The task of computing composite indicators to define and analyze complex social, economic, political, or environmental phenomena has traditionally been the exclusive competence of statistical offices. Nowadays, the availability of increasing volumes of data and the emergence of the open data movemen...

The enrichment of a dataset with information coming from third-party data sources is a common data preparation task in data sci- ence. Semantic technologies and linked open data can provide valuable support for this task, paving the way for new data-scientist-friendly tools that may facilitate effor...

In the business environment, knowledge of company data is essential for a variety of tasks. The European funded project euBusinessGraph enables the establishment of a company data platform where data providers and consumers can publish and access company data. The core of the platform is the semanti...

Digital marketing is a domain where data analytics are a key factor to gaining competitive advantage and return of investment for companies running and monetizing digital marketing campaigns on, e.g., search engines and social media. In this paper, we propose an end-to-end approach to enrich marketi...

Linked Data exploration is an essential task in the process of understanding, assessing, and using datasets made available in the Resource Description Framework (RDF) format. Current solutions for exploration of RDF data are mainly targeted at Semantic Web experts, require non-trivial deployments, a...

Data preprocessing is a crucial step in data analysis. A substantial amount of time is spent on data transformation tasks such as data formatting, modification, extraction, and enrichment, typically making it more convenient for users to work with systems that can recommend most relevant transformat...

A growing amount of public procurement data is being made available in the EU for the purpose of improving the effectiveness, efficiency, transparency, and accountability of government spending. However, there is a large heterogeneity, due to the lack of common data formats and models. To this end, ...