# Challenges and Opportunities of Large Transnational Datasets: A Case Study on European Administrative Crop Data

arXiv: https://arxiv.org/abs/2210.07178 · HTML: https://mlsanity.com/paper/2210.07178/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Sep 2022.

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

- [C3DG: Conditional Domain Generalization for Hyperspectral Imagery Classification with Convergence and Constrained-risk Theories](https://mlsanity.com/paper/2407.04100/) (2024)

## Abstract (arXiv)

Expansive, informative datasets are vital in providing foundations and possibilities for scientific research and development across many fields of study. Assembly of grand datasets, however, frequently poses difficulty for the author and stakeholders alike, with a variety of considerations required throughout the collaboration efforts and development lifecycle. In this work, we discuss and analyse the challenges and opportunities we faced throughout the creation of a transnational, European agricultural dataset containing reference labels of cultivated crops. Together, this forms a succinct framework of important elements one should consider when forging a dataset of their own.