Replication Data for: Classification of behaviors of free-ranging cattle using accelerometry signatures collected by virtual fence collars

Version 1.1

Versluijs, Erik, 2023, "Replication Data for: Classification of behaviors of free-ranging cattle using accelerometry signatures collected by virtual fence collars", https://doi.org/10.18710/ND4CLL, DataverseNO, V1

Learn about Data Citation Standards.

Contact Owner

Dataset Metrics

172 Downloads

Description	This dataset includes the scripts to reproduce the models presented in the paper. The cleaned data used for the analyses is also available. Abstract of the article: Precision farming technology, including GPS collars with biologging, has revolutionized remote livestock monitoring in extensive grazing systems. High resolution accelerometry can be used to infer the behavior of an animal. Previous behavioral classification studies using accelerometer data have focused on a few key behaviors and were mostly conducted in controlled situations. Here, we conducted behavioral observations of 38 beef cows (Hereford, Limousine, Charolais, Simmental/NRF/Hereford mix) free-ranging in rugged, forested areas, and fitted with a commercially available virtual fence collar (Nofence) containing a 10Hz tri-axial accelerometer. We used random forest models to calibrate data from the accelerometers on both commonly documented (e.g., feeding, resting, walking) and rarer (e.g., suckling calf, head butting, allogrooming) behaviors. Our goal was to assess pre-processing decisions including different running mean intervals (smoothing window of 1, 5, or 20 seconds), collar orientation and feature selection (orientation-dependent versus orientation-independent features). We identified the 10 most common behaviors exhibited by the cows. Models based only on orientation-independent features did not perform better than models based on orientation-dependent features, despite variation in how collars were attached (direction and tightness). Using a 20 seconds running mean and orientation-dependent features resulted in the highest model performance (model accuracy: 0.998, precision: 0.991, and recall: 0.989). We also used this model to add 11 rarer behaviors (each < 0.1% of the data; e.g. head butting, throwing head, self-grooming). These rarer behaviors were predicted with less accuracy because they were not observed at all for some individuals, but overall model performance remained high (accuracy, precision, recall >98%). Our study suggests that the accelerometers in the Nofence collars are suitable to identify the most common behaviors of free-ranging cattle. The results of this study could be used in future research for understanding cattle habitat selection in rugged forest ranges, herd dynamics, or responses to stressors such as carnivores, as well as to improve cattle management and welfare. (2023-03-31)
Subject	Agricultural Sciences; Earth and Environmental Sciences
Keyword	Accelerometry, animal behavior, free-ranging cattle, behavioral classification, virtual fence collars
Related Publication	Versluijs E., Niccolai L.J., Spedener M., Zimmermann B., Hessle A., Tofastrud M., Devineau O. & Evans A.L. (2023). Classification of behaviors of free-ranging cattle using accelerometry signatures collected by virtual fence collars. Frontiers in Animal Science, 4. https://doi.org/10.3389/fanim.2023.1083272 doi: 10.3389/fanim.2023.1083272
License/Data Use Agreement	CC0 1.0

Filter by

	1 to 4 of 4 Files	Download
	00_README.txt Plain Text - 8.7 KB Published Mar 31, 2023 42 Downloads MD5: a24140fc5c6b03154092ef5cc8535084 readme file	Preview "00_README.txt" Access File File Access Public Download Options Plain Text Download Metadata Data File Citation EndNote XML RIS BibTeX
	analysis.R R Source Code - 3.9 KB Published Mar 31, 2023 38 Downloads MD5: e505be5c1dbef1cd7948ab920901f806 file to reproduce the model outputs including the pre-processing. The file is adaptable for each model and parameters for each specific model can be set at the start of the Rscript. - Input: Accelerometry data including all matched behaviors within its behavioral category - Output: H2O Random Forest model results	Access File File Access Public Download Options R Source Code Download Metadata Data File Citation EndNote XML RIS BibTeX
	annotated_acc_data.txt Plain Text - 736.2 MB Published Mar 31, 2023 58 Downloads MD5: 3227965fe6e4f41ecd5051e931ca5177 Accelerometry data including all matched behaviors within its behavioral category	Preview "annotated_acc_data.txt" Access File File Access Public Download Options Plain Text Download Metadata Data File Citation EndNote XML RIS BibTeX
	functions.R R Source Code - 10.6 KB Published Mar 31, 2023 34 Downloads MD5: 78c206a537a8f2c783f0c89858dc62c8 source file with functions for pre-processing procedures. Analysis.R sources this file to conduct pre-processing of the data. - Select_behaviors: selecting and merging the behavioral categories into one column with behaviors - Orientation_correction: reverses the collar's axes if the collar was deployed reversed - Feature_calculation: calculation the orientation dependent and orientation independent features across the accelerometry data	Access File File Access Public Download Options R Source Code Download Metadata Data File Citation EndNote XML RIS BibTeX

Citation Metadata

Persistent Identifier	doi:10.18710/ND4CLL
Publication Date	2023-03-31
Title	Replication Data for: Classification of behaviors of free-ranging cattle using accelerometry signatures collected by virtual fence collars
Author	Versluijs, Erik (Inland Norway University of Applied Sciences) - ORCID: 0000-0001-5919-3466
Point of Contact	Use email button above to contact. Versluijs, Erik (Inland Norway University of Applied Sciences)
Description	This dataset includes the scripts to reproduce the models presented in the paper. The cleaned data used for the analyses is also available. Abstract of the article: Precision farming technology, including GPS collars with biologging, has revolutionized remote livestock monitoring in extensive grazing systems. High resolution accelerometry can be used to infer the behavior of an animal. Previous behavioral classification studies using accelerometer data have focused on a few key behaviors and were mostly conducted in controlled situations. Here, we conducted behavioral observations of 38 beef cows (Hereford, Limousine, Charolais, Simmental/NRF/Hereford mix) free-ranging in rugged, forested areas, and fitted with a commercially available virtual fence collar (Nofence) containing a 10Hz tri-axial accelerometer. We used random forest models to calibrate data from the accelerometers on both commonly documented (e.g., feeding, resting, walking) and rarer (e.g., suckling calf, head butting, allogrooming) behaviors. Our goal was to assess pre-processing decisions including different running mean intervals (smoothing window of 1, 5, or 20 seconds), collar orientation and feature selection (orientation-dependent versus orientation-independent features). We identified the 10 most common behaviors exhibited by the cows. Models based only on orientation-independent features did not perform better than models based on orientation-dependent features, despite variation in how collars were attached (direction and tightness). Using a 20 seconds running mean and orientation-dependent features resulted in the highest model performance (model accuracy: 0.998, precision: 0.991, and recall: 0.989). We also used this model to add 11 rarer behaviors (each < 0.1% of the data; e.g. head butting, throwing head, self-grooming). These rarer behaviors were predicted with less accuracy because they were not observed at all for some individuals, but overall model performance remained high (accuracy, precision, recall >98%). Our study suggests that the accelerometers in the Nofence collars are suitable to identify the most common behaviors of free-ranging cattle. The results of this study could be used in future research for understanding cattle habitat selection in rugged forest ranges, herd dynamics, or responses to stressors such as carnivores, as well as to improve cattle management and welfare. (2023-03-31)
Subject	Agricultural Sciences; Earth and Environmental Sciences
Keyword	Accelerometry animal behavior free-ranging cattle behavioral classification virtual fence collars
Related Publication	Versluijs E., Niccolai L.J., Spedener M., Zimmermann B., Hessle A., Tofastrud M., Devineau O. & Evans A.L. (2023). Classification of behaviors of free-ranging cattle using accelerometry signatures collected by virtual fence collars. Frontiers in Animal Science, 4. https://doi.org/10.3389/fanim.2023.1083272 doi: 10.3389/fanim.2023.1083272 https://doi.org/10.3389/fanim.2023.1083272
Language	English
Producer	Inland Norway University of Applied Sciences (INN) https://eng.inn.no/
Contributor	Researcher : Niccolai, Laura J. Researcher : Spedener, Mélanie Researcher : Zimmermann, Barbara Researcher : Hessle, Anna Researcher : Tofastrud, Morten Researcher : Devineau, Olivier Researcher : Evans, Alina L.
Funding Information	The Research Council of Norway: 302674
Distributor	Inland Norway University of Applied Sciences (Inland Norway University of Applied Sciences) https://dataverse.no/dataverse/inn
Depositor	Versluijs, Erik
Deposit Date	2022-10-20
Time Period	Start Date: 2021-06-22 ; End Date: 2021-07-30
Date of Collection	Start Date: 2021-06-22 ; End Date: 2021-09-30
Data Type	Accelerometry data; Rscripts
Software	R, Version: 4.2.1 Behavioral Observation Research Interactive Software, (BORIS), Version: 8.7

Geospatial Metadata

Geographic Coverage	Norway, Innlandet

Dataset Terms

License/Data Use Agreement

Our Community Norms as well as good scientific practices expect that proper credit is given via citation. Please use the data citation shown on the dataset page.

Creative Commons CC0 1.0 Universal Public Domain Dedication. CC0 1.0

Restricted Files + Terms of Access

Dataset Version	Summary	Contributors	Published on
No records found.

Edit File

This file has already been deleted (or replaced) in the current version. It may not be edited.

Restrict Access

Restricting limits access to published files. People who want to use the restricted files can request access by default. If you disable request access, you must add information about access to the Terms of Access field.

Learn about restricting files and dataset access in the User Guide.

Request Access

Enable access request

You must enable request access or add terms of access to restrict file access.

Terms of Access for Restricted Files

Save Changes

Edit Embargo

The selected file or files have already been published. Contact an administrator to change the embargo date or reason of the file or files.

Edit Retention Period

The selected file or files have already been published. Contact an administrator to change the retention period date or reason of the file or files.

Delete Files

The file will be deleted after you click on the Delete button.

Files will not be removed from previously published versions of the dataset.

Select File(s)

Please select one or more files.

Share Dataset

Share this dataset on your favorite social media networks.

Continue

Dataset Citations

Citations for this dataset are retrieved from Crossref via DataCite using Make Data Count standards. For more information about dataset metrics, please refer to the User Guide.

Sorry, no citations were found.

Inaccessible Files Selected

The selected file(s) may not be downloaded because you have not been granted access or the file(s) have a retention period that has expired or the files can only be transferred via Globus.

You may request access to any restricted file(s) by clicking the Request Access button.

Ineligible Files Selected

The selected file(s) may not be transferred because you have not been granted access or the file(s) have a retention period that has expired or the files are not Globus accessible.

You may request access to any restricted file(s) by clicking the Request Access button.

Download Options

The files selected are too large to download as a ZIP.

You can select individual files that are below the 4.7 GB download limit from the files table, or use the Data Access API for programmatic access to the files.

Select File(s)

Please select a file or files to be downloaded.

Inaccessible Files Selected

The selected file(s) may not be downloaded because you have not been granted access or the file(s) have a retention period that has expired.

Click Continue to download the files you have access to download.

Ineligible Files Selected

Some file(s) cannot be transferred. (They are restricted, embargoed, with an expired retention period, or not Globus accessible.)

Click Continue to transfer the elligible files.

Delete Dataset

Are you sure you want to delete this dataset and all of its files? You cannot undelete this dataset.

Delete Draft Version

Are you sure you want to delete this draft version? Files will be reverted to the most recently published version. You cannot undelete this draft.

Unpublished Dataset Private URL

Private URL can only be used with unpublished versions of datasets.

Unpublished Dataset Private URL

Are you sure you want to disable the Private URL? If you have shared the Private URL with others they will no longer be able to use it to access your unpublished dataset.

Delete Files

The file(s) will be deleted after you click on the Delete button.

Files will not be removed from previously published versions of the dataset.

Compute

This dataset contains restricted files you may not compute on because you have not been granted access.

Deaccession Dataset

Are you sure you want to deaccession? This is permanent and the selected version(s) will no longer be viewable by the public.

Deaccession Dataset

Are you sure you want to deaccession this dataset? This is permanent an it will no longer be viewable by the public.

Version Differences Details

Please select two versions to view the differences.

Version Differences Details

Version:
Last Updated:

Select File(s)

Please select a file or files for access request.

Select File(s)

Embargoed files cannot be accessed. Please select an unembargoed file or files for your access request.

Edit Tags

Select existing file tags or create new tags to describe your files. Each file can have more than one tag.

Request Access

You need to Log In to request access.

Dataset Terms

Please confirm and/or complete the information needed below in order to request access to files in this dataset.

This dataset is made available under the following terms. Please confirm and/or complete the information needed below in order to continue.

License/Data Use Agreement

Our Community Norms as well as good scientific practices expect that proper credit is given via citation. Please use the data citation shown on the dataset page.

Creative Commons CC0 1.0 Universal Public Domain Dedication. CC0 1.0

Preview Guestbook

Upon downloading files the guestbook asks for the following information.

Guestbook Name

Collected Data

Account Information

Package File Download

Use the Download URL in a Wget command or a download manager to download this package file. Download via web browser is not recommended. User Guide - Downloading a Dataverse Package via URL

Download URL

https://dataverse.no/api/access/datafile/

Compute Batch

Clear Batch

Dataset	Persistent Identifier	Change Compute Batch

Compute Batch

Submit for Review

You will not be able to make changes to this dataset while it is in review.

Publish Dataset

Are you sure you want to republish this dataset?

Select if this is a minor or major version update.

Minor Release (1.2)

Major Release (2.0)

Publish Dataset

This dataset cannot be published until University of Inland Norway is published by its administrator.

Publish Dataset

This dataset cannot be published until University of Inland Norway and DataverseNO are published.

Return to Author

Return this dataset to contributor for modification.