Innovation potential trapped in data silos
Billions of data units are generated every day: Every click, every step, and every heartbeat is documented and collected by a wide variety of organizations. Data has become the central resource of our time and is therefore particularly important for economic connectivity. This is especially true when it is used to control and optimize machines, processes, products, energy, or traffic flows. The problem: Data collection is usually carried out in isolated data silos within an organization, which is protected as best as possible from external access. While the value of data as an economic asset is often recognized, most people are still skeptical about exchanging, sharing, or even trading data. In addition, technical and legal challenges prevent shared use. Therefore, data exchange often does not go beyond a bilateral exchange regulated by complex contracts. This hinders the development of successful sustainability policies, innovative service offerings, and automated organizational processes.
Data is part of the solutions we need for a sustainable future
Due to the increasing threat of environmental disasters and the consequences of climate change, the urgent need to transition to more sustainable concepts in all areas of life and work is growing. The European Green Deal and the United Nations Sustainable Development Goals (SDGs) define ambitious targets and demand rapid action. This is precisely where the Green Data Hub By sharing and securely using data in a sustainable European data service ecosystem, practical solutions can be developed to address current climate and environmental challenges.
Sovereign sharing in Data Spaces for Sustainability
Data sharing as a solution: A data space is a simple and strictly controlled alternative for sharing data according to international standards. In a decentralized infrastructure, data is made available for sharing between trusted partners using the same standards and rules. Data is not stored centrally but remains at the source and is only made available when needed and under certain rules, for example, for a specific use case.
In a data service ecosystem, business models and services are developed and optimized through the collaboration of data-producing, data-processing, and data-using organizations. The Green Data Hub of the Data Intelligence Offensive (DIO), a powerful networking platform with over 180 stakeholders, invites all organizations along the data value chain to jointly advance the energy and mobility transition, the circular economy, and digital climate twins. Together with business, research, and business development partners, cooperative sustainable use cases are developed in Data Spaces that simultaneously contribute to environmental protection and create business value. The following two use cases, which were created in part by the Green Data Hub, offer insight into the functioning of a data service ecosystem.
Use Case “Efficiency Optimization in the District Heating Network”
An Alpine community covers up to 90 percent of its heat needs with district heating. Consumption is heavily dependent on tourist frequency and capacity utilization. The problem for this use case was the lack of information on the most efficient use of biomass to meet the region's needs. Several data sources are seamlessly linked in the data service ecosystem: mobile frequency data from a mobile provider, energy consumption data from the energy operator, calendar data from open source sources, weather data from a weather service, and overnight stay data from the tourism organization. This creates a forecast model as an information basis that enables intelligent and optimized decisions. On the one hand, this generates business value through more efficient operation of the power plant and the management of demand fluctuations. On the other hand, the savings from using biomass as an energy source contribute to environmental protection and create a scalable solution for a more sustainable energy industry.
Use Case “Thermal Earth Observation for Heat Management”
The heating and cooling of residential buildings and industrial processes causes significant greenhouse gas emissions. The challenge for this use case was a lack of information to detect unused temperature differences. To this end, various Earth observation data are seamlessly linked within the data service ecosystem and used for thermal monitoring and exploration. This enables the monitoring and (predictive) maintenance of inefficient heat transfers, the planning of investments for system stability, the mapping of areas with available waste heat for increased cooling and heating demand, and the planning of countermeasures against urban heat islands for municipal policymakers.
Best Practice: Data Science Challenge
The development of data-driven, innovative solutions to problems was also the focus of the Sustainability Data Science Challenge initiated by ÖBAG. The competition, which was implemented jointly with Capgemini and Microsoft and in which four ÖBAG portfolio companies participated (A1 Telekom, BIG, Austrian Post, and VERBUND), aimed, among other things, to reduce the carbon footprint of properties and analyze the level of biodiversity using advanced analytics.
Of course, technologies and data alone will not be enough to solve the climate crisis or energy supply issues. However, cross-sector and collaborative initiatives, such as those being driven by ÖBAG and the Green Data Hub, offer the opportunity to develop solution models that can subsequently benefit many other companies.
A data service ecosystem thrives on the greatest possible diversity of different actors and data sets. Only through cross-organizational and cross-border collaboration can a multi-value benefit be created for the general public. Cooperation is the guiding principle for breaking down data silos.
Tobias Hofer is at the Data Intelligence Offensive as Green Data Hub Community & Communications Manager and is also responsible for the use case management of the Green Data Hub.
