Data Structures and Integrations for Environmental Reporting and Analytics

Abstract Data structure and integrations are vital components to a successful implementation of environmental software used for tracking, reporting, and data analytics. Defining the expected data outputs at the beginning of a software implementation results in an efficient and effective reporting process, which meets stakeholders’ expectations, and is the foundation for advanced analytics. A robust evaluation of the expected reporting, whether it is required for regulatory, voluntary, or internal reporting, will set the requirements for source system data. If the data in the identified source systems is not available or reliable, the outputs of the environmental system should be adjusted, or the project should be postponed until the source system data is readily available. This paper explains how the project team and stakeholders defined the requirements, data fields, calculation methodologies, necessary reports, and document approvals. Documentation is necessary to effectively communicate the requirements and expectations for developers, while also allowing appropriate stakeholders to agree on the project deliverables. Without proper documentation and approvals, the project outputs are likely to miss the intended outputs and require rework. During the project planning phase, the implementation teams created workflows or diagrams tracing components for each desired output back to source systems. The diagrams identified data points such as source system fields, frequency of updates, unit of measure, unique identifies, Global Positioning System (GPS) coordinates, or run-time information. The data point definitions show the availability of the data from the source system and frequency of updates of source system data to influence integration design.