To the Editor — Animal behavior is increasingly being recorded in systematic imaging studies that generate large datasets. To maximize the usefulness of these data, there is a need for improved resources for analyzing and sharing behavioral data that will encourage reanalysis and methodological developments1. However, for behavioral data, unlike genomic or protein structural data, there are no widely used standards. It is therefore desirable to make data available in a relatively raw form to enable flexibility in data analysis. For computational ethology to approach the level of maturity of other areas of bioinformatics, at least three challenges must be addressed: storing and accessing video files; defining flexible data formats to facilitate data sharing; and developing software to read, write, browse, and analyze the data. We have generated an open resource to begin addressing these challenges for Caenorhabditis elegans behavioral data.

To store video files and the associated features and metadata, we use a community (an open-access repository for data) that provides durable storage and citability, and that supports contributions from other groups. We have also developed a web interface that enables filtering of the video files on the basis of feature histograms that can return, for example, fast and curved worms in addition to more standard searches for particular strains or genotypes (Fig. 1 and The database currently consists of 14,874 single-worm tracking experiments representing 386 genotypes (building on 9,203 experiments and 305 genotypes in a previous publication2) and includes data from several larval stages as well as data from aging experiments consisting of more than 2,700 videos of animals tracked daily from the L4 stage to death (Nature Research Reporting Summary). Full-resolution videos are available in HDF5 containers that include gzip-compressed video frames, time stamps, worm outlines and midlines, feature data, and experimental metadata. HDF5 files are compatible with multiple languages including MATLAB, R, Python, and C. We have also developed an HDF5 video reader that allows video playback with adjustable speed and zoom (an important feature for reviewing high-resolution multiworm tracking data), as well as toggling of worm segmentation over the original video to verify segmentation accuracy during playback.

Fig. 1: Schematic of the searchable database and Tierpsy analysis pipeline.
Fig. 1

a, The OpenWorm Movement Database provides a web interface for searching by genotype, strain, and/or other discrete values, and interactive histograms with sliders to filter results on the basis of feature values. The interface points to data stored on Zenodo. The video and feature data can be further analyzed or combined with data collected by using other worm trackers through the Worm tracker Commons Object Notation (WCON), a human- and machine-readable JSON format. b, Tierpsy (short for tierpsychology, the German word for ethology) segments and tracks worms, extracting the outline and skeleton of each animal then determining the head–tail orientation. These data are saved in WCON. The OpenWorm Analysis Toolbox is then used to extract behavioral features.

Second, we have defined an interchange format named Worm tracker Commons Object Notation (WCON), to facilitate data sharing and software reuse among groups working on worm behavior. WCON uses the widely supported JSON format to store tracking data as text that is readable by both humans and machines. It is compatible with single and multiworm3 tracking data at any resolution, from a single point representing worm position over time4 to many points representing the high-resolution skeleton of a moving worm2. It also supports custom feature additions so that individual laboratories can store their own specific datasets alongside the existing set of basic worm data. WCON readers are available for Python, MATLAB, Scala, and C. Detailed documentation for the file formats and software is available on the project page (

Finally, we have complemented the database and file formats with open-source software written in Python for single and multiworm tracking, feature extraction, review, and analysis (Supplementary Discussion; code and documentation in Supplementary Software or at, where compiled versions are also available).

The suite of tools reported here makes quantitative behavioral analysis and reanalysis accessible for both experimentalists and computational scientists. It may also serve as a template for similar efforts in other model-organism communities.

Reporting Summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Code availability

Tierpsy Tracker is available as Supplementary Software and at Updated versions will be made available at

Data availability

Videos, skeleton (WCON) files, and feature files are available under a Creative Commons attribution (CC BY) license through the database page and Zenodo community page


  1. 1.

    Gomez-Marin, A., Paton, J. J., Kampff, A. R., Costa, R. M. & Mainen, Z. F. Nat. Neurosci. 17, 1455–1462 (2014).

  2. 2.

    Yemini, E., Jucikas, T., Grundy, L. J., Brown, A. E. X. & Schafer, W. R. Nat. Methods 10, 877–879 (2013).

  3. 3.

    Swierczek, N. A., Giles, A. C., Rankin, C. H. & Kerr, R. A. Nat. Methods 8, 592–598 (2011).

  4. 4.

    Ramot, D., Johnson, B. E., Berry, T. L. Jr., Carnell, L. & Goodman, M. B. PLoS One 3, e2208 (2008).

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This work was supported by the MRC through grant MC-A658-5TY30 to A.E.X.B. Q.C. is supported by an ERC Starting Grant (NeuroAge 242666), a Research Councils UK Fellowship, and the University of London Central Research Fund. Some strains were provided by the CGC, which is funded by the NIH Office of Research Infrastructure Programs (P40 OD010440).

Author information


  1. MRC London Institute of Medical Sciences, London, UK

    • Avelino Javer
    • , Kezhi Li
    •  & André E. X. Brown
  2. Institute of Clinical Sciences, Imperial College London, London, UK

    • Avelino Javer
    • , Kezhi Li
    •  & André E. X. Brown
  3. OpenWorm Foundation, San Diego, CA, USA

    • Michael Currie
    • , Chee Wai Lee
    •  & Jim Hokanson
  4. Department of Biomedical Engineering, Duke University, Durham, NC, USA

    • Jim Hokanson
  5. European Research Institute for the Biology of Ageing, University of Groningen, Groningen, the Netherlands

    • Céline N. Martineau
    •  & Ellen A. A. Nollen
  6. Department of Biological Sciences, Columbia University, New York, NY, USA

    • Eviatar Yemini
  7. MRC Laboratory of Molecular Biology, Cambridge, UK

    • Laura J. Grundy
    •  & William R. Schafer
  8. Department of Biology, City College of the City University of New York, New York, NY, USA

    • Chris Li
  9. Centre for Developmental Neurobiology, King’s College London, London, UK

    • QueeLim Ch’ng
  10. Calico Life Sciences LLC, South San Francisco, CA, USA

    • Rex Kerr


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A.J. wrote Tierpsy Tracker and analyzed data; M.C. wrote WCON viewer, the database, and OpenWorm Analysis Toolbox; C.W.L. wrote the database, web interface, and WCON viewer; J.H. wrote the MATLAB WCON viewer and OpenWorm Analysis Toolbox; K.L. wrote stage-alignment code; C.N.M. collected data; E.Y. wrote the skeletonization algorithm and stage-alignment code; L.J.G. collected data; C.L. contributed strains and planned experiments; Q.C. contributed strains and planned experiments; W.R.S. planned the study; E.A.A.N. contributed strains and planned experiments; R.K. designed WCON and wrote several readers; A.E.X.B. planned the study and wrote the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to André E. X. Brown.

Supplementary information

  1. Supplementary Text and Figures

    Supplementary Discussion

  2. Reporting Summary

  3. Supplementary Software

    Source code and documentation for Tierpsy Tracker software

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