To accelerate innovation and drive change across the community, we participate in or lead funded projects in line with our strategic plan. Projects play an important role in shaping the development of our services, metadata schema, and the wider community we serve. We believe that collaborative projects are instrumental in facilitating the discovery and reuse of research outputs and resources.
Current projects include
- FAIR Island
- Implementing FAIR Workflows
- Make Data Count: A Central Corpus for All Data Citations
- PID Network Germany
IGSN e.V. and DataCite have a common purpose, and building a close relationship has provided mutual benefit to our shared vision of connecting research and advancing knowledge. This project brought years of experience across our organizations and communities to begin realizing goals of scaling sample community engagement, developing sample identifier practice standards, and increasing adoption globally.
The aims of this project were twofold. Firstly, we addressed the need to enable and support the use of PIDs and metadata within NFDI4Ing as an essential component for the implementation of the FAIR principles for research data. Secondly, we built interactive dashboards on the consortium output, showing links, and data reuse via event data and the PID graph.
The Data Infrastructure Capacities for EOSC (DICE) consortium brings together a network of computing and data centers, research infrastructures, and data repositories that propose to enable a European storage and data management infrastructure for EOSC, providing generic services and building blocks to store, find, access, and process data in a consistent and persistent way.
During its 30-month project period, ORCID DE 2 sought to expand and consolidate the existing network of scientific institutions that have already integrated ORCID into their infrastructures. One major goal was the increase of support for institutions and target groups interested in and using ORCID. Furthermore, in the course of ORCID DE 2, a survey about the need for an identification system for organizations will be conducted and implementation explored.
re3data COREF aimed to connect re3data as the reference for research data repositories with other services and infrastructures. By providing customizable and extendable core repository descriptions that are persistently identifiable and can be referred and cited in an appropriate manner, re3data was advanced to facilitate the reuse of reliable and trustworthy information on research data repositories.
This project supplied practical solutions for the use of FAIR data principles throughout the research data life cycle. DataCite collaborated with re3data to make FAIR repositories discoverable.
The PARSEC project addressed the following two issues: 1) large amounts of research data related to the Earth and its ecosystems are either not well preserved or preserved at all and 2) there is also limited information on how diverse data are re-used for research and quantifying the value of curated data for such purposes, and how the quality of data preservation affects these outcomes.
DataCite was involved in the creation of a machine-actionable Data Management Plan (maDMP) funded by the National Institutes of Health (NIH). The maDMP aimed to provide researchers with a structured framework for effectively managing and sharing their data, with DataCite’s involvement focusing on developing guidelines and standards for data citation and persistent identifiers (DOIs) to ensure long-term accessibility and attribution of research data.
NIH’s Big Data to Knowledge (BD2K) Data Commons Pilot initiative tested the feasibility of (and developed best practices for) making NIH-funded datasets and computational tools available through communal, collaborative platforms on public clouds. The BD2K program was an NIH data science program that was launched in 2013 to facilitate the broad use of biomedical big data. DataCite participated in the second phase of the project, which started in December 2017, working with partners to develop Global Unique Identifier (GUID) capability to provide a persistent, machine-resolvable identifier platform for all FAIR objects in the NIH Data Commons that is fully aligned with community practices, recommendations, and metadata models.
FREYA, the successor to THOR, got underway in 2018. The mission of FREYA was to foster a robust environment for a range of persistent identifiers as an essential component of the European Open Science Cloud (EOSC). FREYA partners were providing the essential building blocks for supporting changes in the way researchers work and the tools they use. This was all coming together in a new vision for how research is conducted, exploiting the full potential of Open Science, and is core to DataCite’s strategic mission.
Make Data Count is a global, community-led initiative focused on the development of open research data assessment metrics. DataCite contributes to the initiative’s work to build open infrastructure and community-based standards for data metrics, as well as its outreach efforts to support adoption, and collaborations with bibliometric studies to contextualize data metrics. Some of the initiative’s milestones include:
The THOR (Technical and Human Infrastructure for Open Research) project was a collaborative effort involving DataCite, among other organizations, aimed at improving the discoverability and accessibility of research data. DataCite’s role in the project focused on developing and implementing persistent identifiers (DOIs) for research datasets, enabling easier citation and linking to data. Through THOR, DataCite contributed to advancing open research by establishing robust infrastructure and standards for data sharing and reuse.
The ORCID and DataCite Interoperability Network (ODIN) project aimed at designing an ‘awareness layer’ for persistent identifiers for researchers and research outputs, thereby reducing technical, cultural and logistical barriers to the accessibility, attribution, and trust of data. Identifier awareness will make it possible to stabilize: References to a data object; Tracking use and re-use; Links between a data object, subsets, articles, rights statements, and every person involved in its life cycle.