Fraunhofer Institute for Software and Systems EngineeringAs data is increasingly recognized as a valuable asset, effective inter-organizational data sharing becomes crucial to utilize its full potential. However, a lack of trust still prevents the widespread adoption of data ecosystems. In a collaboration, Fujitsu and Fraunhofer ISST developed Levels of Assurance for Data Trustworthiness (Data LoA), an assurance framework designed to promote trust and transparency beyond company and country borders, thereby overcoming existing trust issues.
Fujitsu
Enhancing Trust in Inter-Organizational Data Sharing through Levels of Assurance for Data Trustworthiness
The Challenge
The growing reliance on data emphasizes its critical role in digital transformation and innovation. Consequently, inter-organizational data sharing is gaining traction. However, organizations often hesitate to share data due to trust and transparency issues, primarily stemming from concerns about data sovereignty, i.e. data providers’ fear of losing control over their data.
Much effort has been put into overcoming these trust issues, yet the risks faced by data consumers have been neglected. Data consumers face significant risks from inadequate measures by data providers, leading to potential financial losses or harm from compromised data. Data consumers often have no choice but to trust providers, as establishing trust in the data itself is challenging.
Our Service
In a joint effort with Fujitsu, we developed Data LoA, a novel framework establishing a comprehensive, standardized approach for assuring data trustworthiness in inter-organizational contexts. The framework is designed to empower data consumers with the capability to assess risks associated with utilizing shared data assets effectively.
Additionally, it equips data providers with standardized principles for establishing varying levels of trustworthiness assurances. By focusing on the interactions between data consumers, data providers, and assurance providers, Data LoA creates a robust mechanism for enhancing trust in data sharing activities. Our effort paves the way for a more transparent and reliable data sharing ecosystem, ultimately fostering greater confidence among organizations.
The Result
Data LoA is designed to enhance trust and reduce risks in inter-organizational data sharing. Offering a structured method to evaluate data trustworthiness allows data consumers to confidently assess the reliability of third-party data. Simultaneously, it enables providers to communicate the trustworthiness of their data clearly, promoting transparency. Data LoA adds to a responsible data sharing environment, encouraging organizations to collaborate without the fear of compromising their operational integrity, promoting trust among actors.
Partner
- Fujitsu Research