Pinned Repositories
andrea-ballatore-publications
Academic publications by Andrea Ballatore (author copies)
calculating-uniqueness
An index to calculate the uniqueness of multivariate observations (R code)
facebook-city
This repository contains the data and code associated with the paper titled "Facebook City: Place-named groups as urban communication infrastructure in Greater London". This is part of the "Localising Content Governance" project, funded by Facebook Research.
google-places-api-r
Google Places API in R: This R script takes geospatial geometries as input and retrieves all Google Places Points of Interest (POIs) in the area, generating as many as sub-queries as needed. This script was developed for non-profit academic research in geographic data science.
litter-dynamics
Urban litter, such as cans, packaging, and cigarettes, has significant impacts and yet little is known about its spatio-temporal distribution, with little available data. In contexts of data scarcity, crowdsourcing provides a low-cost approach to collecting a large amount of geo-referenced data. We consider 1.7 million litter observations in the Netherlands, collected by the crowdmapping project Litterati. First, we analyze the biases of this data at the province and municipality level. Second, in a local case study with high-quality data (the city of Purmerend), we investigate the spatial distribution of urban litter and the points of interest that attract it. This study’s findings can support both the crowdmapping process, steering volunteers efforts, and policy-making to tackle litter at the urban level.
open-geo-data-education
Open Geospatial Datasets for GIS Education: This is a repository of open geospatial datasets to be used in an educational context. I created these files over years of teaching Geographic Data Science and GIS. All original datasets are freely available online with open data licenses (see the dataset attribution for details). All the datasets in this repository have been selected, cleaned, harmonised, and repackaged for GIS exercises in a higher-education context. This is a pretty time-intensive process that other educators can hopefully avoid by using these versions.
place-vocabulary
This repository contains a vocabulary of nouns used to describe places, such as river, restaurant, mountain, and park. The vocabulary is the result of a merge between the GeoNames Ontology, the DBpedia Ontology, and Wordnet, and includes both natural and man-made place types. Each term is linked to the URIs in the data sources.
search-geography
Data and code related to research on Search Engine Geographies. Every day, billions of Internet users rely on search engines to find information about places to make decisions about tourism, shopping, and countless other economic activities. In an opaque process, search engines assemble digital content produced in a variety of locations around the world and make it available to large cohorts of consumers. Although these representations of place are increasingly important and consequential, little is known about their characteristics and possible biases.
teaching-programming-for-gis
Jupyter notebooks to teach an introduction to Programming for GIS, including core Python concepts and packages to work with vector, raster, and network data.
wikimapia-research
Research data on crowd-mapping project Wikimapia: Wikimapia is a major privately-owned volunteered geographic information (VGI) project to collect information about places. Over the past ten years, Wikimapia has attracted hundreds of thousands of contributors and collected millions of data points, including towns, restaurants, lakes, and tourist attractions (http://wikimapia.org). Unlike OpenStreetMap, Wikimapia adopts a "placial" perspective, favouring rich descriptions over detailed geometries and encouraging the collection of textual and visual content about places with approximate footprints. In this article, we first trace the origin and development of Wikimapia as a for-profit project, intimately linked with search engine advertising.
andrea-ballatore's Repositories
andrea-ballatore/open-geo-data-education
Open Geospatial Datasets for GIS Education: This is a repository of open geospatial datasets to be used in an educational context. I created these files over years of teaching Geographic Data Science and GIS. All original datasets are freely available online with open data licenses (see the dataset attribution for details). All the datasets in this repository have been selected, cleaned, harmonised, and repackaged for GIS exercises in a higher-education context. This is a pretty time-intensive process that other educators can hopefully avoid by using these versions.
andrea-ballatore/teaching-programming-for-gis
Jupyter notebooks to teach an introduction to Programming for GIS, including core Python concepts and packages to work with vector, raster, and network data.
andrea-ballatore/place-vocabulary
This repository contains a vocabulary of nouns used to describe places, such as river, restaurant, mountain, and park. The vocabulary is the result of a merge between the GeoNames Ontology, the DBpedia Ontology, and Wordnet, and includes both natural and man-made place types. Each term is linked to the URIs in the data sources.
andrea-ballatore/google-places-api-r
Google Places API in R: This R script takes geospatial geometries as input and retrieves all Google Places Points of Interest (POIs) in the area, generating as many as sub-queries as needed. This script was developed for non-profit academic research in geographic data science.
andrea-ballatore/search-geography
Data and code related to research on Search Engine Geographies. Every day, billions of Internet users rely on search engines to find information about places to make decisions about tourism, shopping, and countless other economic activities. In an opaque process, search engines assemble digital content produced in a variety of locations around the world and make it available to large cohorts of consumers. Although these representations of place are increasingly important and consequential, little is known about their characteristics and possible biases.
andrea-ballatore/wikimapia-research
Research data on crowd-mapping project Wikimapia: Wikimapia is a major privately-owned volunteered geographic information (VGI) project to collect information about places. Over the past ten years, Wikimapia has attracted hundreds of thousands of contributors and collected millions of data points, including towns, restaurants, lakes, and tourist attractions (http://wikimapia.org). Unlike OpenStreetMap, Wikimapia adopts a "placial" perspective, favouring rich descriptions over detailed geometries and encouraging the collection of textual and visual content about places with approximate footprints. In this article, we first trace the origin and development of Wikimapia as a for-profit project, intimately linked with search engine advertising.
andrea-ballatore/andrea-ballatore-publications
Academic publications by Andrea Ballatore (author copies)
andrea-ballatore/calculating-uniqueness
An index to calculate the uniqueness of multivariate observations (R code)
andrea-ballatore/facebook-city
This repository contains the data and code associated with the paper titled "Facebook City: Place-named groups as urban communication infrastructure in Greater London". This is part of the "Localising Content Governance" project, funded by Facebook Research.
andrea-ballatore/litter-dynamics
Urban litter, such as cans, packaging, and cigarettes, has significant impacts and yet little is known about its spatio-temporal distribution, with little available data. In contexts of data scarcity, crowdsourcing provides a low-cost approach to collecting a large amount of geo-referenced data. We consider 1.7 million litter observations in the Netherlands, collected by the crowdmapping project Litterati. First, we analyze the biases of this data at the province and municipality level. Second, in a local case study with high-quality data (the city of Purmerend), we investigate the spatial distribution of urban litter and the points of interest that attract it. This study’s findings can support both the crowdmapping process, steering volunteers efforts, and policy-making to tackle litter at the urban level.
andrea-ballatore/map-context-frame
This is JavaScript framework to support map navigation by placing contextual information around the map, bridging the on- and off-screen spaces. The proposed framework allows the dynamic generation of spatial cues in a context frame in the map that show objects located outside of the map, reducing the need for relative positioning. The approach is based on an algorithm that ranks the prominence of nearby objects, and is illustrated on a case study about a small Italian town. This framework can also support cognitive mapping, showing spatial relations between geographical objects in a novel way. The source code and a demo of the framework are available online.
andrea-ballatore/pgis-usability
Research material for usability evaluation of Participatory GIS: While many approaches and procedures have been proposed to assess usability in general, to date there is no standardized way to measure the overall usability of a PGIS. For this purpose, we introduce the Participatory GIS Usability Scale (PGUS), a questionnaire to evaluate the usability of a PGIS along five dimensions (user interface, spatial interface, learnability, effectiveness, and communication). The questionnaire was developed in collaboration with the user community of SeaSketch, a web-based platform for marine spatial planning. PGUS quantifies the subjective perception of usability on a scale between 0 and 100, facilitating the rapid evaluation and comparison between PGIS. As a case study, the PGUS was used to collect feedback from 175 SeaSketch users, highlighting the usability strengths and weaknesses of the platform.
andrea-ballatore/sonification-uncertainty
This data is related to a study on how sound can be used to convey information about data uncertainty in an intuitive way. To answer the research question How intuitive are sound dimensions to communicate uncertainty?, we carry out a cognitive experiment, where participants were asked to interpret the certainty/uncertainty level in two sounds A and B (N=33). We produce sound stimuli by varying sound dimensions, including loudness, duration, location, pitch, register, attack, decay, rate of change, noise, timbre, clarity, order, and harmony.