Digital Science, a technology company serving stakeholders across the research ecosystem, welcomes two US-based startups to the Digital Science family of companies: automated reproducibility assessment tool, Ripeta, and data science platform, Gigantum.
Both companies are playing a key role in making scientific research reproducible and more transparent. Ripeta is developing a “credit report” for scientific publications to assess and help improve the transparency needed to effectively communicate research, while Gigantum is an emerging innovator in the area of data science platforms, supporting large-scale, data-oriented scientific research.
Daniel Hook, CEO of Digital Science, said: “Reproducibility of research is one of the critical topics of modern times – if research is to remain trusted by the populations who fund it, then researchers must ensure that their research can be reproduced by others.”
Ripeta, a previous Digital Science Catalyst grant winner, aims to make better science easier by identifying and highlighting the important parts of research that should be transparently presented in a manuscript and other materials. The tool detects the key evidence for and assesses reproducibility in the scientific research industry through software and analytics development; improving evidence-based science and fiscal efficiency of research investments. These tools leverage sophisticated machine-learning and natural language processing algorithms to extract key reproducibility elements from research articles.
Ripeta focuses on assessing the quality of the reporting and robustness of the scientific method rather than the quality of the science. The company’s long-term goal includes developing a suite of tools across the broader spectrum of sciences to understand and measure the key standards and limitations for scientific reproducibility across the research lifecycle and enable an automated approach to their assessment and dissemination.
Leslie McIntosh, CEO of Ripeta, said: “While technological innovations have accelerated scientific discoveries, they have complicated scientific reporting. Science is hard and reproducibility is important, so we need to make better science easier.
“We are developing the tools to make research methods transparent, enabling the verifiability, falsifiability and reproducibility of research. We are thrilled to receive this investment with the great team at Digital Science who provide a fantastic partnership. This will propel our work at Ripeta helping make scientific reporting more transparent.”
Gigantum is a completely new approach to handling the interaction between code, data and run-time environments in this new data-rich research world. Focused on open-source tools and frameworks, Gigantum helps researchers to better scale the creation, management and dissemination of fully reproducible research and the data science that supports it.
Gigantum seeks to develop a platform that keeps pace with the expanding number of independently created tools and data sources, thereby serving an increasingly diverse but collaborative set of researchers with non-uniform skills, interests, and resources. The team’s technical approach is based on their appreciation that the automated management of data, code, environment, and version history is fundamental to enabling decentralized collaboration.
Dean Kleissas, Gigantum CTO, said: “Despite wide adoption of open-source tools and growing willingness to share research code and data, we still can’t quite escape the evolving difficulties of publishing transparent and easily reproducible research for broad use and consumption.
“When we first spoke with Digital Science, I knew it was a good fit because we immediately clicked on the fact that best practices alone won’t do it. We need technological approaches that enable real changes in what people of all skill levels can do, not just the most skilled.”
“Gigantum and Ripeta together address two of the biggest aspects of reproducibility: workflow and communication. Through Gigantum, a researcher can ensure that they have the full provenance of the data objects that appear in their papers, allowing anyone to repeat their data processing and analysis with ease,” adds Hook.
“With Ripeta, a researcher is able to check that they have correctly described and referred to the data, methodology and analysis approaches that underpin their arguments.”