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Abstract Quantifying movement and demographic events of free‐ranging animals is fundamental to studying their ecology, evolution and conservation. Technological advances have led to an explosion in sensor‐based methods for remotely observing these phenomena. This transition to big data creates new challenges for data management, analysis and collaboration.We present the Movebank ecosystem of tools used by thousands of researchers to collect, manage, share, visualize, analyse and archive their animal tracking and other animal‐borne sensor data. Users add sensor data through file uploads or live data streams and further organize and complete quality control within the Movebank system. All data are harmonized to a data model and vocabulary. The public can discover, view and download data for which they have been given access to through the website, the Animal Tracker mobile app or by API. Advanced analysis tools are available through the EnvDATA System, the MoveApps platform and a variety of user‐developed applications. Data owners can share studies with select users or the public, with options for embargos, licenses and formal archiving in a data repository.Movebank is used by over 3,100 data owners globally, who manage over 6 billion animal location and sensor measurements across more than 6,500 studies, with thousands of active tags sending over 3 million new data records daily. These data underlie >700 published papers and reports. We present a case study demonstrating the use of Movebank to assess life‐history events and demography, and engage with citizen scientists to identify mortalities and causes of death for a migratory bird.A growing number of researchers, government agencies and conservation organizations use Movebank to manage research and conservation projects and to meet legislative requirements. The combination of historic and new data with collaboration tools enables broad comparative analyses and data acquisition and mapping efforts. Movebank offers an integrated system for real‐time monitoring of animals at a global scale and represents a digital museum of animal movement and behaviour. Resources and coordination across countries and organizations are needed to ensure that these data, including those that cannot be made public, remain accessible to future generations.
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This content will become publicly available on August 1, 2026
Citizen scientists for MoveApps: Innovations and insights from volunteer coders in wildlife conservation
Abstract Amidst numerous global crises, decision‐makers have recognized the critical need for fact‐based advice, driving unprecedented data collection. However, a significant gap persists between data availability and knowledge generation, primarily due to time and resource constraints. To bridge this gap, we propose involving a novel group of citizen scientists: volunteer code developers.Utilizing the modular, open‐source analysis platform MoveApps, we were able to engage 12 volunteer coders in a challenge to create tools for movement ecology, aimed at animal conservation. These volunteers developed functioning applications capable of analysing animal tracking data to identify stationary behaviour, estimate ranges and movement corridors and assess human–wildlife conflicts using data sets from human infrastructure, such as OpenStreetMap.Engaging citizen scientists in developing code has surfaced three primary challenges: (i) Community Building—attracting the right participants; (ii) Community Involvement—maintaining quality standards and directing tasks effectively; and (iii) Community Retention—ensuring long‐term engagement. We explore strategies to overcome these challenges and share lessons learnt from our coding challenge experience. Our approaches include engaging the community through their own preferred channels, providing an accessible open‐source tool, defining specific use cases in detail, ensuring quality through feedback, fostering self‐organized community exchanges and prominently illustrating the impact of contributions.We also advocate for other disciplines to consider leveraging volunteer involvement, alongside artificial intelligence, for data analysis and generating state‐of‐the‐art, fact‐based insight to address critical issues such as the global decline in biodiversity.
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- Award ID(s):
- 2127271
- PAR ID:
- 10643698
- Publisher / Repository:
- British Ecological Society
- Date Published:
- Journal Name:
- Methods in Ecology and Evolution
- Volume:
- 16
- Issue:
- 8
- ISSN:
- 2041-210X
- Page Range / eLocation ID:
- 1550 to 1563
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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