Mobile Phone Data for Mapping Urban Dynamics

During the last few years, new tools for estimating people’s density in cities have emerged through mobile network data. As opposed to the more traditional methods of urban surveys, the use of aggregated and anonymous mobile phone network log files has shown promise for large-scale surveys with notably smaller efforts and costs. Moreover, a frequent data feed from the mobile network has been argued to demonstrate fine grain over-time variation in urban movements, lacking from the traditional prediction methods. Despite the positivist approach to the new methodology, additional evidence is needed to show how mobile network data correlate with the actual presence of people, and how they can be used to map different urban domains. We try to address this shortcoming presenting the results of a research carried out in Lombardy Region, using mobile phone data provided by Telecom Italia, as a promising approach to assist the traditional database and analysis of urban dynamics as new challenges for urban plannin

A generalized graph-spectral approach to melodic modeling and retrieval

The development of both musicologically based and efficient music information retrieval metrics to query large music database is crucial in modern music information retrieval, knowledge management and database research. Graph spectral representation of pitch class sequences has proved to outperform other pitch class based melodic similarity methods. Here we compare different spectral approaches to structural queries in databases of symbolic music, which exploits mathematical music theory results to improve the descriptive power of representative graphs. In particular, we explore graph representation of other relevant music features like intervals. The experiments have been conducted on a subset of the RISM collection, and results have been evaluated against a ground truth for the same collection developed for the MIREX competition

Monitoring tourists and visitors through coarse mobile phone data

Visitors and tourists are among the more important urban populations for their impact on local economy, on global fluxes dimensions and on urban vitality and attractiveness. In recent years we assisted at an extraordinary increase in mobile communications and mobile phone is the widest adopted technology. Within the field of urban computing, a new approach has emerged for mapping urban dynamics. In this paper we will introduce and exploit a novel kind of data, namely HLR MSC counters. In this paper we present our research showing how this kind of data can help monitoring and mapping spatial and temporal variability of population, visitors and tourists, in the Lombardia region

Share water sample metadata: an example from Sardinia LTER-Italy marine and freshwater sites

A collection of phytoplankton fixed water samples has been maintained at the Department of Architecture, Design and Planning (DADU) of the University of Sassari, which is part of LifeWatch Italy (LW-ITA). The DADU collection includes samples from different aquatic ecosystems in Sardinia (freshwater, transitional and coastal marine), comprising research stations of sites “14 Sardinian marine ecosystems” and “10 Lake Ecosystems of Sardinia” of LTER-Italy (Long Term Ecological Research). The samples have been collected within different research projects since late 70s. Scientific information available for each sample includes the list of phytoplankton species, their abundances and biovolume. This information has been reported on “raw counting tables”. Furthermore, since the samples have been collected for ecological studies, each sample has been accompanied by data of sets of environmental variables, including measures obtained directly in the field and in the laboratory, reported on “sampling sheets” and “laboratory tables”, partially already organized in electronic format. A project funded by the Fondazione di Sardegna has allowed starting in cataloguing the phytoplankton samples, collecting and digitization of documents associated with them as well, with the general objective to valorise the ecological information present and linked to the samples. Nowadays, the use of innovative techniques (e.g. molecular techniques) can allow obtain more information on biodiversity also from old samples. Consequently, the DADU collection represents a potential source of biodiversity information. A process of sharing, by the use of CSIRO physical samples metadata model according with International Geo Sample Number (IGSN), gathered in the project has been started

Sharing water and sediment samples metadata: an example from the LTER-Italy marine and freshwater sites

Water and sediment samples (also called specimens) are key observational units in environmental sciences, particularly in marine ecology and geosciences, hydrobiology and limnology. Such samples must be maintained in the medium/long term and require to be easily discoverable through unique identification standards and metadata catalogues which are, at the moment, lacking. We present here both best practices and technological solutions for representing and sharing sample descriptions, using as an example water and sediment samples from a number of marine and freshwater sites belonging to the Italian Long-Term Ecological Research network (LTER-Italy). In LTER-Italy, observations are stored and shared following ISO 19156:2011 (O&M). We propose to enhance this practice by introducing the use of the physical samples metadata model identifying with International Geo Sample Number (IGSN) proposed by CSIRO. Information available for each physical sample includes, among the others, the sample name, type, the sampling location and method, and the indication of the sub-samples collected, with the relative sampling methodologies. Moreover, when the samples are analysed, for each of them a list of other information becomes available together with environmental variables data, including measures obtained directly in the field. We present here a proposal that provides a way for describing, archiving, visualising and sharing samples and allows connecting the different related entities, such as sampling methods, persons, instruments, and observations representations. A hyperlinking approach is tested as a valuable solution to manage all the information, giving the possibility to move among them, learning more about the data life cycle. Applying this approach makes it possible to refer each entity to the other, describing not only the relationships between them but also those among the different sub-entities generated from the same samples (e.g. from the sediment core to the slide with recognized foraminifera or from the water sample to the phytoplankton sample)