3.2 Identify output and input data assets

However, when Rashima approached Chris (third-party publisher), she discovered that some of the most detailed government data, particularly on farmer income levels and private sector agricultural investments, was restricted due to data privacy regulations. Chris explained that these indicators were tied to confidential economic strategies, and special permissions were needed for access. Rashima realized their assumptions had overlooked these licensing constraints.

To adapt, Rashima updated the data inventory workbook to include notes on restricted datasets and highlighted those that required special access. She also decided to explore alternative data sources, such as summaries from agricultural reports or aggregated regional-level data to fill these gaps. This process revealed to Rashima the importance of conducting thorough data audits and checking licensing conditions for all external datasets.

Next, Rashima reached out to Chima, the smallholder farmer, who had already contributed initial raw data about crop conditions and input usage from his community. She used Chima’s feedback to better understand the gaps in the existing data. Chima also identified other farmers who could contribute localized data, ensuring the platform’s relevance.

With this information, Rashima organized a meeting with two of Dataland’s foremost experts on precision agriculture (Noora and Marie), who were invited to review and refine the inventory. Noora provided insights on sensor data, highlighting the importance of setting standards for incoming soil and climate data, while Marie discussed how best to display these insights on the platform. Noora flagged that detailed sensor data from private farms could reveal sensitive information about farmers’ land conditions or cultivation methods. Rashima took note of this in the inventory, marking it as ‘Sensitive Data’ to ensure secure storage and limited access within the digital platform.

Rashima used the feedback to populate the final inventory, linking input and output assets and clearly mapping dependencies, accessibility, and licensing requirements. By the end of this iterative process, AgriConnect had a robust inventory that reflected contributions and dependencies from each partner and participant. Rashima distributed the final inventory document to all stakeholders, inviting ongoing feedback to keep it a living document.

During a follow-up meeting with Imamu (third-party publisher), Kaira discovered that accessing key government data on agricultural trends was not as straightforward as they had assumed. Imamu explained that certain economic and demographic indicators were restricted due to privacy laws and required special permissions or anonymization protocols to be used in policy recommendations. This revelation meant that Kaira and her team needed to revisit their data inventory and identify alternative sources or approaches for obtaining sensitive information.

Next, Kaira reached out to Haben (smallholder farmer) to discuss the real-life challenges faced by smallholders and the data that could support solutions. During this conversation, Haben provided detailed information on loan repayment rates and crop yield fluctuations, and gave feedback on existing government support schemes. Kaira reassured Haben that any sensitive data collected, such as financial and land ownership records, would be anonymized and only shared with explicit permission. The team created a separate section in their data inventory workbook to flag datasets requiring ethical considerations or specific licensing permissions.

Later, Kaira met with Saanvi (technical consultant) to review sensor data capturing climate variations and soil conditions. Saanvi explained the significance of soil moisture and temperature measurements, which were essential for designing climate resilience strategies. Together, they outlined the required input data assets and standardized the data collection process for consistency and quality.

Kaira asked Saanvi about the potential sensitivity of geospatial climate data. Saanvi flagged this as an important issue, noting that precise location data could inadvertently reveal private information about specific farm plots or practices. The team agreed to anonymize location-specific details and documented this decision in their inventory under a ‘Sensitive data’ category, ensuring compliance with AgroThrive’s data governance policy.

Aziz (project partner) and Anna (project partner) took the lead in refining the inventory by contributing training data and financial outreach insights from their respective programs. They discussed the accessibility and licensing of their data, ensuring it aligned with AgroThrive’s objectives. Lata (gender consultant) also provided her input, adding gender-specific metrics that needed to be tracked to support inclusive policy formulation.

Once all input and output assets were mapped, Kaira arranged a final meeting with Adnan (government liaison) to review the preliminary inventory. Adnan provided valuable feedback on compliance with government policies and identified gaps in some of the datasets.

To wrap up the process, Kaira hosted a virtual ‘data validation’ session with Imamu (third-party publisher). Imamu gave feedback on accessibility and licensing terms, helping Kaira make necessary adjustments to ensure all external data could be used according to the project’s data governance policies.

To get a comprehensive view, Farah organized field visits with Davu, the smallholder farmer. During these visits, Davu shared details on current crop yields, soil erosion issues, and coping mechanisms against climate variability. This raw, community-level data was crucial for the project’s output. During the visit, Farah also learned of the sensitivity around data on soil health and cropping techniques. Davu expressed concerns that revealing specific practices could give competitors an advantage or expose their village to external scrutiny. Farah assured Davu that such information would be anonymized, and she made sure this was clearly documented in the inventory’s ‘Sensitive data’ section, which included protocols for handling confidential or location-specific datasets.

Farah then met with Joe, the third-party publisher at the government agency, to access historical data on agricultural indicators. Joe’s open data repository provided additional economic, social, and climate trend insights that the team needed. Back at the research center, Farah worked with the team to document all input and output assets in a detailed inventory.

Charlotte, the climate scientist, and Cali, the geneticist, helped cross-reference this inventory against their own datasets on climate impacts and genetic variations. Together, they identified gaps in existing data and proposed solutions to fill them. Farah set up a separate meeting with Jaya, the gender specialist, who provided essential context on how to track the intersectional benefits of the new barley variety for women and children.

By the end of this iterative process, the team had built a comprehensive data inventory. Farah convened a final meeting where each partner reviewed their contributions, ensuring everything was well-documented and compliant with open-access requirements. This inventory became the backbone of NGBT’s research, providing a clear path forward to responsibly publish and share their findings at the project’s conclusion.