Customer Story:
Washington University in St. Louis
At Washington University in St. Louis, TIND RDM has played an important role in enhancing the discoverability and reusability of research data by driving adherence to the FAIR principles, integrating their data curation and publication workflow with DataCite, and fostering collaboration through the Data Curation Network (DCN).
Washington University in St. Louis is a private research university located in St. Louis County and Clayton, Missouri. It is ranked among the top universities in the United States.
Washington University in St. Louis is committed to sharing datasets in the most comprehensive manner possible. However, they faced challenges with cumbersome data submission and review workflows, as well as limited capabilities in adhering to FAIR (Findable, Accessible, Interoperable, Reusable) practices in their previous repository solution. Before transitioning to TIND, their submission and curation workflows often resulted in inefficiencies and data silos. Data and metadata compliance checklists were managed manually, and correspondence between researchers and administrators was scattered across various email accounts. In 2019, the university established a dedicated task force to explore alternative solutions and enhance their data-sharing practices, with the following criteria in mind:
After conducting a thorough review, Washington University chose TIND RDM due to its alignment with their specific requirements. TIND RDM offers a hosted solution that integrates with DataCite, customizable workflows, a user-friendly interface, expert implementation and migration services, and hands-on customer service.
“We went into the implementation believing with some crossed fingers that all this would be possible. And TIND over-delivered, which is something that you almost never say. We finished on time, and we got everything we wanted. It felt like the implementation team was invested in getting things right for us. It felt like a partnership building this thing”.
Jennifer Moore, Head of Data Service at Washington University in St. Louis
Washington University collaborated with TIND to create a customized submission workflow framework that centralizes and manages interactions throughout the submission process. This streamlined framework benefits researchers, library administrators, and reviewers, ensuring consistency and quality of published materials. TIND implemented two workflows within the framework, one for researchers to submit datasets and one for staff to submit acquired datasets. The dataset submission workflow includes several steps, incorporating forms for selecting curators, managing metadata, and evaluating submissions based on FAIR principles.
Adding value to research through FAIR
For Jennifer and Sarah, aligning with FAIR principles is not just about adhering to standards but about adding value to the research. Since they set out on the path toward a new data repository, FAIR data principles have informed their choices. During this time, they have seen FAIR move from the margins to the center of curation discourse. One of the most significant achievements since transitioning to TIND has been implementing a FAIR evaluation tool within the system to assess the FAIRness of their datasets over time. This tool also considers factors like the completeness and quality of the read-me files. The motivation behind this was not just the universal goal of adhering to FAIR principles but also to understand the practicality of actually achieving FAIR compliance.
TIND RDM has improved the discoverability and reusability of their data through various facets of the implementation and functionality:
TIND provides a robust metadata schema that integrates with DataCite and offers the flexibility of custom fields. This ensures that all uploaded data is accompanied by comprehensive, high-quality metadata. Washington University worked closely with TIND as a stakeholder to implement specific DataCite-related TIND features. These include support for the DataCite 4.4 Related Items field and the display of related items in a dedicated and configurable area of the detailed view. There are also improved DataCite mapping for purposes such as DOI export and support for duplicating updates to TIND records in the corresponding record in the DataCite platform.
TIND supports persistent identifiers such as DOIs, ORCID IDs, and ROR. Jennifer and Sarah highlight the benefits of having the option to make persistent identifiers a mandatory field in TIND and ensuring they are entered in a standardized format.
"One of our key priorities was ensuring that persistent identifiers are not just included but standardized. Previously, we didn't even require basics like an ORCID, but now, that's changed. Our users can easily input a variety of identifiers, creating a dynamic knowledge base. With RORs, we've leveraged this further. It's straightforward for our users to add these details and just as easy for us as administrators to make sure they are there."
TIND RDM offers the flexibility to create multiple submission forms based on different parameters, such as asset type or discipline. This allows you to show only the relevant fields to the researcher, while having a more advanced form on the backend for the curator. This simplifies the submission process while ensuring that all necessary information is included.
The TIND RDM's user-friendly interface simplifies data contribution and administration while also enhancing the institution's perception and branding. Sarah highlights that a modern and appealing repository interface is something contributors can take pride in.
“If people are contributing to a repository, it should look like a contemporary tool they're proud to associate with. This is not only about managing research output but also an opportunity for university branding. It's a way of saying, look at us, we're doing cool things.”
Sarah Swanz, Data Curator at Washington University in St. Louis
WashU's flexible TIND workflow framework allowed them to incorporate structured collaboration with their partners in the Data Curation Network (DCN), an initiative that unites experts in digital curation from various institutions.
WashU needed to share uncurated datasets with network partners. However, since the datasets were not curated yet, access would typically be restricted to internal admins only. They required a system that would allow external DCN curators to access only the specific records they were authorized to see, without granting full administrative privileges.
A customized workflow step was created in TIND RDM to grant network curator access rights for a single record and its associated files. This workflow now seamlessly integrates with DCN's existing Jira ticketing system. When a dataset is submitted, the Jira system notifies the DCN service desk via email.
The team at Washington University has achieved significant progress with the integrated workflow. Jennifer and Sarah were greatly impressed by the expert consultation and service provided by TIND during the workflow implementation.
The collaboration between Washington University and TIND demonstrates the significance of choosing the appropriate tools and platforms to meet the constantly changing demands of data management in academic environments. As emphasized by Jennifer Moore and Sarah Swanz, this is not simply a technical upgrade, but a strategic step toward improving the quality and impact of research by adhering to FAIR principles and implementing efficient data management practices.
