• Data fragmentation across disparate systems
  ABO metadata was scattered across more than seven independent systems (including AMDAR, TAMDAR, and IAGOS), creating data silos. This lack of a centralized repository hindered efficient data sharing and analysis, resulting in an estimated 3.5 hours of manual processing per dataset.

• Compliance gaps with international standards
  Manual processes and a lack of standardized metadata management made it difficult to enforce compliance with WMO-No. 1200 and WIGOS (WMO Integrated Global Observing System) standards. This led to frequent compliance queries (over 240 monthly), consuming significant resources and potentially affecting data quality.

• Scalability limitations
  The existing infrastructure struggled to handle the growing volume of ABO data, particularly with over 10,000 aircraft records. This limited scalability impeded the integration with crucial tools like OSCAR/Surface (WMO’s Observing Systems Capability Analysis and Review tool), hindering the WMO’s ability to effectively monitor and analyze global meteorological observations.

• Inefficient data retrieval
  The legacy systems resulted in slow data retrieval, making it difficult for meteorologists to access critical information in a timely manner. This slowed down important work.

• Lack of unified user management
  The absence of a centralized user management system made it difficult to control user access and ensure data security across all member states.

To address the WMO’s critical challenges, Wishtree Technologies developed the Aircraft-Based Observations Metadata Repository (ABO-MR), a custom-built, cloud-native platform designed to centralize, standardize, and optimize the management of global meteorological data.

• Centralized metadata repository for all aircraft-based observation metadata, consolidating data from diverse systems (AMDAR, TAMDAR, IAGOS).

• Automated compliance and validation protocols to ensure compliance with WMO-No. 1200 and WIGOS standards.

• Scalable cloud infrastructure in AWS leveraging auto-scaling capabilities to support the processing of over 10,000 aircraft records and accommodate future growth.

• Secure user management and role-based access control by way of integration Azure Active Directory (Azure AD).

• Seamless integration and data exchange with WMO systems like OSCAR/Surface facilitated by standardized RESTful APIs and WMDR XML exports.

• Geospatial visualization and reporting with real-time insights into fleet coverage and data distribution.

• AI-Ready architecture modular design, and machine readable metadata profiles to allow for the future implementation of machine learning algorithms.