LiveData -- A Worldwide Data Mesh for Stratified Data
Simone Bocca, Amarsanaa Ganbold, Tsolmon Zundui
TL;DR
The paper tackles the challenge of cross-country data reuse in the presence of heterogeneity by proposing LiveData, a worldwide data mesh that reframes heterogeneity as information diversity. It introduces the iTelos methodology to convert low-quality data into four interconnected diversity-aware dataset types—Standardised, Language, Knowledge, and Graph-based—culminating in RDF Knowledge Graphs with rich metadata for discovery and reuse. The architecture partitions each node into a Data Repository, iTelos framework, services, and a data catalogue, enabling decentralized data ownership and product-oriented data distribution. By linking datasets across nodes and supporting compositional data products, LiveData aims to reduce integration costs and improve interoperability, demonstrated through an initial cross-country use case between UNITN and NUM. The work emphasizes a practical path toward scalable, cross-domain data sharing with explicit metadata-driven connectivity and diversity-aware data products, potentially enhancing collaboration and analytics across borders.
Abstract
Data reuse is fundamental for reducing the data integration effort required to build data supporting new applications, especially in data scarcity contexts. However, data reuse requires to deal with data heterogeneity, which is always present in data coming from different sources. Such heterogeneity appears at different levels, like the language used by the data, the structure of the information it represents, and the data types and formats adopted by the datasets. Despite the valuable insights gained by reusing data across contexts, dealing with data heterogeneity is still a high price to pay. Additionally, data reuse is hampered by the lack of data distribution infrastructures supporting the production and distribution of quality and interoperable data. These issues affecting data reuse are amplified considering cross-country data reuse, where geographical and cultural differences are more pronounced. In this paper, we propose LiveData, a cross-country data distribution network handling high quality and diversity-aware data. LiveData is composed by different nodes having an architecture providing components for the generation and distribution of a new type of data, where heterogeneity is transformed into information diversity and considered as a feature, explicitly defined and used to satisfy the data users purposes. This paper presents the specification of the LiveData network, by defining the architecture and the type of data handled by its nodes. This specification is currently being used to implement a concrete use case for data reuse and integration between the University of Trento (Italy) and the National University of Mongolia.