Digital Commons Lab

OpenStreetMap's success continues to grow and contributions are not limited to the collection of spatial data using GPS (Global Positioning System) equipment. A very wide range of software tools developed by, and available to, the OSM community means that at present, anyone can also make a contribution through, for example, tracing aerial imagery, directly importing data, or by adding spatial information retrieved from smartphones. Consequently 'the map' has become increasingly rich, but the quality of the data is very often questioned and comes under scrutiny from the GIS and LBS (Location-Based Services) communities. By examining the world map generated from OpenStreetMap, it is relatively easy to identify areas which are more or less well supported in community mapping activities; a very high level of spatial detail in certain areas can indicate the quality of OSM data. MVP OSM is a software tool designed to highlight areas in OpensStreetMap where users (contributors) are dedicated to providing high levels of spatial detail. This usually correlates with the use of a GPS and on-the-ground mapping, or, at the very least, a deep local knowledge of the area and an inherent desire to see it represented in the highest level of detail on OpenStreetMap. The input to MVP OSM is an OSM XML file, which is converted by Python into a file for spatialite (the GIS extension for sqlite). Within spatialite the data is processed to create clusters and using these spatial clusters, the tool can then derive the activity of single or multiple users in that area. Vector layers and heatmaps are generated as output that can be overlaid onto OSM maps. A high level of detail can be considered a good indicator of the quality of OSM data within a given area. The MVP OSM tool hides the details of OSM XML processing, which many researchers find difficult, and processes the data to produce very useful visualizations of contributor activity in any given OSM area.

OpenStreetMap's success continues to grow and contributions are not limited to the collection of spatial data using GPS (Global Positioning System) equipment. A very wide range of software tools developed by, and available to, the OSM community means that at present, anyone can also make a contribution through, for example, tracing aerial imagery, directly importing data, or by adding spatial information retrieved from smartphones. Consequently 'the map' has become increasingly rich, but the quality of the data is very often questioned and comes under scrutiny from the GIS and LBS (Location-Based Services) communities. By examining the world map generated from OpenStreetMap, it is relatively easy to identify areas which are more or less well supported in community mapping activities; a very high level of spatial detail in certain areas can indicate the quality of OSM data. MVP OSM is a software tool designed to highlight areas in OpensStreetMap where users (contributors) are dedicated to providing high levels of spatial detail. This usually correlates with the use of a GPS and on-the-ground mapping, or, at the very least, a deep local knowledge of the area and an inherent desire to see it represented in the highest level of detail on OpenStreetMap. The input to MVP OSM is an OSM XML file, which is converted by Python into a file for spatialite (the GIS extension for sqlite). Within spatialite the data is processed to create clusters and using these spatial clusters, the tool can then derive the activity of single or multiple users in that area. Vector layers and heatmaps are generated as output that can be overlaid onto OSM maps. A high level of detail can be considered a good indicator of the quality of OSM data within a given area. The MVP OSM tool hides the details of OSM XML processing, which many researchers find difficult, and processes the data to produce very useful visualizations of contributor activity in any given OSM area.

Social capital broadly refers to the opportunities an individual has by being part of a network of relationships. Recently organizations started deploying internal Enterprise 2.0 platforms and Social Network Sites (SNS) to improve how employees collaborate and work. In this paper we report our analysis of the relationships between social capital and the use of a SNS in a research institute. Data collected through a survey from 54% of its 670 employees have been investigated with factor and regression analysis. We found users enabled to use the system, currently one third of all employees, have significantly higher social capital. Moreover social capital correlates with selfreported intensity of SNS usage, while we did not find statistically significant correlation with real usage extracted from system logs but for the unexpected fact that heavy users exhibit a smaller knowledge of their colleagues. We also find significant relationships between social capital and different demographic features such as seniority, job role, age, gender. There are few studies analyzing the real impact of SNSs on employees ability to collaborate. We believe further work is needed in this area so we released the SNS we developed as open source software, aiming at promoting its adoption by other organizations. We also released the dataset we collected in this analysis for comparative purposes. Recently organizations started deploying advanced Web portals on their intranets, sometimes called Enterprise 2.0 [1]. Similar in inspiration to Web2.0 and social network sites such as Facebook, Flickr or Youtube, their goal is to improve collaboration among employees by letting them elicit and organize knowledge relevant for their daily job needs.

The important role of open data in emergencies During emergencies, the geographic information plays a very important and delicate role becoming the main tool to understand what happened and to take decisions. The data therefore will play a crucial role. The availability of data as soon as possible, with the guarantee that they are correct, is a non-trivial aspect.

OpenStreetMap (OSM, https://www.openstreetmap.org) is currently the largest, richest, most up-to-date and complete open geospatial database, in the world. OSM is probably the most popular crowdsourced geographic information project in the world.

Availability of up-to-date geographic datasets, including the information voluntarily created by ordinary people, is crucial for disaster management in areas affected by catastrophic events and humanitarian crises. OpenStreetMap (OSM) is the most popular Volunteered Geographic Information (VGI) project that has been extensively used for collaborative mapping in areas affected by natural disasters. This article provides an overview on how OSM data are exploited in disaster response scenarios and illustrates their specific application during the recent Italian earthquakes.

The disclosure of data is often accompanied by many promises from an open government standpoint that use catchwords such as transparency, participation and engagement, not to mention innovation, viewing such data as a raw material that could be used by old and new companies to create and improve services. Although these promises effectively represent the potential of open data, in actual fact, they prove very difficult to accomplish. The delays, or rather the hurdles, that stand in the way of these data's use are multi-faceted: cultural resistance to sharing data, legal constraints and issues with creating sustainable updating processes. By retracing the steps of open data, this article highlights these issues, proposes courses of action and suggests considering open data as a common good: a resource shared by all the members of a community and from which everyone can benefit.

Availability of up-to-date geographic datasets, including the information voluntarily created by ordinary people, is crucial for disaster management in areas affected by catastrophic events and humanitarian crises. OpenStreetMap (OSM) is the most popular Volunteered Geographic Information (VGI) project that has been extensively used for collaborative mapping in areas affected by natural disasters. This article provides an overview on how OSM data are exploited in disaster response scenarios and illustrates their specific application during the recent Italian earthquakes.

Digital humanitarians represent the current generation of volunteers providing timely contributions in the form<br> of digital map data in the aftermath of natural disasters. Starting from the tragic 2010 earthquake in Haiti and<br> thanks to the success of the OpenStreetMap (OSM) project, the presence and coordination of these volunteers<br> have grown incredibly over the past years. This work investigates the dynamics of the mapping process and the<br> nature of the OSM volunteers who contributed map data after the 2016 earthquake in Central Italy. The analyses<br> show that the existing OSM users were the majority of those contributing to the mapping activity, with less edits<br> performed by new users. The collaborative mapping process was efficiently coordinated through a dedicated<br> platform and the area hit by the earthquake was significantly edited in OSM after the disaster.

Il progetto SMASH (https://www.smashproject.eu), co-finanziato da Climate-KiC (https://italy.climate-kic.org) e in sperimentazione in 12 città tra Italia (Ferrara, Reggio Emilia, Bologna, Milano, Rimini, Trento e Rovereto), Regno Unito (Bristol, Norfolk, Leicester, Salford) e Brasile (Joinville), ha l'obiettivo di supportare i diversi attori dell'ecosistema della mobilità sostenibile (amministrazioni cittadine, <em>authority</em> locali dei trasporti, aziende di trasporto pubblico, gestori di servizi di <em>bike o car sharing</em>, gestori di campagne di incentivazione alla mobilità sostenibile, etc) nel rendere migliori e più efficienti i servizi offerti alla collettività. Per ottenere questo risultato il progetto ha sviluppato una piattaforma in cui i dati che già esistono – e che normalmente sono raccolti dagli attori del territorio per gli obiettivi più disparati – sono messi in relazione, elaborati ed aggregati per identificare i punti critici de...

Following the COVID-19 pandemic emergency, in mid-December 2020 the Italian government introduced travel restrictions during the Christmas holidays. In the implemented policies there was an exception: citizens of a municipality of up to 5,000 citizens can move within an area of 30 kilometers from their respective borders. This policy was used again in the following months to manage travel during the pandemic. 30Cappa is a data visualization created by three civic hackers to give citizens the opportunity to understand this policy ("cappa" is the pronunciation of the letter "k" in Italian and means "km"). The project consists of a website where it is possible to receive information on the matter and the cartographic representation of the municipalities that correspond to the exception. The site has reached 350,000 unique visitors in two months and there has been a lot of talk about it in the media. This work highlights how the transformation of a policy into a tangible product such as a map created with the open data available, becomes an effective tool to guide citizens and also to review the policies themselves.

Data and digital technologies have been at the core of the societal response to COVID-19 since the beginning of the pandemic. This work focuses on the specific contribution of the OpenStreetMap (OSM) project to address the early stage of the COVID-19 crisis (approximately from February to May 2020) in Italy. Several activities initiated by the Italian OSM community are described, including: mapping ‘red zones’ (the first municipalities affected by the emergency); updating OSM pharmacies based on the authoritative dataset from the Ministry of Health; adding information on delivery services of commercial activities during COVID-19 times; publishing web maps to offer COVID-19-specific information at the local level; and developing software tools to help collect new data. Those initiatives are analysed from a data ecosystem perspective, identifying the actors, data and data flows involved, and reflecting on the enablers and barriers for their success from a technical, organisational and...