# BioCube: A Multimodal Dataset for Biodiversity Research

arXiv: https://arxiv.org/abs/2505.11568 · HTML: https://mlsanity.com/paper/2505.11568/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 15 references that are in the map.
- First posted on arXiv 16 May 2025.

## Builds on (most cited first, 4 of 4)

- [Benchmarking Representation Learning for Natural World Image Collections](https://mlsanity.com/paper/2103.16483/) (2021)
- [BIOSCAN-5M: A Multimodal Dataset for Insect Biodiversity](https://mlsanity.com/paper/2406.12723/) (2024)
- [GeoPlant: Spatial Plant Species Prediction Dataset](https://mlsanity.com/paper/2408.13928/) (2024)
- [The GeoLifeCLEF 2020 Dataset](https://mlsanity.com/paper/2004.04192/) (2020)

## Built on by (most cited first, 1 of 1)

- [BioAnalyst: A Foundation Model for Biodiversity](https://mlsanity.com/paper/2507.09080/) (2025)

## Abstract (arXiv)

Biodiversity research requires complete and detailed information to study ecosystem dynamics at different scales. Employing data-driven methods like Machine Learning is getting traction in ecology and more specific biodiversity, offering alternative modelling pathways. For these methods to deliver accurate results there is the need for large, curated and multimodal datasets that offer granular spatial and temporal resolutions. In this work, we introduce BioCube, a multimodal, fine-grained global dataset for ecology and biodiversity research. BioCube incorporates species observations through images, audio recordings and descriptions, environmental DNA, vegetation indices, agricultural, forest, land indicators, and high-resolution climate variables. All observations are geospatially aligned under the WGS84 geodetic system, spanning from 2000 to 2020. The dataset is available at https://huggingface.co/datasets/ BioDT/BioCube, the acquisition and processing code base at https://github.com/BioDT/bfm-data.