In a time of climatic change and shifting tourist expectations, the winter tourism sector must reinvent itself. The EU-funded project "E-DNS – Empowering Nordic Ski in the Dolomites" (2024-2027) aims to redefine the future of Nordic skiing through digital innovation, data-driven solutions and cross-border cooperation.
Led by the cross-country regional network Dolomiti NordicSki and the region of Osttirol, E-DNS involves 8 tourism areas in South Tyrol, Osttirol, and the Province of Belluno. The project focuses on improving the quality and sustainability of nordic ski infrastructure while enhancing real-time communication with guests.
A core element is the integration of open data from Open Data Hub into Contwise Map, a digital platform developed in partnership with the company General Solutions. Through real-time visualization of trail conditions, mobility data, and POIs, Contwise Map empowers both guests and local operators. This allows for the creation of smart slopes: dynamically managed trails offering the best possible experience based on current snow, weather, and infrastructure conditions.
The use of Contwise Infra also enables regions to better manage resources, optimize trail maintenance, and respond more efficiently to environmental changes. Data becomes a strategic asset—supporting planning, sustainability, and transparency.
This talk presents the real use case of how open data—especially in the tourism and mobility sector—can trigger systemic transformation in destination management, improve guest experience, and promote a more sustainable, connected winter tourism model.
The project demonstrates the potential of collaborative innovation between tourism actors, tech providers, and open data ecosystems such as NOI Techpark and Open Data Hub.

Two cases that show how we from IDM Südtirol are using the Open Data Hub to gather tourism data from different sources and how we display it.

In an era of climate change, cities are increasingly tasked with managing green spaces in ways that maximize their environmental, social, and economic benefits. Efficient, data-driven green management is key to building more resilient urban landscapes. At R3GIS, we offer a range of advanced software and hardware solutions designed to help cities optimize the care and maintenance of urban greenery while adapting to climate change.

Open data are defined as " open type data " in Article 68 of the CAD and are considered fundamental elements in the implementation of the European Directive on public sector information. Their publication is a legal obligation.

The Public Administration’s Open Data Portal is the catalog of open government data for the South Tyrolean territory. As a catalog, it contains information (metadata) about the open data (freely downloadable) of the territory, the organizations which produce and manage them, as well as references (links) to the data themselves.

Open data are typically made available as an archive and/or as a web service. In the case of public administration, open data also have great value as trust enablers: making production data available means generating transparency, which allows citizens to monitor the work, product, choices, and measure the performance of the public administration.

As of 24/03/2025, the Open Data Portal of the Autonomous Province of Bolzano has 621 datasets in its catalog, totaling 3326 resources. The Open Data Portal (https://data.civis.bz.it/) is implemented with CKAN (https://ckan.org/), the market-leading open-source product in this specific sector.

The portal mentioned comprehends also a variety of geographic data (geodata), organized in the GeoCatalogue, which has become an integral part of the MapView GeoBrowser since October 2024. This is a great advantage for users, as they will find all the data in one place. Users can search and view themes and their metadata and download them. This integration allows to combine GeoBrowser data with GeoCatalogue data and export it, for example, as custom maps. The MapView online portal thus becomes the most important platform for accessing and downloading governmental geodata, sector plans and other geographic information. This system is the result of the collaboration between the Autonomous Province of Bolzano, the Consortium of Municipalities, the Civil Protection Agency and, in the role of technological partner, Informatica Alto Adige Spa.

The South Tyrolean public administrations offer Open Government Geodata through the integrated MapView system, aiming to its wide use. The license for most datasets, as published in their metadata, is the Creative Commons Zero 1.0 (CC0) license. Before downloading the data or using the webservices, users are invited to take note of the license.

Recent and new projects, especially in the mobility sector, are leading towards the shared use of existing open data resources in South Tyrol.

For example, the Euregio project DIGIWAY brings the shared use of hiking routes and road networks.
Looking ahead to the planned MMCS (Mobility Management Center Südtirol), one of the aims is to share official traffic events such as closures or detours in addition to the official road network of the administration.

In this way public administration, research and development are growing ever closer together through the shared use of open data.

Open Data is revolutionizing research by providing access to real, interconnected datasets that enhance the accuracy and reliability of analyses. Whether in business, academia, or policymaking, integrating Open Data—such as electoral records, geographical data, and economic statistics—can improve traditional research methods like survey analysis and data modeling. This talk will explore how Open Data complements and strengthens research by enabling cross-validation, reducing biases, and enriching findings with real-world correlations. From market studies to social science research, we will discuss practical applications and best practices for leveraging Open Data to enhance decision-making and drive more precise, evidence-based insights.

Energy Management and Information Systems (EMIS) in buildings often face significant challenges related to scalability and interoperability. These limitations stem primarily from the absence of standardized metadata models, which creates barriers when implementing solutions across multiple buildings with different naming conventions and system configurations.

The Brick ontology offers a promising solution as an open-source framework designed to standardize the description of physical and logical building entities. However, creating ontology-based metadata models requires specialized knowledge in both building systems and semantic modeling—a rare combination of expertise that limits widespread adoption.

This talk introduces BrickLLM, an innovative Python library (EURAC, Politecnico di Torino) that leverages Large Language Models (LLMs) to automatically generate Resource Description Framework (RDF) graphs using the Brick ontology. BrickLLM transforms natural language descriptions of buildings and their energy systems into machine-readable, standardized metadata models, dramatically reducing the time, cost, and expertise required for this critical task.

Key features of BrickLLM include:
1. Support for both cloud-based LLM APIs (OpenAI, Anthropic, Fireworks AI) and local open-source models (LLaMA 2, LLaMA 3)
2. Two workflow options: a streamlined "instruct" workflow for fine-tuned models and a more structured workflow for general-purpose LLMs
3. Built-in validation against Brick's SHACL shapes to ensure semantic correctness
4. Modular architecture based on LangChain and LangGraph for extensibility

The presentation will demonstrate how BrickLLM enables users without specialized knowledge to generate comprehensive, standards-compliant RDF representations of buildings and their systems through simple natural language descriptions. We'll explore the practical applications of this technology, including:

• Facilitating portable EMIS applications across different buildings
• Enabling more efficient energy optimization strategies
• Supporting fault detection and diagnosis systems
• Enhancing interoperability between different building management platforms

By democratizing access to ontology-based metadata modeling, BrickLLM addresses core challenges in the open data ecosystem for smart buildings and energy management. The library's open-source nature encourages collaboration and further research, potentially leading to optimized workflows for semantic metadata model generation.

We'll also discuss how this approach aligns with broader initiatives to standardize and democratize data across different domains, making it particularly relevant to the Open Data Hub Day's mission of promoting best practices in data management and utilization.

The Open Data Hub is part of the Regional Access Point (RAP) implementation for the Province of Bolzano – South Tyrol within the MaaS4Italy project.
We will go through the API we've implemented (https://transmodel.api.opendatahub.com), the technologies involved, which type of data is available, and how users can access it.
We will also highlight our NeTEx binding library for golang (https://github.com/noi-techpark/go-netex) for which we are looking for contributors

The European Union has established NeTEx and SIRI as de jure standards for mobility data exchange, requiring Member States to adopt them in their National Access Points (NAPs) to ensure interoperability and accessibility of transport data. However, GTFS (General Transit Feed Specification) and its extension GTFS-RT (General Transit Feed Specification - Real Time) remain the most widely used de facto standards for multimodal trip planning, creating a “barrier” to the adoption of EU standards and the intended usage of NAPs.

To address this challenge, in the context of the OTP-Italy project, OpenMove and Cefriel are developing an innovative solution to enable the transition from GTFS and GTFS-RT to NeTEx and SIRI (Italian profiles) in the open-source journey planning software OpenTripPlanner (OTP).

The solution includes two converters supporting the conversion from GTFS to the Italian NeTEx profile and from GTFS-RT to the Italian SIRI profile, leveraging a reference conceptual model and semantic web techniques to ensure optimal conversion and data enrichment. Moreover, the solution includes the development of an OTP fork to improve integration with the NeTEx and SIRI italian profiles, optimizing interoperability among transport companies' data and enhancing the accuracy of transport information.

This initiative goes beyond mere data conversion, aiming to improve the quality of information provided to end users by enriching it with new sources and expanding its informational coverage. The result contributes to a more integrated, interoperable, and accessible mobility ecosystem that facilitates stakeholder collaboration and makes public transport an increasingly competitive alternative to private car use.

Through this presentation, we aim to share the challenges faced and the solutions adopted so far, providing a concrete implementation case to support the transition to European mobility standards. We will offer insights into the technical aspects of data conversion, the advantages of integrating open standards in trip planning, and the broader impact on mobility data interoperability and accessibility across Europe.

This talk presents some patterns that can be used in the design of service APIs to help avoid the waste of resources in the exchange of information between two systems. It will go through different practices, discussing their impact on sustainability, as well as the trade-offs related to other quality attributes. The following are some practices that will be presented and discussed: (a) divide data retrieval into more granular services to allow clients to retrieve just what is needed; (b) provide parameters to customize the content that should be returned; (c) provide an endpoint that allows the verification of the last data update; and (d) adopt as default the option that consumes the lowest amount of resources.

Open Quiz Hub is a quiz application developed by two students from TFO Bozen, David Spitaler and Elias Klotz, as part of a school project. Inspired by Kahoot, our app leverages open data from the Open Data Hub to create dynamic, interactive quizzes on various topics. In this session, we will share our journey from concept to implementation, highlighting how we integrated multiple data sources, tackled technical challenges, and refined the user experience.

From proprietary data/formats to Open Source/Open Data: from IVU/Hacon to OTP/Digitransit

A bit of history and the reasons of choice

Open Source: using OTP and Digitransit-UI; architecture of LiguriaGO (regional travel planner) and MOBIMART (cross-regions travel planner)

Open Data: GTFS, quality issues, common problems and how we cope with them

RAP (Regional Access Point) Liguria

GTFS2NeTEx-converter and RAP Liguria

Using NeTEx Italian Profile with OTP: the results achieved and those to be achieved

The new Regione Liguria Open Data Portal

Roadmap 2025 and beyond

An OTP versions journey: from 1.5 to 2.1 to the latest versions

Travel planning evolution towards MaaS: flexible/demand-responsive, vehicle sharing, parking

Travel planning and e-ticketing: a happy marriage

The front-end dilemma: Digitransit-UI or otp-react-redux, a comparison

The Meridian Project, started in 2022 and still ongoing, aims to bridge the gap between physical infrastructure and digital ecosystems by creating a seamless Digital Layer alongside the A22 highway (also known as Autostrada del Brennero/Brennerautobahn), integrating real-time and historical mobility data. By using open data provided by third parties, among which and in particular OpenDataHub, this project fosters the development of innovative mobility services beyond traditional traffic management.

Aligned with the European vision of horizontal data layers, the project prioritizes API-driven integration with existing platforms instead of standalone applications, maximizing user reach and impact. Strategically, it anticipates the future of mobility, where digital tools mediate transportation decisions, from real-time traffic updates to intermodal journey planning.

The A22 Digital Layer transforms mobility data into a valuable asset, supporting future services like autonomous shuttles and dynamic route optimization. At its core, the project develops a multimodal digital infrastructure that aggregates and standardizes data from multiple sources while ensuring compliance with EU standards (TRANSMODEL, NeTEx and SIRI) and providing advanced validation, security, and management tools. It also includes a multimodal trip planner, capable of processing diverse datasets such as DATEX II, GTFS/NeTEx, GTFS-RT/SIRI and private mobility services. In the near future, the journey planner will also optimize routes based on factors like traffic conditions, emissions, cost, weather and intermodality. Moreover, to ensure controlled access and usability, the project also includes the development of a web dashboard allowing real-time monitoring, third-party integration, and potential monetization models for premium services.

By empowering external digital players and leveraging its mobility data assets, this project not only enhances traffic management but also positions itself as a key enabler of smart mobility, shaping the future of connected transportation.

Dynamic Destination Insights: Data, Scenarios and Sustainability for the Future of Destination Management

The Open Data Hub provides many web components that users can integrate on their websites to visualize data from the Open Data Hub.
In this talk we will present our web component store, and show developers how they can use, customize, or even create and contribute their own web components to the Store / Open Data Hub

The Open Data Hub project is using Golang for many of it's recent implementations.
We will go through:
- an overview of the Go language
- why we've made this choice
- our experiences in using it so far

The INSTINCT project, funded by ERDF programme aims to develop and validate sustainable management practices for key insect pests in South Tyrolean agriculture through intelligent sensor systems and low-impact intervention techniques. To facilitate data sharing and collaboration among project partners, a Minimum Viable Dataspace (MVD) has been implemented. This dataspace leverages the European data space framework to enable secure and interoperable data exchange ensuring data sovereignty.

The MVD architecture integrates the minimum set of technical and organizational components, including two distinct connectors, namely the International Data Spaces Association (IDSA) connector and the Eclipse Data Space Connector (EDSC), which are linked with Identity and Access Management (IAM) and the Dynamic Attribute Provisioning Service (DAPS). The connectors ensure secure and standardized data access and exchange. IAM manages user identities and access permissions, ensuring that only authorized users can access the data. DAPS provides dynamic attribute provisioning, enabling real-time updates to access policies based on changing conditions. The Data Space Authority oversees the governance and management of the dataspace, ensuring compliance with legal and ethical standards. It establishes data sharing agreements, can monitor data usage, and enforces data privacy and security policies. This setup allows seamless data sharing between project partners Laimburg Research Center, University of Bolzano, EURAC Research, and Gruppo FOS.

The dataspace supports the exchange of agricultural-related data, including sensor data for automated recognition of insect stages and environmental data for climatic and phenological analysis. The INSTINCT App will be developed in a second stage and possibly will serve as the user interface, allowing partners to access data seamlessly. The web app provides a user-friendly platform for visualizing data, generating insights, and making informed decisions.

The MVD aims to be further developed into the INSTINCT Dataspace along the project implementation and will enhance the project's impact on sustainable agriculture, by fostering collaboration and innovation, and aims to contribute to the broader European data space for agriculture.

Existing Data Spaces have focused primarily on secure and policy-compliant data sharing, our work takes the next leap, enabling the sharing of services, specifically Federated Learning (FL) services, as part of a data ecosystem.

FL is a privacy-preserving machine learning approach where multiple participants collaboratively train a model without sharing raw data. Each party trains the model locally, and only model updates (not the data itself) are exchanged and aggregated. This makes FL particularly suited for sectors where data sensitivity, sovereignty, or compliance are critical such as healthcare, energy, mobility, or finance.

In this talk, we present a novel framework that integrates FL into the International Data Spaces Association (IDSA)’s Data Space Protocol. Our framework allows organizations to advertise their FL capabilities via IDSA’s Protocol and enables interested parties to dynamically join collaborative training rounds. This evolution from data sharing to policy compliant collaborative model training represents a significant extension of today’s Data Space paradigms.

One of the key challenges we address is automated usage policy enforcement across distributed, multi-party FL pipelines. Unlike traditional data exchanges, FL introduces complex service-level interactions that occur outside the strict boundaries of a data space connector. We identify and design policy enforcement points (PEPs) tailored to federated workflows and embed them into the FL framework architecture. This is achieved through a policy injection at orchestration level and runtime monitoring hooks that triggers the enforcements.

To ensure interoperability, we’ve also developed an ontology for FL, which defines core concepts and relationships critical for FL-aware data ecosystems. The ontology captures key concepts such as Federated Aggregation, Training Rounds, Model Artifacts, Policy Definitions, and Incentives, ensuring semantic alignment between participants and their connectors. Beyond providing a common vocabulary, the ontology is now being adopted as a foundation for defining machine-readable usage policies, allowing constraints and governance rules to be explicitly tied to these concepts. For example, restricting how model artifacts can be reused, setting participation limits per training round, or expressing incentive conditions for contributors. Moreover, the ontology is then integrated into the IDSA information model for to facilitate FL Service advertisement and discovery.

We have implemented a proof-of-concept using the Flower Federated Learning framework, demonstrating real-world feasibility. Our prototype showcases FL server discovery, policy negotiation, server orchestration, and enforcement in a multi-organizational setup, providing insights for future adoption within data space ecosystems.

Scaling a distributed system posses many challenges. One of them is how to observe a system where many small components interoperate with each other.
In this talk we will explore the software telemetry world focusing on metrics, metrics and correlation.

We will see how the Open Data Hub approached the challenges, our choices and the tech-stack.

As Europe moves towards more interoperable and connected data ecosystems, trust and governance play a crucial role in enabling secure, transparent, and scalable data sharing across sectors. This session will explore how the iSHARE Trust Framework provides a neutral, trust-based foundation for Open Data ecosystems, helping organisations collaborate with confidence while ensuring compliance, data sovereignty, and security.
Through real-world examples, we will demonstrate how iSHARE fosters interoperability and governance, supporting businesses, policymakers, and researchers in maximising the value of Open Data while respecting data rights and regulations such as the Data Governance Act and Data Act.

The Open Data Hub now has reusable generic data collectors.
This allows new data providers to get connected much quicker, and start data collection even before the full integration is complete.

We will give an overview of this new architecture, and present some options that data providers can use today:

• REST polling
• REST push
• MQTT client
• OCPI
• NOI Lorawan
• AWS S3
• Google Spreadsheet

Presentation of the newly developed Open Data Hub Analytics Tool, showing also the maps capabilities shared with the Data Browser.

In this session, we’ll explore how to unlock valuable insights from the Open Data Hub using the Data Browser. Learn how to visualize open-source data effectively, leveraging the power of the Data Browser to analyze and display diverse datasets.

This talk introduces a novel tool that tests the data quality of a given dataset from the Open Data Hub. Besides formal tests of the data fields, the tool uses a machine learning approach to test the quality of images and whether the content of an image agrees with its description. Hence the tool can provide valuable insights into potential errors or issues with the data and images.

As organizations and governments increasingly depend on data-driven decision-making, standardized data management practices become critical. DCAT and ODPS are essential frameworks enabling efficient data sharing, interoperability, and utilization. Their roles become particularly prominent in the context of data spaces and AI.

People use natural language for most of their communication needs.
What if people could consult the data in the Open Data Hub using regular natural language.

We will share the experience we gained in the last months, using so-called text2query techniques. We will compare different approaches and benchmark their accuracy in generating a query that matches as well as possible the intent of the user.

More specifically, we will compare the following approaches:

1) directly the underlying data source in SQL
2) the virtual knowledge graph in SPARQL
3) the virtual knowledge graph in SQL.

Our research in this area is an ongoing effort for the ERDF project "CRIMA", a joint project of Ontopic, unibz and Eurac.

An open environment of collaborating parts is beneficial to mutually support growth. Whether they're internal or third-party, having collaborators offloads our concerns and multiplies our possibilities. Yet, we still face challenges when handling data that can be spread across this ecosystem. Specific protocols, different data structures and naming conventions, lifecycles… Most of the time, all we wanted is to grab a piece of data from a provider, cross it with an internal resource, and serve the result to our clients and partners. But those challenges slow down the development of the flow. Not only that, as time goes by, the flow simply breaks, and again we face again the same challenges to maintain the code. What a mess!
In this talk, I want to share some strategies to stand up to the mess created by combining data from multiple places, that hopefully bring us closer to our values and goals.

AlpineBits HotelData has been a free and open standard for over a decade. However, each implementation contains different rules for sending and receiving correct OTA XML messages. All of them need to be validated and well tested before going into production and displaying hotel rate information or even sending bookings. That's where AlpineBits certification comes in. In this talk we will see how a rule-based certification of an API can be automated by a (pre-)certification tool.