What is a significant limitation of open source data?

A significant limitation of open source data relates to attribution. Open source data often comes with specific licensing requirements that dictate how the data can be used, shared, and modified. Many open source datasets require users to give credit to the original creators or sources, which can complicate the integration of this data into projects, particularly those that involve commercial use. If users fail to properly attribute the sources, it can lead to legal issues or violate the terms of the data's use. This aspect of attribution is crucial for maintaining transparency and ensuring that data creators receive recognition for their work.

In contrast, issues like availability of datasets might arise but do not universally apply to all open source data; in fact, many communities actively share abundant datasets. Quality of imagery can vary significantly, regardless of whether data is open source or proprietary, and while some open source datasets may provide high-quality imagery, this is not a defining limitation of open source data overall. Compatibility with proprietary software can present challenges, but many open source formats are designed to work well with various systems, so this limitation isn't inherently tied to the nature of the data being open source. Thus, the challenge of attribution stands out as a notable concern in the context of open source datasets.