Multidisciplinary Data Science Collaborations

Made Trustful and Easy

Many data science projects today struggle to be efficient. It is difficult to identify available data, and then even more to share it; those who share data are often not recognized for their contribution; it is a struggle to keep track of versions of data; it is hard to see what code and data were used by whom to produce what results.
RENKU is an open platform that addresses these problems. RENKU supports versioning of data and code; RENKU tracks which results were produced by whom and when. RENKU makes it possible to have greater trust in results and acknowledge the contributions of all those involved, regardless of whether their contribution was to implement the solution, provide the data, or ask the right questions.


And RENKU does this without getting in the way of your established style of working.


Trust in data

The platform promotes open data and science. This is a true incentive for researchers to post high quality, curated data enhances the trust other researchers have in the material provided, therefore making RENKU a real one-stop shop for high quality data.

Trust in science

Scientists can stand on the shoulders of giants by comparing their science against state of the art techniques and methods. By doing so, they build on existing research and enable the reusability of trusted science.

Trust in the community

RENKU’s philosophy is to mobilize and connect skills from the data science community, enhance their collective intelligence, and finally allow for the discovery of unforeseen knowledge.



A real Git for data science, RENKU fosters reproducible research by enabling scientists to retrieve history and data provenance, and go back in time to every step of published science.

Reusability and repetition

The platform facilitates the sharing and reuse of data and algorithms, and empowers specialists to use other people’s work in their own projects and execute them in an infrastructure agnostic environment. Attributions are therefore also consistently guaranteed.


RENKU supports a collaborative environment for dynamic and interactive prototyping by enabling content-rich discussions.


Data is safe with RENKU. It makes use of state of the art security and privacy preserving technologies and  best practices. It will give fine grained control over who accesses any data, from where and how.


RENKU is designed to connect independently administered platforms and positions itself as a unique one-stop shop for high quality data by allowing a federated access across institutions, giving each the freedom to enforce its own access controls over resources.


Thanks to its automatically maintained and enriched knowledge graph, the platform supports targeted exploration as well as unforeseen discoveries by giving scientists access to the big picture through interconnected metadata. Science is thus described in a straightforward, intelligible manner.



We have seen that RENKU can provide a functionality that is missing in any other tools we explored, as it enables traceability of all steps and data sources in the hypothesis-model-data-evaluation workflow. We believe that RENKU will be a game changer for the scientific community as it records and preserves links between elements of different projects, which is currently not possible through scientific papers and citations alone.

Stan Schymanski
Luxembourg Institute of Science and Technology (LIST)

The challenges with working on data science projects in a company rely on involving different stakeholders with different exposure levels to technologies and tools required to gather, treat, explore and analyze data. As projects’ complexity grows, a collaborative framework that allows teams spread around diverse locations and with different backgrounds to work together is needed. To address those challenges we use RENKU in our pipeline to bring versioning and reproducibility to our data science work flow, complementing our software development stack. RENKU is a ready-to-deploy working environment, without requiring admin access and lengthy setups. Such a platform allows us to validate and disseminate results, and is an essential pillar to the success of a project.


Hông-Ân Sandlin
Data Scientist, Bühler AG

We would like to warmly thank the SDSC for the job done. The SDSC has managed to provide PSA with relevant methodologies in regards with data governance and data management, and also provided valuable insights in the specifics of PSA repair activity. We have much appreciated the flexibility the SDSC team has shown throughout the project. PSA has learned a great deal in regards with its data management. The SDSC has proved itself to combine a scientific approach with an operational, down-to-earth, objective-driven attitude, which is precisely what we were looking for.


David Allard
StelLab@EPFL innovation outpost Manager

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