By now, it is clear that without data there can be no social progress. The EU is very clear about this, and for this reason it is constantly carrying out initiatives to find new ways of progressing as a society with data as the basis for everything. One of them is the carrying out of some experiments, the purposes and results of which we will now comment on.
Within the ongoing process of social and economic digitisation in which the European Union finds itself, data play an indispensable role, together with innovative technologies and approaches for their capture, processing, sharing and use.
Therefore, many efforts are being focused on the creation of a common European data space covering information specific to strategic sectors such as environment, agriculture, industry, health or transport.
In this article we will draw the main conclusions from a set of experiments that sought to explore and improve the understanding of new approaches and technologies for data-driven innovation in order to establish this European data space through the European Data Strategy.
The European Data Strategy as a basis
The main objective of the European Data Strategy is to make data the real fuel for social progress. Through a single data space, data will be able to circulate without any kind of obstacle between the member countries of the European Union and between all the agents involved, such as companies, governments, researchers, etc.
Data that will be available to everyone and that will be used to make documented decisions based on their processing and the knowledge generated. Of course, always respecting the regulations concerning privacy and data protection.
This will lead to greater productivity and competitiveness, as well as advances in health and well-being, better care for the natural environment, greater transparency and better managed public services.
To achieve all this, the European Union will need to take the following steps:
- Set clear and fair rules on access to and re-use of data.
- Invest in technological tools and infrastructure to store and process data.
- Join forces to increase their cloud computing capacity.
- Pool data in key sectors, creating common and interoperable data spaces.
- Empower users with rights, tools and capabilities to maintain full control over their data.
What experiments were carried out to achieve greater data-driven innovation?
These aforementioned experiments deal with the following topics:
- Storing and sharing large amounts of data: binary serialisation for static and dynamic data.
- Getting data to its destination: event-driven architectures for data exchange.
- Data processing close to the source: perimeter computing in IoT devices to detect noise pollution.
- Applying automation to the creation, testing and deployment of software applications: the case of web-based data services.
- cloud.
- Combining public sector and citizen-generated data: the case of addresses.
- Addressing public-private partnerships for data provision: data collaborations for air quality in cities.
- Understanding the demand for data-driven innovation in the public sector: the case of algorithmic processes.
- Align EU-level policies and local practices in the context of European data spaces.
Following the analysis of the studies contained in this Community document, the authors draw a set of conclusions from their work. We will highlight the most important aspects of these conclusions.
Firstly, it is specified that the generation of data spaces will depend to a large extent on the constant and conscious effort and active participation of countries, regions and municipalities.
The document makes it clear that a better description of the territory with the right data helps to understand the challenges faced by authorities, businesses and citizens and to find the best solutions for them.
To this end, we face a set of barriers that need to be broken down as soon as possible. These include the excessive overall length and uncertainty of European regulatory processes, the lack of local capacity, technological uncertainty and the significant costs of generating data spaces.
It also discusses the identification of several strategic angles that can act as key enablers for the active participation of cities, regions and municipalities in the establishment of data spaces.
These enablers include technologies and methodologies that improve overall infrastructure agility, digital sovereignty and effective data management. For example, access optimisation and cloud infrastructure management.
In summary, we can say that working towards well-structured and maintained data spaces that are responsive to society’s demands is the basis for successful participation in data collaborations. With it, society will be able to benefit from knowledge creation and transfer, improve decision making and related policy monitoring and evaluation.
This requires continuous exploration of emerging technologies and changing demands. An innovative character that is part of Geograma‘s DNA. If you are interested in learning more about it, we encourage you to take a look at our success stories and to contact us to find out about the opportunities that open up by applying them to your project.
