Role of an i-Space and its Alignment with Other Initiatives

The concept of Data Innovation Space was initially coined in 2014 by the BDVA and identified as a key instrument to foster data-driven innovation based on experimentation, testing and benchmarking. Since then, many other instruments have appeared in Europe, aimed at bringing innovation closer to industry and society, and more specifically to those actors with no capacity to benefit from the latest European digital innovations.

In this way, and considering that only about 1 out of 5 companies across the EU is highly digitalised, and around 60% of large industries and more than 90% of SMEs lag in digital innovation, the European Commission introduced in 2017 the concept of the Digital Innovation Hub (DIH), to ensure that every company, small or large, high-tech or not, can take advantage of digital opportunities. DIHs are one-stop shops that help companies become more competitive with regard to their business/production processes, products or services using digital technologies. DIHs provide access to technical expertise and experimentation so that companies can “test before invest”. They also provide innovation services, such as financing advice, training and skills development, that are needed for a successful digital transformation.A Digital Innovation Hub brings many actors together, to develop a coherent and coordinated set of services that are needed to help companies (especially SMEs or enterprises from low-tech sectors) that have difficulties with their digitisation through a one-stop shop. However, the core of a DIH is the Competence Centre, which provides technical expertise and access to advanced facilities (see Fig. 1).

Figure 1: Competence Centres and Digital Innovation Hubs (Source: European Commission) (by European Commission licensed under CC BY 4.0)

The European Commission has developed an online catalogue to provide a comprehensive picture of DIHs in the EU across varying competences structures and service offerings. It is a repository with more than 400 DIHs, over 200 of which are fully operational, including information on the technology and application specialisation, geographical coverage, markets addressed and general digitisation support available. According to this catalogue, there are around 190 DIHs in Europe specialised in data mining, big data and database management, meaning that these data-driven DIHs are ready, based on the expertise provided by their Competence Centres, to support companies in their respective ecosystems in the development, adoption and testing of data-driven solutions.

In this way, the concept of Data Innovation Space is aligned with that of a Competence Centre on Big Data, in the sense that it provides access to infrastructure, expertise, support to experimentation and production of new services, and best practices regarding data-driven solutions and products. On the other hand, it can also offer advanced services such as brokerage, access to finance, training, and incubation and acceleration. In this case, it would act as a Data-Driven Innovation Hub (actually, all BDVA i-Spaces are recognised DIHs on big data), bringing together not only technical competencies but all tools and aspects needed to allow SMEs to put their data-driven services and products into the market. Taking all of the above into consideration, and depending on the offered services, a Data Innovation Space would range between a Competence Centre on Big Data and a Data-Driven Innovation Hub (see Fig. 2).

Figure 2: Data Innovation Space vs. DIH and Competence Centre

Other important instruments developed to mobilise data and foster data sharing and reuse are data platforms and data spaces. According to a BDVA position paper on data sharing and data spaces, a data space is an ecosystem of data models, datasets, ontologies, data sharing contracts and specialised management services (e.g. as often provided by data centres, stores and repositories, individually or within “data lakes”), together with soft competencies around it (i.e. governance, social interactions, business processes). These competencies follow a data engineering approach to optimise data storage and exchange mechanisms, in this way preserving, generating and sharing new knowledge. On the other hand, data platforms refer to architectures and repositories of interoperable hardware/software components, which follow a software engineering approach to enable the creation, transformation, evolution, curation and exploitation of both static and dynamic data in data spaces. Specific examples of data space and data platforms are mentioned in this BDVA paper, and it is also worth mentioning the nine innovation actions funded by the European Commission under the topic “Supporting the emergence of data markets and the data economy”, especially aimed to address the necessary technical, organisational, legal and commercial aspects of data sharing/brokerage/trading, both for personal and industrial data.

These instruments incorporate in Data Innovation Spaces (and Data-Driven Innovation Hubs) the dimension of data sharing, data trading and data reuse, allowing Data Innovation Spaces to share datasets and data sources with other Data Innovation Spaces, and providing interoperability and scalability in terms of data.

The new Digital Europe Programme will reinforce the role of Digital Innovation Hubs and European Data Spaces as the main instruments to increase the competencies and bring innovation to the European industry and society in terms of data. This programme also includes technology infrastructures with specific expertise and experience of testing mature technology in a given sector, under real or close to real conditions (e.g. smart hospital, smart city, experimental farm, corridor for connected and automated driving), which are the Testing and Experimentation Facilities (TEFs) on AI.

These TEFs will exploit, test and validate data spaces to test AI-powered solutions, also enriching them by providing user feedback. TEFs will contribute to data spaces by collecting and providing data from experimentation. On the other hand, the Digital Innovation Hubs will act as a distribution channel for AI to empower all local companies and users.Figure 3 shows the different dimensions provided by different European instruments.

Figure 3: European instruments to foster data-driven innovation and experimentation

According to the European Commission, a Digital Innovation Hub relies on four pillars to increase the competitiveness of companies with regard to their business/production processes, products or services using digital technologies. These pillars are: (i) access to an innovation ecosystem with connection and networking with multiple stakeholders, (ii) test before invest, with access to technical expertise and experimentation, (iii) support to find investments and (iv) skills and trainings. With respect to this last aspect, to find alignments and synergies with the so-called centres of excellence, organisational units within a national system of research and education that provides leadership in research, innovation and training in digital technologies are of utmost importance, given the regional/national scope of both types of initiatives and their complementarities. In the case of big data, the connection between Data-Driven Innovation Hubs and the network of Big Data Centres of Excellence is valuable in identifying gaps in the industry demand side (workforce) at regional level and jointly planning a training programme to fill those gaps. Further details on big data and AI Centres of Excellence are available in Chap. “A Best Practice Framework for Centres of Excellence in Big Data and Artificial Intelligence”.

Excerpt from: Alonso D. (2021) Data Innovation Spaces. In: Curry E., Metzger A., Zillner S., Pazzaglia JC., García Robles A. (eds) The Elements of Big Data Value. Springer, Cham.