LEADS: Large-Scale Elastic Architecture for Data as a Service

There is a wealth of publicly available data in today's Internet (e.g. Web pages, government law texts, public statistics, media archives, etc.) that can be exploited by large and small companies in various business domains. Storing, processing, and querying such ever increasing amounts of data is becoming a major challenge, and having the capability to do so is a strong asset for the few big companies with sufficient infrastructural resources. For instance, it is not possible for many small companies to mine publicly available content on the Internet because they do not have the means to build, access or store a complete graph of the Web.LEADS is based on the premise that, instead of maintaining data in-house in dedicated data centres, it is both economically and ecologically better to store it in a shared infrastructure. Its objective is to build a decentral-ized Data-as-a-Service (DaaS) framework that runs on an elastic collection of micro-clouds. LEADS will provide means to gather, store, and query publicly available data, as well as process this data in real-time. In addition, the public data can be enriched with private data maintained on behalf of a client, and the processing of the real-time data can be augmented with historical versions of the public and private data. The platform will be designed from the ground up to account for privacy, security, energy-efficiency, availability, elastic scalability, and performance considerations. The project will be validated on use-cases involving the crawling of Web data and its exploitation in different application domains.
The project website will be http://www.leads-project.eu/