Enterprise GIS Data Integration and Web Service Architecture for the Resilient Coastal Communities Program

Problem

The Resilient Coastal Communities Program (RCCP) requires a scalable system for integrating geospatial data from multiple communities and delivering that data through enterprise GIS infrastructure. Communities provide datasets in inconsistent formats, including ArcGIS packages, shapefiles, and file geodatabases, with varying schemas, naming conventions, and spatial references. While the initial challenge focused on standardizing and ingesting these datasets, the scope expanded to include enterprise database provisioning, schema design, performance optimization, and web-based service delivery. The system needed to support centralized data management, enable efficient querying and visualization, and scale from a small pilot group to dozens of communities without requiring structural redesign.

Analysis Procedures

This project developed into a fully integrated enterprise GIS workflow that combines Python automation, PostgreSQL database design, and ArcGIS Enterprise service delivery. A comprehensive ArcPy-based ingestion tool was created to process ArcGIS packages, extract their contents, and import datasets into a standardized structure. The tool automates package extraction, discovers geodatabases and loose datasets, enforces consistent naming conventions, and normalizes spatial references to a common coordinate system. It also includes logic to handle unknown coordinate systems through extent-based inference and routes uncertain datasets into review categories. Throughout the process, the script generates detailed logs documenting inventory, processing steps, and quality control outcomes, ensuring transparency and repeatability across runs. To support enterprise data management, a separate automation workflow was developed to provision PostgreSQL users, schemas, and connection files dynamically. This process scans incoming community datasets, derives standardized schema names, creates database users, and generates secure connection files while maintaining a persistent record of credentials. Each community’s data is isolated within its own schema, improving organization, access control, and long-term scalability of the system. A third script handles the migration of standardized datasets into the enterprise geodatabase using per-community connection files. This workflow iterates through each dataset, automatically routes data into the appropriate schema based on connection context, and applies logic for handling duplicates and overwrite conditions. By leveraging database authentication, the system ensures that datasets are written directly into the correct schema without requiring manual intervention, further reinforcing the repeatability and reliability of the pipeline. To support efficient web service delivery, custom SQL views were developed within the database to aggregate datasets across schemas into unified, service-ready layers. These views standardize attributes such as community name, theme, and subcategory while abstracting underlying schema complexity. By consolidating datasets into a consistent structure, the views enable simplified service publishing and support dynamic filtering in web applications. Data was registered with ArcGIS Server to ensure that services referenced the enterprise database directly. Map and feature services were then published and configured with attention to performance, scale dependencies, and layer organization. Web applications were developed using ArcGIS Experience Builder and ArcGIS Hub to provide users with the ability to explore data by community and theme. During development, performance challenges such as slow rendering and unresponsive filters were addressed by refining SQL views and reducing unnecessary data complexity, resulting in a more responsive and usable system.

Results

The final system is a fully automated and scalable enterprise GIS architecture that integrates data ingestion, database management, and web service delivery. Incoming datasets can be processed through a repeatable workflow that significantly reduces manual effort while improving consistency. The PostgreSQL enterprise geodatabase provides a centralized data store organized by schema, while custom SQL views deliver standardized, service-ready datasets. Web services published through ArcGIS Server provide reliable, real-time access to data, and web applications offer an accessible interface for users to explore and filter datasets without requiring advanced GIS software. The system was designed to scale from an initial set of eight pilot communities to more than forty communities without requiring fundamental changes to the underlying architecture.

Reflection

This project evolved from a data processing workflow into a comprehensive enterprise system design effort. One of the most important lessons was that automation alone is not sufficient; ensuring that data can be efficiently delivered and used at scale requires careful attention to database structure and performance. Developing separate scripts for ingestion, provisioning, and migration reinforced the importance of modular system design, where each component addresses a specific task while contributing to a larger, cohesive workflow. Another key takeaway was the value of pushing data logic into the database through the use of SQL views, which simplified service configuration and improved overall system maintainability. This experience represents a shift from using GIS tools to designing and implementing GIS systems, where decisions about data structure, processing workflows, and service delivery directly impact performance, scalability, and user experience.