News

Summer Internships 2019

The Whole Tale is inviting Internship applications for 2019!

The act of sharing scientific knowledge is rapidly evolving away from traditional articles and presentations to the delivery of executable objects that integrate the data and computational details (e.g., scripts and workflows) upon which the findings rely. This envisioned coupling of data and process is essential to advancing science. The WholeTale project aims to connect computational, data-intensive research efforts with the larger research process - transforming the knowledge discovery and dissemination process into one where data products are united with research articles to create "living publications" or tales.

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Workshop on Education and Training for Reproducible Research - An Infrastructure Perspective

Are you interested in training for research reproducibility? We want to hear your perspective on the knowledge requirements and gaps in education.

Please join us at the Workshop on Education and Training for Reproducible Research at the National Center for Supercomputing Applications (NCSA). This workshop will explore the required skills, with emphasis on both immediate and long-term needs, training for advancing reproducibility, and opportunities to leverage current infrastructure for reproducibility training and teaching. Organized by the NSF Whole Tale Project (https://wholetale.org/)

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Whole Tale - RDA/US Fellowship Call for Applications

The Whole Tale project, in cooperation with the US region of the Research Data Alliance (RDA/US) and its early career fellowship program RDA/US Data Share, invites applications for the joint WT-RDA/US Early Career fellowship program. Through self-directed projects or discussions fellows will engage with both the WT and RDA communities to explore issues related to reproducibility, provenance, sharing, and citation in computational research that combines software and data.

The program offers two kinds of awards: * Project Fellows (Project + Travel): Up to 3 applicants will receive a $5,000 stipend over a 6 month period and travel support to attend the RDA Thirteenth Plenary and 2019 WT Working Group workshop. * Travel Fellows (Travel only): Up to 7 applicants will receive travel support to attend the RDA Thirteenth Plenary

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Whole Tale Workshop on Tools and Approaches for Publishing Reproducible Research

Dates: September 13-14, 2018

Location: Big Ten Center, Chicago

Do you conduct computational research that you want to make more accessible? Do you want to learn about exploring and building upon research and data produced elsewhere?

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Summer Internships 2018

The Whole Tale is inviting Internship applications for 2018!

The act of sharing scientific knowledge is rapidly evolving away from traditional articles and presentations to the delivery of executable objects that integrate the data and computational details (e.g., scripts and workflows) upon which the findings rely. This envisioned coupling of data and process is essential to advancing science. The WholeTale project aims to connect computational, data-intensive research efforts with the larger research process - transforming the knowledge discovery and dissemination process into one where data products are united with research articles to create "living publications" or tales.

Read More →

Architecture Paper Published

Our architecture paper was published in Future Generation Computer Systems.

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Summer Internships 2017

The Whole Tale is inviting Internship applications for 2017!

Scholarly publications are often disconnected from the underlying data and code that was used to produce the findings. There is no shortage of tools and cyberinfrastructure (CI) addressing specific aspects of this challenge, yet scientists find it difficult to utilize these different pieces and building blocks in a seamless way that spans the “whole story”, i.e., from conducting the computational science to the publication of a “living” or executable paper. These new types of publications include not only the science narrative, but also (references to) all the relevant data, code, and provenance information needed to reproduce and experience the computational and research processes described by the paper.

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