Introducing Xiaoli and the FAIR Workflows Project

I’m glad to report that at the tail-end (hopefully, but probably a long tail just like the reuse of research data) of the dark tunnel that’s the COVID pandemic, there’s a new beginning for me – I’m excited to join DataCite as the Implementing FAIR Workflows Project Lead (remember this ?). For the next 3 years, I will be engaged in the daily work of the project working with the core team which consists of project director Helena Cousijn and colleagues at the Max Planck Institute of Empirical Aesthetics.

I’ve been devoted to Open Science work and active in the community since 2013, throughout the end of my master and the bulk of my Ph.D. years studying Library and Information Science, I worked with the data management team at CERN on several projects including the upgrade of the INSPIRE digital library and Open Data Portal, and research for the CERN Analysis Preservation. I also led the CERN effort on communication/engagement for the EC-funded THOR Project. I’m passionate about Open Science and invigorated to witness the increasingly enthused engagement of the many stakeholders in scholarly communication in a great number of Open Science initiatives, supported by the PID infrastructure provided by organizations like DataCite.

The Implementing FAIR Workflows Project is a multi-partner, 3-year collaborative project funded by the Templeton World Charity Foundation, aimed to provide an exemplar FAIR and Open workflow based on the reality of an entire research lifecycle. DataCite will be working closely with Professor Lucia Melloni’s research team to build a specification for a FAIR workflow through the implementation of PIDs with tailored metadata solutions for various elements of research, including pre-registrations, investigators, articles, datasets, data management plans, grants/ awards, organizations and more. The workflow will then be applied to a multi-modal imaging experiment on consciousness to provide a proof of concept, and the combination of the data from the research and the metadata from the research artifact will culminate into an open interface that display citation and data usage, which will allow researchers to track connections among artifacts. A parallel sustainability effort will be carried out to pave way for further dissemination and adoption of the FAIR workflow.

The project will benefit from the valued contribution and consultation by the project partner and supporter organizations: Australian Research Data Commons, California Digital Library, Chronos Hub, Dryad, Stanford University, Center for Open Science, and Crossref.

Going forward I will be sharing the progress of the FAIR Workflows project with the community on a regular basis, keep your eyes peeled!

This project was made possible through the support of a grant from Templeton World Charity Foundation, Inc. The opinions expressed in this publication are those of the author(s) and do not necessarily reflect the views of Templeton World Charity Foundation, Inc.

Xiaoli Chen
FAIR Workflows Project Lead at DataCite | Blog posts