OpenStreetMap (OSM) is a collaborative mapping platform that provides an open-source, community-driven alternative to public national datasets. Unlike many government-provided geospatial data sources, which often adhere to strict data models and standards, OSM offers a more flexible and inclusive approach to mapping and data collection.
Flexibility of the Tagging System
One of the key features that sets OSM apart is its tagging system. In OSM, data about features such as roads, buildings, and natural landmarks is recorded using a system of tags—simple key-value pairs that describe the attributes of each feature. For example, a road might be tagged as highway=residential to indicate that it is a residential street. This system allows for great flexibility, as contributors can create and use tags that are relevant to the specific features they are mapping, even if those features do not fit neatly into more rigid data models.
This flexibility is particularly beneficial in cases where local knowledge and specific details are important. Contributors can include a wide variety of information, such as accessibility features, surface types, or even historical significance, without being constrained by a predefined set of categories. As a result, OSM often includes a rich variety of data that might not be available in more formal national datasets.
Challenges of the Tagging System
However, the very flexibility that makes OSM powerful can also be a drawback. The lack of a strict, standardised data model means that the same type of feature might be tagged in different ways by different contributors. This inconsistency can lead to challenges in data quality and interoperability, making it difficult to use OSM data in some GIS applications, especially those based on the relational data model.
Most traditional GIS data models rely on the Relational data model, which organise data into tables with fixed schemas. These models are designed for structured data with consistent types and categories, making them less suited to the fluid and often inconsistent nature of OSM’s tag-based data. As a result, integrating OSM data into these systems can require significant preprocessing, including standardising tags, resolving conflicts, and transforming the data into a format compatible with relational tables.
OSM as an Alternative to National Datasets
Despite these challenges, OSM serves as a valuable alternative to national datasets, especially in regions where official data is outdated, incomplete, or simply unavailable. The community-driven nature of OSM allows for rapid updates and the inclusion of local details that might be overlooked in official maps. For many users, the trade-off between flexibility and consistency is worth it, particularly when the goal is to capture diverse and dynamic information that evolves over time.