Documentation
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Practical guide for the publication of Spatial Data
A spatial data or geographical data is that which has a geographical reference associated with it, either directly, through coordinates, or indirectly, such as a postal code. Thanks to these geographical references it is possible to locate its exact...
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Guidance for the deployment of data portals. Good practices and recommendations
Open data portals help municipalities to offer structured and transparent access to the data they generate in the exercise of their functions and in the provision of the services they are responsible for, while also fostering the creation of applications...
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Practical guide for the publication of linked data
It is important to publish open data following a series of guidelines that facilitate its reuse, including the use of common schemas, such as standard formats, ontologies and vocabularies. In this way, datasets published by different organizations will...
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Introduction to data anonymisation: Techniques and case studies
Data anonymization defines the methodology and set of best practices and techniques that reduce the risk of identifying individuals, the irreversibility of the anonymization process, and the auditing of the exploitation of anonymized data by monitoring...
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Practical guide to publishing tabular data in CSV files
Nowadays we have more and more sources of data at our fingertips. According to the European Data Portal, the impact of the open data market could reach up to EUR 334 billion and generate around 2 million jobs by 2025 ('The Economic Impact of Open Data...
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A practical guide to publishing Open Data using APIs
An application programming interface or API is a mechanism that allows communication and information exchange between systems. Open data platforms, such as datos.gob.es, have this type of tool to interact with the information system and consult the...
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Practical guide for improving the quality of open data
When publishing open data, it is essential to ensure its quality. If data is well documented and of the required quality, it will be easier to reuse, as there will be less additional work for cleaning and processing. In addition, poor data quality can be...
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A practical introductory guide to exploratory data analysis in Python
The following presents a new guide to Exploratory Data Analysis (EDA) implemented in Python, which evolves and complements the version published in R in 2021. This update responds to the needs of an increasingly diverse community in the field of data...
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How to use OGC APIs to enhance geospatial data interoperability
In a world where geospatial information is crucial to address global challenges such as climate change and natural resource management, interoperability and the creation of standards are essential. Interoperability facilitates collaboration between...
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Glossary of data-related terms
The following is a definition of various terms regarding data and related technologies. 1. Glossary of terms related to open data. (You can download the accessible version here) 2. Glossary of terms related to new...