Catalyst Grant Supports Simplified Workflow

Editing tools developed for improving workflows in publishing and machine-learning were announced as the latest winners of a Catalyst Grant supporting early stage development of concepts with the potential to transform scientific and academic research.

The projects, SciSwipe (Switzerland) and SciFlow(Germany) have each been awarded up to £25,000 or $30,000, by research industry technology company Digital Science.

SciSwipe is a data pipeline platform which breaks down complex, large-scale datasets into simple images the public can view and label. Labeled reference sets are a prerequisite for supervised machine learning.

"Crowdsourced exploration of complex, large-scale data holds great potential - a trained computer can mine nearly infinite amounts of data for clues to improve human health," said co-founder Mariëlle Van Kooten.

"Each user can help train a computer by swiping and in effect labeling a small number of such images on a smartphone, dividing labour and increasing reliability," added co-founder Anton Pols.

SciFlow is a collaborative authoring tool which simplifies writing and publishing workflows for researchers and their institutions. The tool aims to cut down communication time and take away the frustrations of re-formatting multiple manuscript versions and word files. The idea has been developed by founders Dr. Carsten Borchert and Frederik Eichler, who as students both found problems with formatting publishing software with research data.

“Research institutions and libraries follow our vision to re-establish the library as the best place to produce and access knowledge for researchers and millions of knowledge workers worldwide,” said Eichler.

SciFlow’s tool offers instant collaboration in one place, automated formatting and reference management works with drag and drop. The tool currently has over 1,000 active monthly users and four research institutions including Max Planck Society.