Publications by authors named "Maurizio Lenzerini"
It is well-known that Artificial Intelligence (AI), and in particular Machine Learning (ML), is not effective without good data preparation, as also pointed out by the recent wave of data-centric AI. Data preparation is the process of gathering, transforming and cleaning raw data prior to processing and analysis. Since nowadays data often reside in distributed and heterogeneous data sources, the first activity of data preparation requires collecting data from suitable data sources and data services, often distributed and heterogeneous.
View Article and Find Full Text PDFArticle Synopsis
- The ENCODE project is an expansive public database of over 4,000 experiments and 25,000 data files aimed at unlocking biological knowledge through genomic research.
- Searching for relevant datasets within ENCODE has been challenging due to the simplicity and incompleteness of its metadata and the lack of a coherent ontology.
- To address these limitations, the S.O.S. GeM system was developed, allowing for effective semantic search and retrieval of ENCODE datasets by utilizing a Semantic Knowledge Base that enhances search accuracy and relevance for biologists' queries.