| NSF Org: |
OAC Office of Advanced Cyberinfrastructure (OAC) |
| Recipient: |
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| Initial Amendment Date: | March 3, 2016 |
| Latest Amendment Date: | January 23, 2022 |
| Award Number: | 1541450 |
| Award Instrument: | Cooperative Agreement |
| Program Manager: |
Alejandro Suarez
alsuarez@nsf.gov (703)292-7092 OAC Office of Advanced Cyberinfrastructure (OAC) CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | March 1, 2016 |
| End Date: | February 28, 2023 (Estimated) |
| Total Intended Award Amount: | $4,986,951.00 |
| Total Awarded Amount to Date: | $5,887,240.00 |
| Funds Obligated to Date: |
FY 2019 = $293,559.00 FY 2020 = $304,774.00 FY 2021 = $301,956.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
506 S WRIGHT ST URBANA IL US 61801-3620 (217)333-2187 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
506 S. Wright Street Urbana IL US 61801-3620 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Data Cyberinfrastructure |
| Primary Program Source: |
01001920DB NSF RESEARCH & RELATED ACTIVIT 01002021DB NSF RESEARCH & RELATED ACTIVIT 01002122DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Scholarly publications today are still mostly disconnected from the underlying data and code used to produce the published results and findings, despite an increasing recognition of the need to share all aspects of the research process. As data become more open and transportable, a second layer of research output has emerged, linking research publications to the associated data, possibly along with its provenance. This trend is rapidly followed by a new third layer: communicating the process of inquiry itself by sharing a complete computational narrative that links method descriptions with executable code and data, thereby introducing a new era of reproducible science and accelerated knowledge discovery. In the Whole Tale (WT) project, all of these components are linked and accessible from scholarly publications. The third layer is broad, encompassing numerous research communities through science pathways (e.g., in astronomy, life and earth sciences, materials science, social science), and deep, using interconnected cyberinfrastructure pathways and shared technologies.
The goal of this project is to strengthen the second layer of research output, and to build a robust third layer that integrates all parts of the story, conveying the holistic experience of reproducible scientific inquiry by (1) exposing existing cyberinfrastructure through popular frontends, e.g., digital notebooks (IPython, Jupyter), traditional scripting environments, and workflow systems; (2) developing the necessary 'software glue' for seamless access to different backend capabilities, including from DataNet federations and Data Infrastructure Building Blocks (DIBBs) projects; and (3) enhancing the complete data-to-publication lifecycle by empowering scientists to create computational narratives in their usual programming environments, enhanced with new capabilities from the underlying cyberinfrastructure (e.g., identity management, advanced data access and provenance APIs, and Digital Object Identifier-based data publications). The technologies and interfaces will be developed and stress-tested using a diverse set of data types, technical frameworks, and early adopters across a range of science domains.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
Note:
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Communities across the sciences are increasingly concerned about the transparency and reproducibility of results obtained by computational means. Through new policies and community norms, researchers are now regularly required to provide the underlying data and software used to produce published results and findings. The Whole Tale project is addressing this challenge through the creation of an open-source cloud-based platform designed to simplify the creation, publication, and verification of transparent and reproducible computational research.
Used by thousands of researchers, students, and educators, Whole Tale implements best practices in support of computational transparency and reproducibility. Through integration with popular research repositories (e.g., DataONE, Dataverse, Zenodo, and OpenICSPR), support for widely-used analysis environments (e.g., JupyterLab, RStudio, MATLAB, and Stata), and containerization techniques, researchers can easily connect the data, code, and computational environment used to obtain findings to scientific publications. Standards-based packages, called tales, are published to supported archival repositories enabling exploration, verification, and re-use. The recorded run feature enables capture of provenance information, further increasing trust in findings by demonstrating that the provided data and software were actually used to obtain reported results.
The Whole Tale team currently operates an open-access service using the NSF Jetstream2 cloud (https://dashboard.wholetale.org). The system can also be deployed on anything from a single server to a scalable multi-node cluster to meet the needs of specific research teams or communities. Documentation, training, and outreach materials are publicly available.
The Whole Tale project is developing infrastructure designed to address key challenges related to trust in the integrity of published research. Although the initial grant is completed, development of the platform is ongoing. As an open-source project, community contributions are always welcome.
Last Modified: 06/29/2023
Modified by: Bertram Ludaescher
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