Due to the increasing uptake of semantic technologies, ontologies are now part of a good
number of information systems. As a result, software development teams that have to combine …

It is commonly agreed that in silico scientific experiments should be executable and repeatable
processes. Most of the current approaches for computational experiment conservation …

In the past decades, one of the most common forms of addressing reproducibility in scientific
workflow-based computational science has consisted of tracking the provenance of the …

Reproducibility of published results is a cornerstone in scientific publishing and progress.
Therefore, the scientific community has been encouraging authors and editors to publish their …

Data scarcity is a common and challenging issue when working with Artificial Intelligence
solutions, especially those including Deep Learning (DL) models for tasks such as image …

Posts published in the social media are a good source of feedback to assess the impact of
advertising campaigns. Whereas most of the published corpora of messages in the Sentiment …

The data retrieved from satellite imagery and ground-based photometers are the two main
sources of information on light pollution and are thus the two main tools for tackling the …

In this demo we present OnToology, a tool for developing ontologies collaboratively using
Github. OnToology addresses several steps of the ontology development lifecycle, including …

Reproducible research in scientific workflows is often addressed by tracking the provenance
of the produced results. While this approach allows inspecting intermediate and final results…

Statistics data is often published as tabular data by statistics offices and governmental
agencies. In last years, many of these institutions have addressed an interoperable way of …