Today it becomes possible to gather, share and integrate data from various sources along with a remarkable new capacity for data analysis and visualization. The consequences are transformative. Data, algorithms to analyze data and data visualization expand the opportunities for meaningful debate, dialogue and policy making in informed societies.

This site is dedicated to communicate research findings about real-world uses of data as well as guidance in data practices. The focus is on spatial data analysis and text mining.

Spatial data analysis is the process of analyzing and interpreting data that has a spatial component associated with it. Spatial data analysis often involves the use of geographic information systems (GIS software), which allows users to analyze and visualize spatial data. Spatial data analysis is used in a wide range of fields, including geography, social sciences, urban planning and environmental science, among others.

Text mining is the process of extracting meaningful insights from unstructured text data. Text mining involves a combination of data analytics, natural language processing and machine learning to analyze and gain insights from large amounts of text data. Text mining can be applied to a wide variety of data sources, including social media content, customer reviews, news articles and other types of text data and it is used in many fields, including business, marketing and the social sciences.