activity
20182022
most citedUser-friendly Composition of FAIR Workflows in a Notebook Environment

10 citations · 19 across the 6 of their papers we have counts for

collaborators

9 papers

q-bio.QM2022

BioSimulators: a central registry of simulation engines and services for recommending specific tools

Bilal Shaikh, Lucian P. Smith, Dan Vasilescu +68

Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, becau…

cs.DC20222 cited

LUCE: A Blockchain-based data sharing platform for monitoring data license accountability and compliance

Visara Urovi, Vikas Jaiman, Arno Angerer +1

Easy access to data is one of the main avenues to accelerate scientific research. As a key element of scientific innovations, data sharing allows the reproduction of results, helps…

cs.HC202110 cited

User-friendly Composition of FAIR Workflows in a Notebook Environment

Robin A Richardson, Remzi Celebi, Sven van der Burg +4

There has been a large focus in recent years on making assets in scientific research findable, accessible, interoperable and reusable, collectively known as the FAIR principles. A…

cs.AI20201 cited

Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019

Nacira Abbas, Kholoud Alghamdi, Mortaza Alinam +71

One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is…

cs.LG20193 cited

Towards FAIR protocols and workflows: The OpenPREDICT case study

Remzi Celebi, Joao Rebelo Moreira, Ahmed A. Hassan +4

It is essential for the advancement of science that scientists and researchers share, reuse and reproduce workflows and protocols used by others. The FAIR principles are a set of g…

cs.LG20193 cited

Privacy-Preserving Generalized Linear Models using Distributed Block Coordinate Descent

Erik-Jan van Kesteren, Chang Sun, Daniel L. Oberski +2

Combining data from varied sources has considerable potential for knowledge discovery: collaborating data parties can mine data in an expanded feature space, allowing them to explo…