aufwändig. Ziel des Projekts ist die Entwicklung eines Portals mit API, das automatisierte Updates, eine Bewertung der Metadatenqualität sowie Filter- und Sortierfunktionen bietet. Technisch basiert der GeoHarvester auf Natural Language Processing, um Schlüsselwörter aus Metadaten zu extrahieren und die Ergebnisse in vier Sprachen (DE, FR, IT, EN) zu optimieren. Derzeit wird ein grosses Sprachmodell integriert, um die Suche weiter zu verbessern. Für die Zukunft sind eine räumliche Suche und automatische Updates der Datenquellen geplant.

Der zweite Vortrag von Ralph Straumann (EBP) beleuchtete den aktuellen Stand der Schweizer Geoinformationslandschaft sowie die Herausforderungen bei der Produktion und Bereitstellung von Geodaten – und versuchte einige Lösungsansätze aufzuzeigen.

Die Schweizer Geoinformation sei gut aufgestellt, es gebe aber auch Verbesserungspotenzial. Defizite bestünden bei ungenügenden Metadaten, der Auffindbarkeit von Geodaten, uneinheitlichen Nutzungsbedingungen und fehlenden intelligenten Suchfunktionen. Herausforderungen seien die Integration neuer Anwendungen wie BIM oder Echtzeitdaten, eine stärkere Nutzerorientierung und ein optimiertes Tooling. Lösungsansätze sind einheitliche Zugangsplattformen, die Förderung der Mehrfachnutzung (“once only”), Cloud-native Datenstrukturen und interdisziplinäre Zusammenarbeit. Die Vision ist, Geodaten leichter zugänglich und anwendungsorientierter zu machen, um sie gezielt in Wissen umzuwandeln. Die Entwicklung einer datengetriebenen Kultur und fortschrittliche Technologien wie KI sollen diesen Wandel unterstützen.

Stefan Keller schloss das Seminar mit Empfehlungen für Portalbetreiber aus Nutzersicht. Diese Empfehlungen hat er aus einem Dutzend Interviews abgeleitet. Die Interviews ergaben zentrale Defizite in fünf Bereichen: Suche, Zugang, Datenverarbeitung, Datenanalysefähigkeit und Lizenzen. Kritisiert wurden unter anderem veraltete oder unvollständige Metadaten, das Fehlen harmonisierter Standards und die mangelnde technische Reife einiger Datenformate und Schnittstellen. Empfohlen werden die Einführung semantischer Suchfunktionen, die Priorisierung nationaler Datensätze und eine bessere Integration bestehender Portale. Weitere Vorschläge der Interviewten sind einheitliche OGC-Standards für Vektordaten, harmonisierte Lizenzmodelle wie CC0 und die Bereitstellung moderner Datenformate wie GeoParquet. Ziel sei es, den Zugang zu Geodaten einfacher, effizienter und nutzerorientierter zu gestalten. Abschliessend betonte er die Wichtigkeit des Austausches in Foren wie dem GEOWebforum.

Das Webinar zeigte die Dynamik und die Herausforderungen der Schweizer Geoinformationslandschaft auf. Es gab wichtige Impulse für die Weiterentwicklung zentraler Themen wie Datenzugang, Nutzerorientierung und technische Innovation. Die vorgestellten Ideen und Visionen bilden eine solide Grundlage, um Geodaten in Zukunft noch nutzerfreundlicher und anwendungsorientierter zur Verfügung zu stellen.

October 09, 2024, by Gundula Heinatz Bürki, data innovation alliance

The Swiss Conference on Data Science (SDS) is Switzerland’s premier event for applied data science. The conference brings together leaders and science and business experts to exchange ideas and drive innovation in products and services, with a focus on the Swiss market. The SDS2024 took place in Zurich on May 30-31 at The Circle Convention Centre, Zurich Airport. If you want to get an impression how it was, have a look at the SDS2024 Flashback Video!

The 2-day conference started with an interactive workshop day to provide in-depth, practical and application-oriented insights into the latest developments in the field of data science and Artificial Intelligence. Over 450 participants took advantage of these opportunities and were able to benefit from exciting and professionally prepared and conducted workshops. Six of the workshops were supported by the Innovation Booster Databooster to identify challenges and discuss possible ideas for radical solutions.

Real World Applications of LLMs for Business and Industry

The first workshop addressed challenges and solutions in the cleantech sector and was organized and moderated by D ONE (Gabriel Levaillant, Andrei Dmitrenko and Thanos Spinoulas).

This workshop aimed to delve into the real-world applications of Large Language Models (LLMs), targeting both technical and business professionals. The agenda included a balanced mix of hands-on coding and brainstorming sessions to apply LLMs in addressing modern business challenges. 

Participants got a comprehensive introduction to LLMs, and then moved into developing a web application using LLMs. Subsequent sessions focussed on performance and cost analysis, optimizing solutions, and exploring various applications. 

The attendees gained practical skills and strategies for using LLMs efficiently in diverse scenarios.

---

Elevating Business Through Social Values – The Companies’ Perspective and Future Challenges

The 2nd workshop dealt with elevating companies through social values and related challenges. This workshop was organized by Jürg Meierhofer (ZHAW School of Engineering & data innovation alliance – Head Expert Group Smart Services) and Adrienne Schäfer (Lucerne University of Applied Sciences and Arts – School of Business).

Sustainable business practices focus on considering the impact on the environment, society, and the economy. While economic and ecological sustainability are already firmly anchored in practice, the social dimension of sustainability tends to be neglected. The participants discussed these challenges and the causal relationship between data-driven operations and social outcomes.

---

AI in Action: A Practical Guide to Using Agents for Integrating Custom Knowledge With Large Language Models

The third workshop provided a practical guide about Agents for integrating custom knowledge with LLMs, organized by D ONE (Heiko Kromer and Philipp Warmer).

This workshop explored Retrieval Augmented Generation (RAG) in Large Language Models (LLMs), focusing on the integration of custom knowledge bases and the use of agents in the generation process.

Attendees learnt about the two main components of RAG: retrieval and generation. The workshop explained the role of agents, which are managed by an orchestrator that delegates tasks and condenses results into valuable answers for the user. 

---

AI Standards: Navigating Compliance and Regulations for Responsible AI

The 4th workshop dealt with Compliance and Regulations for Responsible AI, one of the focus topics of the IB Databooster. This workshop was organized by ZHAW (Christoph Heitz and Ricardo Chavarriaga).

AI-related standards are a key element to comply with upcoming regulation of AI. This workshop provided an overview of the regulation process and important standards for AI innovation, and provided practical exercises on how to apply them in practice. More than 30 participants discussed this topics in detail.

---

Predictive Maintenance & Time Series Anomaly Detection With Darts

The fifth workshop discussed the time Series Anomaly Detection With Darts, organized by Unit8 (Dennis Bader, Antoine Madrona, Aron Horvath and Samuele Piazzetta)

The hands-on workshop on predictive maintenance and anomaly detection using Darts more than 60 participants learnt how to use time series data to predict equipment failures and detect anomalies. To understand this topic better the moderators presented two real-world use cases from the healthcare and industrial sectors. 

---

Data Science in Spatial Computing – Explore Your Data Using PlotAR

The sixth workshop addressed data science in spatial computing, also one of the focus topics in the Databooster. The workshop was organized by D ONE (Philipp Thomann, Shiva Farghar, Charlotte Cabane, Moritz Haag and Lucas Brunner)

The participants had an immersive experience: walking through the data, grasping it with their own hands. They made hands-on exercises the basics of PlotAR and explored it in more detail.

The day was concluded with a networking apero and the presentation of the Swiss Viz Awards.

By Reik Leiterer, Booster Manager

In open innovation, creating a safe space to share knowledge and ideas is vital for successful co-creation. This entails establishing a legal framework for open innovation by creating policies and guidelines that foster collaboration, protect intellectual property (IP) rights, ensure fair use, and maintain compliance with relevant laws. The following video explains how to enable a trust-building setting with rules of participation for an open innovation program and for collaborating teams.

How to set a legal framework for open innovation? (Video)

In the frame of Intellectual Property Management, create and/or follow guidelines on the ownership and sharing of IP created through open innovation, including e.g. joint ownership, licensing agreements, or IP transfer policies. Create understanding on how patents and trademarks will be handled, including the set-up of agreements on filing and maintaining IP protection. If necessary, use non-disclosure agreements (NDAs) to protect sensitive information shared during collaboration.

With regard to compliance with laws and regulations, be aware of data protection laws (e.g., GDPR, CCPA) when handling personal or sensitive data, comply with export control regulations that may affect the sharing of technology or information across borders, and avoid anti-competitive practices by ensuring that collaboration does not lead to market monopolization or unfair trade practices. May be consider using Creative Commons and open source licenses  (e.g., MIT, GPL) to facilitate and ensure legal sharing, contribution and reuse of creative works. 

We always recommend establishing ethical guidelines to ensure that innovations are developed and used responsibly. In addition, the incorporation of sustainability criteria into the innovation process could be something to think about to promote environmentally and socially responsible practices.