How to Select Best Results?
When searching for datasets in Dateno, you will encounter facets—filters based on dataset attributes that help refine your results. Understanding how facets work and how to use them effectively can dramatically improve the quality of your search outcomes.
What Are Facets?
Facets are based on dataset attributes and allow you to focus your search on datasets that match specific criteria. Each facet contains multiple options corresponding to possible values of the attribute it represents.
Logic Within and Across Facets
- Within a facet: The logic is OR. Selecting multiple options in a single facet will include datasets matching at least one of the selected options.
- Across different facets: The logic is AND. Selecting options in multiple facets will narrow your results to datasets matching all of them. Datasets that do not meet any facet condition will be excluded.
For example:
- Selecting both
GeoportalandOpen data portalin the Catalog type facet will include datasets from either type. - Adding a selection in the Country facet, such as
Germany, will restrict results to datasets from those catalog types AND associated with the Germany.
Dynamic Facet Behavior
When you select options in one facet, the search engine narrows the set of selected datasets. Consequently, options in other facets that no longer fit any of the remaining datasets will be hidden. This dynamic behavior simplifies the search process by presenting only relevant options.
IMPORTANT
The order in which you select facets does not affect the final results. The search engine always applies all selected criteria consistently.
Facets in Dateno
The following table describes the available facets and their role in refining your dataset search:
| Facet | Description |
|---|---|
| Catalog type | Classification of datasets by the type of catalog, such as geoportals, scientific repositories, or open data portals. |
| Who owns data | Information about dataset publishers or owners, focusing on trusted or relevant sources. |
| Macroregion | Geographic granularity for larger areas. |
| Country | Connection to a primary country of focus, useful for finding region-specific data. |
| Subregion | Geographic granularity for smaller areas, such as states or administrative divisions. |
| Data theme | Categories aligned with INSPIRE Directive, such as environmental monitoring or transportation. |
| Topic category | Taxonomy based on ISO 19115 for geospatial data, ensuring interoperability and consistency. |
| Software | Association with content management systems or platforms managing their catalogs. |
| Language | Language of dataset content or metadata, helping users filter datasets they can work with. |
| Source | Types of origins for datasets, such as APIs, repositories, or portals. |
| Format | File formats available for datasets, such as CSV, JSON, or GIS-specific formats. |
| License | Usage rights, ensuring compliance with legal requirements and user needs. |
| Datatypes | Organization by general data types, such as geospatial data, tabular data, or text documents. |
Tips for Using Facets Effectively
- Start broad, then refine: Begin with general criteria and narrow down as you identify what’s most relevant.
- Combine facets strategically: Use facets that reflect your research priorities, such as selecting specific themes, regions, or data formats.
- Monitor hidden options: If certain options disappear after applying a facet, it’s an indication that no datasets in the current results match those criteria.
By understanding and utilizing facets effectively, you can significantly improve your dataset search experience, ensuring the results are tailored to your specific needs.