Data interoperability refers to the capacity of different devices and systems to communicate and effectively exchange data with each other. In other words, it is the ability of data to be shared and used across different platforms or systems without any loss of information or functionality. By facilitating interoperability, we ensure that farmers, agronomists, and other stakeholders are not weighed down with the task of enabling communication between different systems. Therefore, it becomes apparent why it is of the highest importance for modern agriculture, where the number of digital solutions used in the field continuously increases.
Agriculture data interoperability implications
The absence of interoperability in agricultural data can result in various issues. The most prominent ones include data fragmentation, where data generated by various sources (e.g., farm machinery, weather sensors, etc.) are stored in different formats or silos, making it difficult to access, integrate and generate valuable insights. Data inconsistency, which leads to incomplete or inaccurate data analysis, directly affecting decision-making. Moreover, the absence of data interoperability can also restrain data sharing and collaboration between stakeholders, dramatically reducing the potential for synergies which may lead to increased farmer profit and the creation of innovative solutions. Finally, it may lead to increased costs as managing different data streams and integrating heterogeneous data becomes more complex and time-consuming, limiting the adoption of digital agriculture solutions.
Reasons for lack of agriculture data interoperability
Across the numerous issues, modern agriculture has to deal with to achieve interoperability, the most significant ones that directly link to the main implication mentioned above are the following. Numerous and Incompatible data standards and formats (every digital solution provider uses a different and, on occasion, proprietary format) make it impossible to gather them under a single platform. In turn, this leads to poor data fusion as each type of data and format requires a different expert to translate it into meaningful information, which can be used by non-experts such as farmers and agronomists. Moreover, agriculture is a domain where data sharing is limited as all involved parties tend to be secretive and overfocus on data privacy, intellectual property rights, and regulatory constraints. Finally, agricultural data is segmented across numerous different systems (siloed), with poor data management complicating access and utilization of those data.
Agriculture data interoperability future
More and more stakeholders in the agriculture industry recognize the need to share and integrate data across different systems and devices. As a result, several efforts have been made in that direction by public entities and researchers alike. Examples are the constantly growing use of open data platforms that allow farmers, researchers, and agribusinesses to share and access data in a standardized format. The development of common and open data standards that enable different systems and devices to communicate and share data seamlessly, reducing data across the supply chain, and the introduction of technological innovations such as the Internet of Things (IoT) and blockchain enable real-time monitoring, tracking, and data sharing across the entire supply chain.