Autonomous tracking of honeybee behaviors over long-term periods with cooperating robots

Open data API in a single place

Provided by AAAS

Get early access to Autonomous tracking of honeybee behaviors over long-term periods with cooperating robots API!

Let us know and we will figure it out for you.

Dataset information

Country of origin
Updated
2024.10.17 00:00
Created
2024.01.01
Available languages
English
Keywords
Behavioral Ecology, Cognitive Robotics, Metrics, Long-term Observations, Honeybee Ethology, Tracking
Quality scoring

Dataset description

Dataset and code description This repository contains the codes and data for theScience Robotics paper Autonomous tracking of honeybee behaviors over long-term periods with cooperating robots. The codes are in rr_scirob_analyses and the datasets are in rr_scirob_data.  If you want to rerun the data processing as presented in the paper, you need both rr_scirob_analyses and rr_scirob_data. You can copy the contents of rr_scirob_data into rr_scirob_analyses, as they have the same folder structure. Alternatively, you can run the download scripts to obtain the partial datasets relevant for certain subfigures. The file rr_scirob_data_readmes contains more detailed README files (rosbag info). You can copy its contents to rr_scirob_analyses after copying the contents of the rr_scirob_data. The individual datasets are organised into seven folders. Three Figures with Key Behavioural Metrics  Three of the folders correspond to the Key Behavioural Measures, which are presented in three figures in the paper. These are: Figure-2-KBM-1-Queen                     Queen - related Key Behavioural Metrics Figure-3-KBM-2-Workers                  Worker Bee - related Key Behavioural Metrics Figure-4-KBM-3-Comb                      Comb and Brood -related Key Behavioural Metrics  Each of these Figure-X folders contains the relevant figure from the paper and four subfolders corresponding to the panels of that figure.  These are macro, micro, mezo, social, related to the four panels of that figure.Each of these subfolders contains a README file, describing how to process the data and providing further details. Furthermore, there are three additional folders located in each of the 'panel' folder: data: this is used to store the data necessary to generate the graphs. You can either populate it with the data from Zenodo, i.e.,  https://zenodo.org/records/13801588 Alternatively, you can use the `download.sh` script wich will download and extract the necessary data from the RoboRoyale project cloud. tmp: This folder is used to store intermediate results of the processing scripts output: This folder is used to store all the generated outputs of the individual scripts. These should be identical with the panels of the figure in the paper. These figures are also provided in the relevant folders. Running the scripts contained in the micro, mezo, macro and social folders generates images and graphs in the output subfolders. These should be identical to the ones in the panels of Figures 2-4 in the paper. One Resting Analysis Figure One folder corresponds to the queen resting analysis figure Figure-5-Resting       : Queen resting time analysis This folder has three subfolders named data, tmp and output similar to the previous folders. Again, running the scripts will generate the figures and/or run the statistical tests as in the previous case. Three Performance Assessments: Queen Tracking, Workerbee Localisation and Oviposition Detection Three other folders are related to performance analysis of the core methods required to calculate the KBMs. KBM-1-performance evaluation:       Provides datasets and scripts to assess the performance of the queen marker detector KBM-2-performance evaluation:       Provides datasets and scripts to assess the performance of the worker bee detector KBM-3-performance evaluation:       Provides datasets and scripts to assess the performance of the oviposition detector  Each of these folders contains a README file explaining what to run in order to evaluate the performance of the method and to replicate the paper's results. Additional materials and data The core data used here is the month-long queen tracking information, consisting of 28 million entries in a file 2023-month-queenpos-short.txt. A description of the file structure is provided in the README of the relevant KBM folder. Additional data are available in the dataset section of https://roboroyale.eu. Rosbags The work is based on the Robot Operating System (ROS) and thus, the raw data come in the form of rosbags. We provide a few of the rosbags to allow checking examples of video and other raw data as reported by the system: 2023-10-25-08-42-20-Queen-Feeding.bag       -   queen feeding (KBM-1 Social) KPI1_2_mezo-queen_walk_sample.bag           -   queen walk as drawn in (KBM-1 Mezo) 2023-10-10-00-04-10-trophylaxis.bag              -    worker bee trophylaxis  (KBM-2 Social) 2023-09-19-09-00-20-egg-removal.bag           -   worker bee removing egg (KBM-2 Social) Licence  This data and code are under the Creative Commons Attribution-ShareAlike 4.0 International license. If you use these data in your work, please cite the relevant paper, i.e.,  Ulrich, Stefanec, Rekabi-bana et al.: Autonomous tracking of honeybee behaviors over long-term periods with cooperating robots. Science Robotics, 2024.  
European data infrastructure with broad catalog discovery, free evaluation access and production-grade API options.
190K+
indexed dataset pages
32
countries and EU institutions
2019
API-first since
Free API quota
for evaluation and prototypes
SLA
history and push on production APIs
FAQ

Questions before production use

Practical answers on evaluation, licensing, freshness, versioning and support.

api.store is built and operated by Apitalks s.r.o. Company details and a direct contact path are linked in the footer for vendor checks and procurement review.
Yes. Selected APIs include a free API quota, so your team can validate coverage, freshness, response shape and workflow fit before asking for a production plan.
Often yes, but usage rights depend on the source license and dataset. We surface source, license and update metadata where available, and can help review terms before a production integration.
Maintained APIs include update metadata where available. For production integrations, we can add history, monitoring and push updates so changes are easier to detect and act on.
Production APIs can add SLA, stable identifiers, versioning support, history, push updates and direct support around the data your product or AI workflow depends on.

Didn't find the API you need?

Let us know and we will figure it out for you.

European data discovery with free evaluation access and production-grade API options.

Copyright © 2026. Made by Apitalks