[1]<\/a><\/p>\n<\/blockquote>\n\nTo achieve this objective, the creation of innovative \u2018data intermediation services\u2019 (data intermediaries) is proposed. An intermediary is a neutral body which acts as a mediator between at least two parties in the interests of those parties (or partners), not least because the parties trust the intermediary. The intermediary may be trustworthy as an organisation acting in the public interest, but also because it has no intention whatsoever of being a market competitor; rather, its focus is solely on the quality of the intermediation service it provides. If data trustees are understood as intermediaries of this kind, it is possible to identify their key characteristics and distinguish them from other data services. A data trustee acts as a third party between data providers and data recipients and endeavours to organise the exchange of data in such a way that best serves the interests of both parties. The role of the data trustee consists solely, for example, of data transfer, making data usable or a service package that includes, for instance, anonymisation\/pseudonymisation of the data. <\/p>\n\n
2.2 Distinction from other data services<\/h4>\n\n
Given their lack of self-interest in exploiting (or even simply being aware of) the content of the datasets they manage, data trustees must be differentiated from platforms. Platform models (e.g. marketplaces) are based on control of all processes \u2018on\u2019 the platform; they analyse the resulting data trails and aim both to monetise them and to make commercial use of the shared data itself. However, data rooms must also be distinguished from trust models; this stems from the capacity of the data trustee as an actor. Whilst a data room functions as a general enabler, a set of rules and standards (e.g. with regard to a specific data domain), combined with a corresponding technical infrastructure, a data trustee is a purpose-built organisation, usually a company. In data rooms, data trustees can act as a kind of honest and neutral intermediary which facilitates or guarantees the transfer of data to ensure it is shared in a spirit of trust. After all, data trustees are not the same as research data centres either. Whilst the latter review, archive and make data available for scientific purposes, the actual function of the data trustee does not lie in the long-term storage or archiving of data. Its main role is that of intermediation. It also follows from this that the anonymisation or pseudonymisation of data does not, in itself, comprise a trust role. An anonymisation service on its own does not constitute a data trustee, even though anonymisation may form part of a trustee\u2019s remit. <\/p>\n\n
2.3 Specific use cases \u2013 specific data trustee models<\/h4>\n\n
So what exactly is a data trustee model? The wide variety of answers to this question is primarily due to the fact that the use cases in which trust models are developed vary considerably. The specific areas of application give rise to different requirements regarding the technical, legal and organisational structure of a data trustee. If, for example, personal data is primarily being shared or analysed, technical procedures for anonymisation and pseudonymisation are required and consent management plays a role. An intermediary can handle both of these tasks. The question of whether primary data (\u2018peer-to-peer\u2019) or merely analysis results (\u2018compute to data\u2019 or \u2018algorithm to data\u2019) are transmitted also has implications for both the technical and legal design of a trust model. In the B2B sector, a trust service generally requires agreements that are highly binding (which may include liability, dispute resolution etc.). In the scientific community, the use of a trustee may be subject to fewer legal formalities. In the C2B sector, for example within the context of Personal Information Management Systems (PIMS), which involve data donation, the data transfer service is largely pre-organised at a technical level. <\/p>\n\n
With regard to the legal dimension, there are a number of legal frameworks specific to data trusteeship, including, in particular, data protection law, competition law, financial supervision law, private law and the EU Data Strategy. Which areas of law are relevant, and in what way, depends in turn on the specific use case. Data trustees which act as intermediaries for personal data must comply with the GDPR; where data transfers within the financial sector are concerned, competition law may also come into play. As far as organisational arrangements are concerned, the question of appropriate business models for data trustee schemes is the subject of particularly intense debate. At present, many of the data trustee projects which are currently being set up receive government funding. The possibility of scaling and sustaining such \u2018DTM projects\u2019 depends on whether viable business models can be found. Here too, specific use cases lead to different approaches in terms of the business plan, as well as governance and the choice of legal structure. Data transmission services as defined by the DGA are required to be legally independent but are not required to adopt any specific legal form. At present, the legal forms under discussion include, in particular, associations, co-operatives, foundations, limited liability companies (GmbHs) and public limited companies (AGs). A fundamental and, as such, hotly debated question is that of whether a data trustee model is geared towards the common good. The DGA expressly provides for an \u2018altruistic\u2019 type of new intermediary. <\/p>\n\n
2.4 What value do data trustees provide? <\/h4>\n\n
The value of data trustees lies in their fulfilment of four key functions. Their matchmaking function involves bringing suppliers and customers together on the basis of in-depth market knowledge, thereby reducing their search costs. Furthermore, they play a supporting role by assisting market participants in initiating and carrying out transactions. These include the centralised collection and consolidated provision of market-relevant information, the documentation of transactions and the processing of payments. After all, their trust-based role is intended to reduce information asymmetries and prevent opportunistic behaviour. This enables them to provide expertise before a contract is concluded in order to address information gaps or implement measures to build trust (e.g. vetting participants to ensure they are reputable, providing rating systems). Once a contract has been concluded, they help to monitor compliance with its terms and their involvement in a large number of transactions enables them to realise economies of scale. A fourth function could be described as market pluralisation, as neutral intermediaries are intended to prevent certain typical effects of the \u2018platform economy\u2019, i.e. unintended data outflows, unintended secondary trading in data and the formation of oligopolies. In this respect, data trustee models are an instrument of European data market policy. <\/p>\n\n
3. Future: Challenges and opportunities <\/h3>\n\n
The challenges facing data trustee projects are as great as the hopes and promises of added value associated with them. In the context of tackling major societal challenges, they can be seen as catalysts for data-driven innovation, which are designed to drive a \u2018European\u2019 transformation of the data economy. However, many data trustee projects do not (yet) have a robust business model; initiatives are still at the design stage or in the pilot phase. Similarly, data trustees have lacked visibility thus far. Their benefits and potential, such as the legally compliant provision and use of data via trustworthy infrastructure, are not yet sufficiently well known. Nevertheless, the open experimental environment in which data trustee projects are currently operating remains promising. The diversity of approaches offers the opportunity to learn with and from one another. It is also worth considering whether, and if so how, data trustees are contributing to a noticeable shift in recent years from a data-protection-oriented approach to one that prioritises data utilisation. A key term here is \u2018data sovereignty\u2019. The undoubtedly legitimate security interests of the data providers should be respected and taken seriously. However, data providers\u2019 interest in making their data usable, for example, through data intermediation services, is also legitimate and must not be thwarted, for instance, by excessive consent requirements. The concept of data trusteeship therefore offers the opportunity to reconcile different perspectives in a way that is both innovation-driven and grounded in ethical and normative principles. All those involved should be fully committed to this. <\/p>\n\n
\n\n[1]<\/a> Regulation (EU) 2022\/868 of the European Parliament and of the Council of 30 May 2022 on European data governance and amending Regulation (EU) 2018\/1724 (Data Governance Act), L 152\/2.<\/p>\n","protected":false},"excerpt":{"rendered":"Whilst \u2018trust\u2019 or \u2018trustee\u2019 had long been a rather outdated legal term, the digital age has seen the emergence of the \u2018data trustee\u2019 as a new model for the \u2018sharing\u2019…<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_price":"","_stock":"","_tribe_ticket_header":"","_tribe_default_ticket_provider":"","_tribe_ticket_capacity":"","_ticket_start_date":"","_ticket_end_date":"","_tribe_ticket_show_description":"","_tribe_ticket_show_not_going":false,"_tribe_ticket_use_global_stock":"","_tribe_ticket_global_stock_level":"","_global_stock_mode":"","_global_stock_cap":"","_tribe_rsvp_for_event":"","_tribe_ticket_going_count":"","_tribe_ticket_not_going_count":"","_tribe_tickets_list":"[]","_tribe_ticket_has_attendee_info_fields":false,"_kad_post_transparent":"","_kad_post_title":"","_kad_post_layout":"","_kad_post_sidebar_id":"","_kad_post_content_style":"","_kad_post_vertical_padding":"","_kad_post_feature":"","_kad_post_feature_position":"","_kad_post_header":false,"_kad_post_footer":false,"_kad_post_classname":"","footnotes":""},"coauthors":[221],"class_list":["post-5045","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/datnet.eu\/en\/wp-json\/wp\/v2\/pages\/5045","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/datnet.eu\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/datnet.eu\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/datnet.eu\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/datnet.eu\/en\/wp-json\/wp\/v2\/comments?post=5045"}],"version-history":[{"count":1,"href":"https:\/\/datnet.eu\/en\/wp-json\/wp\/v2\/pages\/5045\/revisions"}],"predecessor-version":[{"id":5046,"href":"https:\/\/datnet.eu\/en\/wp-json\/wp\/v2\/pages\/5045\/revisions\/5046"}],"wp:attachment":[{"href":"https:\/\/datnet.eu\/en\/wp-json\/wp\/v2\/media?parent=5045"}],"wp:term":[{"taxonomy":"author","embeddable":true,"href":"https:\/\/datnet.eu\/en\/wp-json\/wp\/v2\/coauthors?post=5045"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}