Understanding the many actors in the data value chain

Companies and organisations in Europe are increasingly becoming aware of the potential competitive advantages timely and accurate big data analytics has to offer. However, when considering to avail of big data analytics, or more generally to get involved in the data economy, one needs to identify the various actors implicated in the collecting, processing, managing and analysing of the data, as well as the different types of data concerned.

This article aims to provide a general overview of those various possible actors involved in big data analytics. It by no means pretends to give a full picture of the complex and evolving data ecosystem, which in general involves many (different types of) actors as well as a myriad of goods, services, technologies and business models.

The following Figure aims to depict the data value cycle.[1]


Figure 1. Data value cycle

Looking at the data value cycle, one can distinguish various actors and determine their roles in the data economy, in particular in the “datafication” process, the analysis of data and the decision making phase. It should however be kept in mind that certain organisations may play multiple roles. Also, the data value cycle does not reflect the cross-border flow of data and the legal intricacies related thereto[2].

This article will shortly discuss five key actors as well as the roles they assume in big data analytics.

The various actors and their central role

Internet service providers

Internet Service Providers (“ISP’s”) are at the heart of the data ecosystem through which data is exchanged[3]. They play an important role at the beginning of the process, as they provide the necessary technical foundations to end-users (organisations or individuals), or to other ISP’s. Certain ISP’s also provide supplementary IT services, such as cloud computing and data analytics services. Consequently, ISP’s play a fundamental part in big data analytics, including – for some of them – by offering specific data-related services and/or availing of such services for their own needs.

IT infrastructure providers

IT infrastructure providers make available to other companies the toolkit, including both software and hardware, to handle and analyse big data. They offer tools for data analytics, data management, critical computing, data storage and transport, cloud computing, software allowing database management and analytics, etc[4]. A typical example is Hadoop, which has almost become a ‘standard’ technology allowing to deal with complex unstructured large volumes of data.

Data providers

Various kinds of data (service) providers are active in the data environment.

  • Data brokers and marketplaces
    Data brokers and marketplaces compile and aggregate information (including personal data) obtained from a broad range of sources with the ultimate objective to sell, license or otherwise distribute such data to companies, consumers or other data brokers. Possible data sources include[5]:

    • Data disclosed or provided by organisations or individuals;
    • Data from sensors;
    • Data mined or crawled on the Internet;
    • Data obtained from not-for-profit organisations;
    • Open data (see below);
    • etc.
  • Individuals (such as data subjects, consumers, patients, etc.)
    Certain individuals play an active role in the data economy either by providing their data (be it personal or not) to organisations (including data brokers), or by assembling, storing and managing their own (personal) data; including in the cloud.
  • Public sector
    Public authorities have been active for several years in making certain sets of data ‘freely’ available – a concept which is also known as “open data”. In the EU, for example, the EU institutions adopted a Directive on the re-use of public sector information (government-held data), which aims at unlocking the potential of big data held and accumulated by government authorities[6] .

Data analytics service providers

The analysis of data is oftentimes performed by ISP’s, IT infrastructure providers or data providers. Nevertheless, the data ecosystem still includes specific providers of data analytics services, including for the development of dedicated software and visualisation tools based on data analytics[7]. The role of data analytics service providers tends to be assumed by start-ups or SME’s specifically active in the development of new techniques, such as predictive analytics, simulations, scenario development and advanced data visualisations.[8]

Peculiar, however, is the fact that data analytics service providers, contrary to data brokers, generally obtain their data directly from their customers, rather than from third party sources. This naturally has consequences for the identification of actors as data controllers or processors in a data protection context. Taking into account that particularity of their service, data analytics service providers usually qualify as “data processors”, rather than data controllers. Data brokers, on the contrary, are generally considered to be independent data controllers.

Data-driven entrepreneurs

The last category of actors we will discuss covers those organisations developing cutting-edge products, services and technologies based on the use of data and data analytics for different purposes; the so-called data-driven entrepreneurs. These include start-ups and incumbents, but also innovative (ICT and non-ICT) companies and governments. Not only do they use data as the core enabler for their business operations; for a majority of them it can even be said to be the fundamental economic value behind the service they provide. Against such background, data becomes a valuable asset due to the transformation of data into know-how and intelligence, and thus it can be used for decision-making purposes.

A layered approach of the key roles of actors

The actors as well as their roles briefly explained above can be depicted in layers, where the underlying layers supply the upper layers with goods and services[9]:


There is a multitude of actors on the market actively reaping the benefits of the data economy. The relationships between such actors are an essential element of the data value cycle. One should therefore carefully assess the multiplicity and multi-layer agreements governing the access and the exchange of data between those various actors, taking into consideration the type of data involved in the analytic processing.

The legal framework is unfortunately not satisfactory at this stage. In fact, it is clear that one of the factors limiting the availability, use and exchange of data in commercial settings is the legal regime (or the lack thereof). At the current time, the various commercial entities exchanging data in the context of the data value cycle do so mainly on the basis of contractual agreements. It is unclear, however, whether such practice allows encompassing all possible situations with the necessary and satisfactory legal certainty surrounding such contractual agreements. Indeed, in the absence of a comprehensive legal framework regulating numerous rights (e.g., ownership, access or exploitation rights), the way in which such rights can be exercised and by whom, there is an abundance of potential limitations attached to data.

As a matter of urgency, emerging issues of ownership, interoperability, usability and access to data in situations such as business-to-business, business-to-consumer, machine generated and machine-to-machine data will need to be analysed. The EU Commission already emphasised this in its Communication on “A Digital Single Market Strategy for Europe”[10]. In particular, it will be necessary to identify the current EU legal regime determining what rights linked to data exist, how these can be exercised and by whom, notably in a commercial context. Similarly, it will be necessary to determine what rights are legally established for third parties wanting to access data held by a commercial entity. Furthermore, questions have arisen as to whether contractual arrangements provide an efficient legal framework for managing rights attached to data (including on exclusivity, exchange, exploitation or access to data), and which elements – if any – may be missing in legislation for contracts to perform this function.

These questions and many more will be dealt with by Bird & Bird in the framework of the EU-funded TOREADOR project. For more information, see the Bird & Bird press release and the TOREADOR website.

This article was written within the European Union TOREADOR project (“TrustwOrthy model-awaRE Analytics Data platfORm”). Granting authority: European Union. Call: H2020-ICT-2015. Topic: ICT-16-2015 (Big data – research). Type of action: RIA. Grant agreement no.: 688797, Starting date: 1st January 2016, Ending date: 31st December 2018.

By Jasmien César, Julien Debussche, Benoit Van Asbroeck

  1. OECD, Data-driven Innovation: big data for Growth and Well-being [2015] OECD Publishing, Paris, p. 33.
  2. See in this respect the recent Free Flow of Data Initiative of the EU Commission as part of the Digital Single Market.
  3. OECD, Data-driven Innovation: big data for Growth and Well-being [2015] OECD Publishing, Paris, p. 72.
  4. Idem.
  5. Idem, p. 82.
  6. Directive 2003/98/EC of the European Parliament and of the Council of 17 November 2003 on the re-use of public sector information, OJ L 345, 31.12.2003, p. 90–96.
  7. OECD, Data-driven Innovation: big data for Growth and Well-being [2015] OECD Publishing, Paris, p. 86.
  8. Idem.
  9. OECD, Data-driven Innovation: big data for Growth and Well-being [2015] OECD Publishing, Paris, p. 72.
  10. Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions, A Digital Single Market Strategy for Europe, COM(2015) 192 final, 6 May 2016.