Link prediction with VeTo

VeTo+ is a novel approach that effectively deals with the problem of expert finding in academia by exploiting scholarly knowledge graphs. It expands a given set of experts with new individuals, sharing similar expertise, by identifying scholars having similar publishing […]

sHINER: Entity Resolution with Graph Generating Dependencies

sHINER is a tool made for validating and repairing a new class of graph dependencies named Graph Generating Dependencies (GGDs). The Graph Generating Dependencies is a new class of graph dependencies proposed for property graphs inspired by the tuple- and […]


Our paper entitled “Discovering Mixture-Based Best Regions of Arbitrary Shape” by Dimitrios Skoutas, Dimitris Sacharidis and Kostas Patroumpas was presented at SIGSPATIAL 2021 on November 4th. Given a collection of geospatial points of different types, mixture-based best region search aims […]

HIN exploration and analysis with SciNeM

SciNeM is a data science tool for metapath-based querying and analysis of Heterogeneous Information Networks (HINs). It currently supports the following operations, given a user-specified metapath: (i) ranking entities using a random walk mode, (ii) retrieving the most similar pairs […]

EDBT 2021

The EDBT 2021 Conference will take place online during March 23 – 26. The program includes two presentations involving work carried out in the context of the SmartDataLake project: – SciNeM: A Scalable Data Science Tool for Heterogeneous Network Mining. […]

Project Facts
SmartDataLake is a Research and Innovation action funded by the Horizon 2020 Framework Programme of the European Union.

Project Full Title: Sustainable Data Lakes for Extreme-Scale Analytics

Topic: ICT-12-2018-2020 - Big Data technologies and extreme-scale analytics

Grant Agreement No: 825041

Duration: 36 months (1/2019 – 12/2021)

Coordinated by : IMSI / Athena RC