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Certification & Governance management (EV ILVO)

flowchart LR
    UM(User Management) --> CG("`**Certification & Governance management**`")
    DPU(Data & Knowledge publication) --> CG

??? question to allign on: is this governance related to:

  • connecting with a data space,
  • setting up the SWR as a data space
  • or common usage of data and knowledge by users? In case of the latter are we not further distributing "open data" and what extra governance policies do we need?



Soilwise plans to implement a governance framework to tackle the challenge of ensuring equitable access to and utilization of data and knowledge. This framework aims to foster data sharing and enable the generation of value from these resources. A governance framework encompasses a set of principles, standards, policies (rules/regulations), and practices. Additionally, the framework addresses the enforcement of these measures and the resolution of any conflicts that may arise.

The governance framework will be designed by integrating relevant EU legislation concerning governance within data ecosystems, alongside insights from ongoing Digital Europe CSA projects focused on constructing the Common European Data Spaces. The formulation of this governance framework will rely mainly on the Data Spaces Support Centre (DSSC) results which are:

  1. Starter Kit, a document that helps organizations and individuals understand the requirements for creating a data space by providing. a multifaceted view of data spaces, highlighting business, legal and governance, operational, functional, and technical aspects to consider
  2. Glossary
  3. Blueprint, a consistent and comprehensive set of guidelines to support the development cycle of data spaces.

Additionally, the DSSC proposes the utilization of the Building Blocks Taxonomy, which serves as a classification scheme. This taxonomy aids in describing, analyzing, and organizing data space initiatives based on predefined characteristics, thus promoting a structured approach to governance implementation (Figure 1). We will equally consider the openDEI design principles for data spaces, the requirements of ISO 30401 for KM and rely on the results of the preparatory action for the data space for Agriculture (AgriDataSpace).


img_governance.png

Following the introduction of the GDPR, the European Commission has put forward several legislative proposals, such as the Digital Services Act, the Digital Markets Act, the Data Act, and the Data Governance Act. Soilwise places particular emphasis on the Data Governance Act and the Data Act, as their primary goals align closely with the project's aims to enhance data sharing and facilitate product development. These legislations are designed to:

  • Promote equity in the distribution of value derived from data across various stakeholders.
  • Enhance access to data and its utilization.

The documents described in the higher paragraphs will be used to asses if the technical components used to develop and implement SWR meet the necessities for the governance of the data ecosystem. If this is not the case technical components adhering the governance requirements will be integrated in further iterations of the project.

  • governance
  • interoperability
  • clearing house, broker, ...

  • vocabulary provider (connects to knowledge graph)

  • connections with: external repo, identity providers, connectors, UI/UX

SoilWise Data Spaces (EV ILVO + WE)

T1.4 will produce detailed technical specifications, including information on components to be (re)used, interfaces between them and explaining the data flows and processing schemes, considering AgriDataSpace project conceptual reference architecture, AI/ML architecture patterns and the Ethics by Design in AI.

--- WE ---

A Data Space is a type of collaboration model defined as a decentralized infrastructure (where data is not stored centrally, but at the source) for trusted data sharing and exchange in data ecosystems, based on commonly agreed principles. There is no central repository into which data providers supply their data and from which consumers can access and retrieve data. Instead, data is exchanged directly between appropriate parties.

Data Space facilitates the secure exchange, linkage, and interoperability of data within a confined ecosystem, based on standards and collaborative governance models, while preserving the digital sovereignty of data owners. Data spaces enable the use of data that may not be open but provides a certain level of accessibility.

Reference_architecture_model_IDSA

Image credited to IDSA: The Reference Architecture Model

Components/ Design of a data space (based on the IDSA)

There are different approaches to designing data spaces, but the IDS-RAM (reference architecture model) of IDSA the International Data Space Association, which is characterized by an open, reliable and federated architecture for cross-sectoral data exchange, can be taken as a benchmark, containing at least a basic set of components necessary to build a robust data space.

The most important components of Data Spaces are briefly described below.

Connectors

The Connector is the central technical component for secure and trusted data exchange, through which participants access data in a Data Space. It is handling the data according to policies defined by the data owner interms of access and usage rights, thus ensuring its sovereignty. IDS connectors for instance can publish the description of their data endpoints atan IDS meta-data broker. This allows potential data consumers to look up available data sources and data in terms of content, structure quality, actuality and other attributes (source: IDSA).

Connectors can be certified in order to prevent malfunctionand to guarantee their integrity and compliance. 

Intermediaries

Intermediaries are services provided by third parties that are necessary for publishing, searching and registering transactions. Some of the intermediaries are: 

Vocabulary providers

Vocabulary providers manage and offer vocabularies and ontologies, reference data models and metadata to annotate and classify data sets, describe the datasets’ relationships and define possible constraints. This allows data to be systematically organized, categorized and labelled, thus improving interoperability.

Metadata broker

According to IDSA, the Metadata Broker forms the reference implementation for registration and search functionality compliant with International Data Spaces. As such, it follows the generic connector architecture described in the reference architecture model.

Identity providers

An identity provider is a system entity that creates, maintains, manages and validates identity information for clients and also provides authentication services for trusted applications within a federated or distributed network. (Source: wiki).

Clearing house

Clearing house allows to keep control of the operations carried out. The IDS clearing house for instance provides decentralized and auditable traceability of all transactions if needed.

CONNECTOR:

  • config and control of data access
  • config and control of data usage

  • user authorisation for data access

  • connections with: Storage, APIs

  • technologies used: Eclipse Dataspace Components Connector
  • responsible person: Thorsten Reitz
  • participating: