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  * Research-grade US iNaturalist observations geo-binned/time-binned through 1 March 2025.
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  ### Dataset Summary
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- * **Motivation:** To create a spatiotemporally binned co-occurrence matrix of biological taxa based on GBIF observation data, suitable for machine learning tasks like predicting species distributions or analyzing community patterns.
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  * **Source:** GBIF.org (Global Biodiversity Information Facility) occurrence data, specifically from the dataset with download DOI: https://doi.org/10.15468/dl.wn7arn
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  * **Processing:** The raw observation data was processed through several steps:
 
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  * Research-grade US iNaturalist observations geo-binned/time-binned through 1 March 2025.
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  ### Dataset Summary
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+ * **Motivation:** To create a spatiotemporally binned co-occurrence matrix of biological taxa based on iNaturalist observation data (accessed through GBIF) suitable for machine learning tasks like predicting species distributions or analyzing community patterns.
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  * **Source:** GBIF.org (Global Biodiversity Information Facility) occurrence data, specifically from the dataset with download DOI: https://doi.org/10.15468/dl.wn7arn
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  * **Processing:** The raw observation data was processed through several steps: