Abstract

<strong>Objectives:</strong> (1) to identify common errors in data organization and metadata completeness that would preclude a “reader” from being able to interpret and re-use the data for a new purpose; and (2) to develop a set of best practices derived from these common errors that would guide researchers in creating more usable data products that could be readily shared, interpreted, and used. <strong>Methods:</strong> We used directed qualitative content analysis to assess and categorize data and metadata errors identified by peer reviewers of data papers published in the Ecological Society of America’s (ESA) Ecological Archives. Descriptive statistics provided the relative frequency of the errors identified during the peer review process. <strong>Results:</strong> There were seven overarching error categories: Collection & Organization, Assure, Description, Preserve, Discover, Integrate, and Analyze/Visualize. These categories represent errors researchers regularly make at each stage of the Data Life Cycle. Collection & Organization and Description errors were some of the most common errors, both of which occurred in over 90% of the papers. <strong> Conclusions:</strong> Publishing data for sharing and reuse is error prone, and each stage of the Data Life Cycle presents opportunities for mistakes. The most common errors occurred when the researcher did not provide adequate metadata to enable others to interpret and potentially re-use the data. Fortunately, there are ways to minimize these mistakes through carefully recording all details about study context, data collection, QA/ QC, and analytical procedures from the beginning of a research project and then including this descriptive information in the metadata.

Highlights

  • Data are increasingly being recognized as important products of the scientific enterprise (U.S GAO 2007; OSTP 2013) and funding agencies such as the U.S National Institutes of Health and U.S National Science Foundation

  • The Ecological Society of America’s (ESA) data papers represent a unique type of article that the ESA has published since 2005

  • The most common errors identified by reviewers were Collection & Organization and Description errors

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Summary

Introduction

Data are increasingly being recognized as important products of the scientific enterprise (U.S GAO 2007; OSTP 2013) and funding agencies such as the U.S National Institutes of Health and U.S National Science Foundation. Both agencies require that proposals include plans describing how data will be shared and managed (NIH 2003, NSF 2011). In order for the data to be interpreted, shared, and re-used, it must be accompanied by metadata that describe the scientific context. ESA’s Ecology publishes the abstract describing the data paper and Ecological Archives publishes the comprehensive data sets and accompanying metadata that describe the content, context, quality, and structure of the data. Data papers undergo extensive peer review to assess the submission’s overall quality and significance to the ecological sciences as well as additional technical review of the data and metadata to ensure a high standard of usability

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