Designing Metadata and Schema Structure—setting up the structure of your geodatabase, defining how different datasets will interact, and establishing standards for metadata. This step ensures data organization, consistency, and accessibility throughout the GIS application

The first step involves designing the metadata and schema structure, which entails setting up the structure of the geodatabase—a database designed to store, query, and manipulate geographic information and spatial data. It's a type of database that integrates geographic data (spatial data), attribute data, and spatial relationships between different datasets, providing a more robust framework for managing spatial data compared to traditional flat file storage methods, defining how the different datasets will interact, and establishing standards for metadata.

Following this, you must establish metadata standards, with INSPIRE and ISO 19115 commonly used for geospatial data

After deciding on the standards, creating metadata templates based on the chosen standards becomes crucial. Documenting your data collection and entry procedures also forms a significant part of the workflow. The last part of this stage involves implementing data quality controls by establishing procedures to check your data's quality

The output of this process is a structured geodatabase, comprehensive metadata standards, and data collection and quality control procedures.

Data Collection and Digitization: In this step, you will collect spatial and non-spatial data from various sources. The accuracy and comprehensiveness of your data collection efforts are essential for accurate property assessment and tax calculations. Highlight the need for thorough planning and testing within the workflow to address challenges that may arise when integrating different open-source software components.

Identify Data Sources: Identify the sources from which you will collect data. This can include local government databases, open-source data platforms, public records, surveys, or field data collection.

Collect Spatial Data: Collect the necessary spatial data for property assessment. This may involve acquiring parcel boundaries, future development plans, satellite images, topographic data, land use data, road networks, environmental data, and other relevant spatial information. QGIS is commonly used for handling and processing spatial data. It provides various data collection, analysis, and validation tools.

Collect Non-Spatial Data: Collect the non-spatial data pertinent to property assessment. This can include information such as structural characteristics of properties, rental history, ownership details, sale history, tax records, local market data, zoning regulations, environmental efficiency ratings, disaster history, crime statistics, liens and judgments, and other relevant data. This is a foundational step. If you have physical paper records, you must manually input this data or use scanning and Optical Character Recognition (OCR) technology to digitize the records. Check the digitized data for any errors or discrepancies. Data in Excel or other digital formats can be compiled for easier processing in the next steps. For OCR, you can use tools like Adobe Acrobat or Tesseract. You can use Excel or a similar spreadsheet tool to organize digital data. Tools like spreadsheets or databases (e.g., Microsoft Excel or PostgreSQL) can also be used for managing and cleaning non-spatial data.