What are the skills and competencies required for GIS integration and interoperability?

1 Data standards and formats

One of the fundamental skills for GIS integration and interoperability is the ability to understand and work with different data standards and formats. Data standards are the rules and specifications that define how data is structured, encoded, and exchanged. Data formats are the specific ways that data is stored and represented in files or databases. For example, some common data standards and formats for GIS are OGC, GeoJSON, Shapefile, and PostGIS. A GIS professional needs to be familiar with the advantages and limitations of various data standards and formats, and how to convert, validate, and manipulate them using tools and software.

2 Data quality and metadata

Another important skill for GIS integration and interoperability is the ability to assess and improve data quality and metadata. Data quality refers to the accuracy, completeness, consistency, and reliability of data. Metadata is the information that describes the characteristics, origin, and usage of data. For example, some common metadata elements for GIS are spatial reference system, scale, projection, date, and author. A GIS professional needs to be able to evaluate and document data quality and metadata, and apply methods and techniques to enhance, correct, or harmonize them.

3 Data integration and fusion

A core skill for GIS integration and interoperability is the ability to integrate and fuse data from different sources and platforms. Data integration is the process of combining data from multiple sources into a single, coherent, and consistent data set. Data fusion is the process of extracting information from multiple sources and creating a new data set that provides more value than the individual sources. For example, some common data integration and fusion methods for GIS are spatial join, overlay, interpolation, and classification. A GIS professional needs to be able to apply data integration and fusion methods using software and algorithms, and understand the implications and challenges of data heterogeneity, redundancy, and uncertainty.

4 Data sharing and dissemination

A key skill for GIS integration and interoperability is the ability to share and disseminate data across different platforms and users. Data sharing is the process of making data available and accessible to others. Data dissemination is the process of distributing and communicating data to a target audience. For example, some common data sharing and dissemination platforms and tools for GIS are web services, APIs, portals, and dashboards. A GIS professional needs to be able to design, implement, and manage data sharing and dissemination platforms and tools, and ensure data security, privacy, and ethics.

6 Collaboration and communication

A crucial skill for GIS integration and interoperability is the ability to collaborate and communicate with different stakeholders and partners. Collaboration is the process of working together with others to achieve a common goal or outcome. Communication is the process of exchanging information and ideas with others using verbal or non-verbal means. For example, some common collaboration and communication tools and strategies for GIS are online platforms, workflows, standards, protocols, and documentation. A GIS professional needs to be able to collaborate and communicate effectively with different stakeholders and partners, such as data providers, users, developers, managers, and decision-makers.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?