Abstract. Bike Sharing Systems (BSS) are growing worldwide for the social and environmental benefits that they can provide. Thanks to the increasing popularity of the BSS and the availability of monitoring technologies, there is a continuous production of data that can help to understand bike usage and to improve its design and management. This study aims at exploring BSS users’ mobility patterns habits and the demand for the service. To reach this scope, the available data have been preprocessed in order to allow data mining and data visualization with open source tools based on Python. The study case regards the BikeMi BSS of the City of Milan between June 2015 to December 2018. The suggested approach proceeded, first, with the categorization of the user typology based on the frequency of use of the service; at a second stage, the influence of the day typology on the use of the service has been explored; third, the spatial and temporal patterns of the BSS use among the stations has been analysed; fourth, the influence of meteorological conditions on the use of the service has been considered; at last, the clustering of the stations with similar bikes use activity through K-Means has been performed. As expected, it was observed that the service is extensively used for commuting to work-related activities. Regular users compose a large part of the BSS community making use of the service mostly during weekdays. In addition, it was noted that only 'strong' meteorological conditions can impact the use of the service. Both the identification of the demand for the service and of the external factors that can affect its use support the clustering activities, allowing for the elimination of not relevant information and facilitating the interpretation of the obtained clusters.

Abstract. This paper describes the development of a web application to facilitate the management and processing of geoid models in the ISG collection as well as of additional information available in the ISG website (mainly projects, services and publications). The ISG service pays significant attention to metadata and data interoperability from published geoid models. As a result, the possibility of creating a database with all necessary information for describing geoid models has been considered. PostgreSQL was chosen as the database for the implementation to take advantage of PostGIS geographic processing functions for developing a Database Management System for the resources available inside the ISG service catalogue (including geoid products, software, publications, etc.). The project's web development environment is Django, a web framework which is supported by the PostgreSQL database back-end and which makes it easier to integrate new applications or processing services into the website. A model solution for raster data integration using a PostGIS database back-end named Django-raster has also been investigated as part of the implementation, provided also that it is possible to take advantage of the vast Django community. The Django-raster model allows for the storage of datasets as tiles in the database, their exposure as a Tiled Map Services (TMS), and allows as well raster map algebra operations. TMS services will be utilized to share the geoid models and metadata included in the open access archive using a WebGIS, created with OpenLayers.

<p><strong>Abstract.</strong> Open Data, and Open Government Data, are proving to be an important resource for the economic development inside the domain where information has a key role (Carrara et al., 2015). Although, different practices for data publishing have led to misalignment, underuse and repetition of information (Bizer et al., 2011). For this reason, the Public Administrations have undergone efforts on integrating the information and promoting interoperability through the implementation of best practices, as for example, the use of a common semantics vocabulary for the metadata (DCAT) as proposed by the ISA2 programme of the European Commission. The Interreg Italy-Switzerland GIOCOnDA project has been proposed for enhancing the data sharing processes in the cross-border area, particularly addressing tourism and mobility that are key economic activities for the region. For this work, a review on the data catalogues published in dati.lombardia.it and opendata.swiss is presented. The revision of the datasets showed the need for: 1) defining common semantics for the description of the categories of data to avoid the arbitrary use of vocabularies, and 2) adopting standards for the description of geodata. On the other hand, it was observed the potential to gather existing information to produce geodata querying the datasets with specific keywords that can provide spatial information. Open data, as well as the use of best practices for publishing data, push towards the use of FOSS. In this work, Python has been exploited to analyse the content of the catalogues to access web portals resources.</p>