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Usecases

All sectors are concerned at different scales.

• B2B & B2C can share data to unlock new insights and opportunities for businesses and customers • Communities can leverage collective intelligence and crowdsource data

Agriculture​

The agriculture supply chain relies on several interdependent actors, from the field to the fork. They need efficient information systems to better evaluate, manage and value the efforts made and the agri-environmental benefits associated to the practices. Moreover, they need to share data to create knowledge valuable at each link of the chain.

Crossing technical and accounting data from multiple providers (farmers, accountants, cooperatives, advisors...) can generate unique insights sold to industries, brands, retail and local authorities and provide transparency to end-consumers.

But knowledge created from these data can go way beyond traceability of practices. It can provide valuable insights for companies, public authorities or even new opportunities to develop new applications on top of the shared data. For exemple to feed agro-ecological machine learning models or business intelligence tools. Moreover, data sharing between these actors is able to lead to new indicators and thus a greater knowledge of what is produced on a farm and how.

For instance, accountants of farmers can share, with the consent of farmers, economical data with other actors such as cooperatives and technical advisors who can share, on their side, technical data of those farmers. A data space can guarantee that accountants will never see the technical data and reversely. The authorized actors see only the insights resulting from data treatment and calculation services. These actors, the knowledge consumers, use the new insights to provide consulting service to farmers. The members of the data space decide the policies to share the value. The business model described in the data space makes sure that the value created by the service is shared between all the contributors (data and services providers).

To go further, public institution can integrate the Data Space to have access to indicators they are not able to get otherwise. For instance, water authorities need to pilot the quality of fresh water. Knowing that agriculture is one of the main factors of pollution and eutrophication, it would be profitable for water agencies to follow indicators of farming practices that reduce chemical fertilizers use and limit nitrate leaching such as the share of legumes in the rotations or the implantation of intermediate crops.

Gaming and Metaverse​

The Metaverse, seen as the future of our digital interactions, is merely updating old aspirations. The risk of the Metaverse, however, is the expansion of data collection (in volume and type of data) which could prove problematic if its development is not mastered. The Metaverse is inextricably linked to Big Data.

Facebook has taken the first shot at the Metaverse market, but it is already not alone in this project as the gradual transformation of Fortnite into a virtual living space shows. There is no doubt that other major digital players will position themselves on these new access modes. This innovation could well be the starting point of a new digital era.

Metaverses present a risk of technological lock-in and data sovereignty. If we had total control over this data collection, according to rules defined by the participants, the Metaverse could then interconnect, passing information and data between them (one can think of one's avatar, which would have the same properties in several of these worlds).

We know that an action in the Metaverse can lead to an action in real life. Nike, for example, is building a "virtual shop" in the game world The Sandbox. It would be beneficial to both parties if The Sandbox and Nike had a common data space so that a potential customer's data could be fed directly into the Nike virtual shop interface from within The Sandbox game and the buying journey reduced. The Data Space governs in this case the data sharing rules (which data is shared to the virtual shop by The Sandbox), the business model (how this data is paid by Nike to The Sandbox) and the interactions between these two actors.

Users, once connected in this Metaverse, visit the Nike shop, and can, directly during the game, make a purchase that will be delivered to their home. Thanks to this pooling and sharing of data between these players, users will not need to change their interface or device. Everything can be done directly inside The Sandbox thanks to this Data Space.

Finally, the Data Space specifies the modalities of entry by new members. This Data Space can therefore quickly integrate other brands or be replicated with different data sharing conditions.

Health: Cancer treatment​

For more than a decade, the use of tumour cell-specific monoclonal antibodies has been one of the major 'revolutions' in the fight against cancer. More recently, similar antibodies coupled with chemotherapies have proven to be effective. However, the effects of these treatments remain insufficient. Unfortunately, some patients are not sensitive to them, and relapses are observed. Today we do not know how to treat all cancers. Why not? Because we lack knowledge.

Today, there is a serious lack of data to analyse, whether on new treatments, past elements, triggers, complications, causes, immunities... but why? Because researchers, laboratories or hospitals do not share enough and do not pool their data sufficiently in order to analyse them to create new knowledge.

It is almost certain that if private laboratories as well as many hospitals were to share more of their data for research purposes, we would find similarities, differences and other information that is now untraceable. Unfindable because the data is in silos, locked up and not communicating with each other. A data sharing ecosystem (Data Space) of this scale could allow the world of medical research to take a big step into the future. This Data Space would allow all these actors to guarantee trust, security, and respect for patients' consents across the entire ecosystem. Thus, organisations would be able to choose the conditions of data sharing (sharing or exchange of datasets, anonymisation or pseudonimisation mandatory or not, which datasets) and the economic model that suits them (total free of charge for hospitals only or remuneration, marketplace or sharing of the value generated).

Thus, this Data Space would enable the sharing of medical data between private and public actors by guaranteeing trust, security and respect for patients' consents throughout the ecosystem, but also by aligning the interests of the various stakeholders. And all this to create life-saving knowledge.

Supply chain​

Between 2015 and 2022, the volume of data created annually has increased more than sixfold. Data sharing is at the heart of tomorrow's Industry 4.0. Preventive maintenance or production automation: many industrial processes today depend on their analysis. However, it is necessary to look beyond the walls of the factory. By restricting themselves to analysing their own data, supply chain actors limit the scope of their possibilities. Data sharing is a major lever for performance and competitiveness. Reactivity of the production chain, innovation, precise monitoring, risk management are only some of the possibilities. How can companies take advantage of this data? In what context can data sharing be used? And above all, what are the benefits?

  • Cost reduction. Sharing data between actors in the supply chain results in greater precision in the management of activities and financial, human or material resources. For example, an in-depth knowledge of the production and sales rhythms of all players, as well as the use of resources, would enable factories to reduce their stocks and consequently the associated costs.
  • Better collaboration. Interoperability and collaboration of systems are at the heart of the data sharing model. This implies cooperation and promotes coordination between partners. Geographical, temporal or informational distance is one of the major challenges of supply chain management. The development of our solution would make it possible to overcome this and to create a climate of trust between all the players in the same supply chain.
  • Quality and efficiency of production. Thanks to data sharing, each actor in the supply chain would have in-depth knowledge of its structure and the dynamics that govern it. Thanks to the Data Space, its actors would be able to take joint decisions at any time in order to respond to a crisis situation or to improve processes; this would make them more efficient. In addition, manufacturers can, for example, ensure that raw materials are available or that production conditions meet customer requirements (quality, safety, ethics, etc.).
  • Risk management. GPS control of deliveries, real-time evaluation of equipment performance, stock levels, traceability of resources, predictive maintenance... Players now have the necessary monitoring means to identify threatening risks and provide the necessary solutions before suffering the repercussions.

A Data Space would provide a framework of trust for supply chain actors to share data and create value by reducing costs, improving efficiency and productivity and having better risk management. The actors must first define the governance of their Data Space and therefore the rules including those ones :

  • data management: where the data is stored, who has access to which indicators and/or raw data
  • data security: whether data should be encrypted or not
  • business model: each data or service provider is paid each time the processing workflow is launched (i.e. the indicators are updated)

Public sanitation in developping countries​

The construction of toilets and hand-washing facilities in schools in Vietnam's rural provinces is helping students develop better hygiene habits and have a better chance of staying healthy. According to UNICEF, inadequate access to water, sanitation and hygiene such as this remains a major problem for many children in rural Vietnam (a problem that extends to any other region of the world in the same situation). Many families do not have toilets at home and are therefore forced to defecate in their backyards. Without access to a toilet at home, for some children, school is their only access to a toilet.

But when schools also lack adequate sanitation facilities, this contributes to poor learning outcomes, school absenteeism and an increased risk of diarrhoeal or gastrointestinal diseases (which are one of the top ten causes of death worldwide according to Oxford University, and account for 12% of deaths of children under five in Vietnam).

For several years, NGOs have been trying to help these regions to have better access to water and hygiene. Their actions have led to the development of new hygienic habits by children to better protect their health since then. During these projects, many photos and other information are taken in order to send maintenance personnel, initiate repairs or new constructions. These photos and information are stored by several organizations, in different storages, in very heterogeneous formats.

We could then imagine a Data Space bringing together NGOs, sanitation companies and hygiene access solution builders. The associations would take photos and share them within the Data Space. In the Data Space, the data would be shared free of charge with NGOs and other associations that wish to help them or for public research for example. In parallel, it could be shared for a fee with companies for analysis or market research. The Data Space would also include various processing services such as format conversion services or AI services to assess the state of the facilities and evaluate where to prioritize for further interventions.