databases > bsg-d001769
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in development Zoltar

General Information
Zoltar is a research data repository that stores forecasts made by external models in standard formats and provides tools for validation, visualization, and scoring. Zoltar can host real-time or retrospective forecasting challenges, competitions, or research projects, with users specifying the forecast targets.


Countries that developed this resource United States

Created in 2020

Taxonomic range

User-defined Tags

Awaiting DOI assignment.

This record is maintained by cornell

Record added: Dec. 16, 2020, 2 p.m.
Record updated: Dec. 16, 2020, 2 p.m. by The FAIRsharing Team.



Additional Information

Access / Retrieve Data

Conditions of Use

Data Access

REST Web Services


The Zoltar forecast archive: a tool to facilitate standardization and storage of interdisciplinary prediction research (Preprint)

Nicholas G Reich, Matthew Cornell, Evan L Ray, Katie House, Khoa Le
arXiv 2020

Link to Publication

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Reporting Guidelines

No guidelines defined

Terminology Artifacts

No semantic standards defined

Models and Formats

No syntax standards defined

Identifier Schemas

No identifier schema standards defined


No metrics standards defined

Related Databases

No related databases defined

Implementing Policies

This record is not implemented by any policy.


Record Maintainer

  • This record is maintained by cornell



Grant Number(s)

  • R35GM119582 (National Institute of General Medical Sciences (NIGMS), Bethesda, MD, USA)