The Challenge of Different Data File Formats in GMM Applications
There is no arguing the importance of high data integrity when performing landmark-based Geometric Morphometric (GMM) analyses, where accurate data makes a direct impact on human lives. Unfortunately, the exchange of data is rarely seamless. There is little standardization of data file formats in the various GMM applications currently available.
Given the ubiquitous use of computers in every field, you would think that this would be a solved issue by now. Just about everyone working with data from landmark-based GMM studies has had the experience of searching through the ‘Save As..’ or ‘Export’ or ‘Translate’ menu options without finding the format needed for the next step of your process. This is because the various applications written for landmark-based GMM analyses often output data into different file formats.
Complications Created by Lack of File Format Standardization
Interoperability Issues: Incompatible file formats mean that the commonly used tools for GMM and landmark analyses cannot directly export/import data sets into each other, which leads to
Increased Complexity: Managing a diverse range of data formats increases the complexity of the work you do in the field, which adds to the cost and effort required for data management. But worst of all are
Manual Translation Errors: Most file formats used in GMM tools are human readable, so it is possible (if not easy) to translate a file from one format to another manually. The more times a user manually interacts with the data, transcription, translation, or even cut and paste, the more opportunity for errors to occur.
The Value of Automated Data Handling
Countless studies have shown that automated data handling versus human handling greatly reduces error, hence projects like Open Data Kit and the recent proliferation of electronic lab notebook (ELN) products.
In 2008, business professor Dr. Raymond R. Panko of the University of Hawaiʻi at Mānoa published a research paper showing many examples of studies into manual data entry human errors. He wrote that when humans input data into simple spreadsheets and documents, the probability of a human error was between 18% and 40%.
In 2011, Dr. Kimberly Burchard and Dr. Larry Pace published their research describing how human data entry can result in errors that ruin statistical results and conclusions. She concluded that researchers should design and use human computer interactions that minimize data entry errors.
In a perfect world, standardization would be the key to addressing these challenges. By adopting widely accepted data file formats, researchers could achieve greater consistency in their data sets and better interoperability in their software. Until that happens, an interim solution is not just necessary but critical to scientific data integrity.
Revware’s LFFC Can Help
With the importance of data integrity for landmark-based GMM studies in mind, Revware has built a simple automated utility to load data files for translation into other file formats specific to landmark-based GMM studies. We call this free tool the Landmark File Format Converter (LFFC). This utility allows import and export of multiple file standards, removing transcription errors and helping preserve data integrity.
Current supported formats in LFFC are ‘monolithic’ CSV, MorphoJ (r/c), MDT (Morpheus), and Morphologika. Future Revware GMM products will allow the import and export of other file formats as well.
For questions about LFFC or suggestions for other useful file formats, please reach out to us at contactus@revware.net.
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