Schlpfer, M. et al. This dataset provides information about the current administrative regions in Europe. The study of socio-technical systems has been revolutionized by the unprecedented amount of digital records that are constantly being produced by human activities such as accessing Internet services, using mobile devices, and consuming energy and knowledge. Blondel, V., Decuyper, A. Trentino is an autonomous province of Italy, located in the northern part of the country. As you can see, the data was supplied in batch mode, using downloadable compressed files, or through API, if this kind of access is meaningful.API data access allows a specific audience to use data more quickly, easily and efficiently when they are looking to do something specific with the information. Since Telecom Italia only possesses the data of its own customers, the computed interactions are only between them. In the meantime, to ensure continued support, we are displaying the site without styles EPJ Data Science 4, 3 (2015). These metrics were also linked to socio-economical data in order to estimate poverty levels in a region. We compare some locations that we expect to have markedly different behavioural signatures. arXiv preprint arXiv:1503.06152 (2015). Cellular network Clustering Decomposition Deep learning Machine learning Traffic prediction 1. Proceedings of CHI, 511520 (2014). This dataset contains data derived from an analysis of geolocalized tweets originated from Milan during the months of November and December.Each row corresponds to a tweet. The almost universal adoption of mobile phones and the exponential increase in the use of Internet services is generating an enormous amount of data that can be used to provide new fundamental and quantitative insights on socio-technical systems. 6. Square id: identification string of a given square of the Trentino GRID; Line id: identification string of the distribution power line, which is grouped with the Trentino GRID square; Number of customer sites: number of customer sites present in a given square of the Trentino GRID, connected to the grid powerline (Line id). To ensure the privacy of SET's customers, their locations and the geometry of the 180 primary distribution lines is not explicitly exposed. Proceedings of WWW., 965968 (2012). Intuitively, the former provides the locations of the sensors and the unit of measurements, while the latter contains the measurement files for each sensor. The output is written in the same directory where the script resides. Nature comm. Google Scholar. The SMSs are sent from the nation identified by the Country code; SMS-out activity: activity proportional to the amount of sent SMSs inside a given Square id during a given Time interval. Hawelka, B. et al. The reason is that our goal is to give researchers the possibility both to extract known metrics and to design new ones. Telecom Italia announces the Big Data Challenge: the first contest in Italy to stimulate the creation and development of innovative technological ideas from Big Data with the release of one of the largest heterogeneous Big Data set. Dynamic population mapping using mobile phone data. How to cite this article: Barlacchi, G. et al. As depicted in the mobile phone usage plot (see Fig. Telecom Italia's "Big Data Challenge" was an online call for developers, researchers and designers from all over the world to come up with new big data services and applications. 2). It covers an area of more than 6,000km2, with a total population of about 0.5 million. Hence, in this section we propose a statistical and visual characterization with the aim of supporting the naive correctness of the information provided. The data of the Italian Administrative Regions are provided from ISTAT and were updated in 2011. acheneID: unique identification string of Dandelion; level: the level of this administrative region which can be. These data was used during the Big Data Challenge 2014, an online call for developers, researchers and designers from all over the world to come up with brand-new big data services and applications. The stream was gathered through the Twitter Streaming API (https://dev.twitter.com/docs/streaming-apis) which is a free service allowing the extraction of ~1% of the total Twitter feed through a set of filterers provided by the user. Square id: identification string of a given square of Milan/Trentino GRID; Time Interval: start interval time expressed in milliseconds. The contest involved the participation of 1,100+ participants (652 teams and 105 universities) from all over the world. Because the 10 min interval dataset was quite sparse, it was not conducive to extracting spatiotemporal characteristics. This dataset [Data citations 8,9] provides the directional interaction strengths between different areas of Milan and the Province of Trento. EPJ Data Science 4, 4 (2015). Telecom Italia dataset elds. The lender . G.T. Dataset with 6 projects 1 file 1 table. It can also be useful to visualize the data and the distribution of the events inside the geographical areas. Google Scholar. In Pervasive computing 6696, 133151 (2011). The first number is proportional to the number of calls issued from the area B to the province A, the second one is proportional to the number of calls from the province A to the area B.the spatial aggregation is the Trentino GRID squares and the Italian provinces.the temporeal aggregation values are in timeslots of ten minutes. Telecom Italia's board of directors has agreed to the spin-off of its 23 data centers into a separate business. data integration objective observation design, surface layer precipitation Media electrical energy consumption administrative region Telecommunications, weather stations Internet Electronic Communication network analysis Geographic Information System Telecommunication Device, Milan Trentino-South Tyrol anthropogenic habitat, Machine-accessible metadata file describing the reported data (ISA-Tab format). This is spatiotemporal data because it contains both spatial and temporal aspects of subscribers and networks. ADS This work is licensed under a Creative Commons Attribution 4.0 International License. & Capra, L. Poverty on the cheap. Sign up for the Nature Briefing newsletter what matters in science, free to your inbox daily. Unfortunately the availability of communications and social media data is usually restricted to a few research teams that sign non-disclosure agreements (NDAs) and research contracts with telecommunication and other private companies. Two types of CDR datasets were also produced to measure the interaction intensity between different locations: one from a particular area (Trentino/Milan) to any of the Italian provinces and one quantifying the interactions within the city/province (e.g., Milan to Milan). Google Scholar. Similarly, Twitter data (see Fig. converter.py It converts the raw CDRs to the grid overlay as explained previously. This allows the researcher to observe the relative and absolute temporal distribution of the events. Scientific reports 4 (2014). master 1 branch 0 tags Go to file Code dwhitena Update README.md 398c34c on Apr 15, 2015 3 commits README.md Update README.md 8 years ago call_in_mgrid.png Initial Commit arXiv preprint arXiv: 1407.4885 (2014). The current flowing through the distribution lines has been recorded every 10 minutes. ISSN 2052-4463 (online). Then, a new CDR is created recording the time of the interaction and the RBS which handled it. Each sensor has a unique ID, a type and a location. The goal of this challenge was to come up with technological ideas related to big data that in return. The lack of open datasets limits the number of potential studies and creates issues in the process of validation and reproducibility needed by the scientific community. We would like to show you a description here but the site won't allow us. In Computational Approaches for Urban Environments 13, 363387 (2015). The SMSs are received in the nation identified by the Country code; Call-in activity: activity proportional to the amount of received calls inside the Square id during a given Time interval. As expected, Navigli is characterized by an increase in Internet connections during the evening, while Bocconi's connections drop off during the weekends. Smith-Clarke, C., Mashhadi, A. ADS PLoS ONE 9, 6 (2014). From Figs 5 and 6 it is possible to observe a strong daily seasonality which usually starts at 7:00, when people turn on their phones and probably commute to work and then slowly decreases in the evening when people return home and sleep. Time Interval: Start interval time expressed in milliseconds. Proceedings of the 9th Python in Science Conference 445, 5156 (2010). Different types of software and tools were used in the dataset generation process and it would have been too complicated to share and explain all the used source code used. Moreover, there is also a weekly seasonality due to the work cycles behaviour of people (e.g., working days versus weekends). The obfuscation of the username has been done using the hash function SHA-1, and two random generated strings (SALT1 and SALT2): The dataTXT is a tool to identify meaningful sequences of one or more terms, and then to link them to the most appropriate Wikipedia page. For the latter, each task is performed for predicting service-specific traffic data based on a fully connected network. These datasets are now freely available for anyone to use. F.A. The data are released on 7 Italian cities: Bari, Milan, Naples, Rome, Turin, Venice and Palermo. Google Scholar. This datatset is available both for Trentino province and city of Milan. Not always available. Journal of Machine Learning Research 12, 28252830 (2011). Thus, the area of Milan is composed of a grid overlay of 1,000 (squares with size of about 235235meters and Trentino is composed of a grid overlay of 6,575 squares (see Fig. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. There is no spatial aggregation and the data are aggregated in timeslots of 15min. Cite this article. All articles published by the on-line newspaper Milano Today and Trento Today from 01/11/2013 and 31/12/2013 are contained in this dataset [Data citations 17,18]. MATH This helps researchers to observe and understand the spatial distribution of the various datasets. From the Telecommunications interactions datasets (e.g., Milan to Milan), it is possible to create a virtual network of an area that describes a who-calls-whom network. This dataset provides information regarding the level of interaction between the areas of the city of Milan and the Italian provinces. The Trentino Grid is provided in GeoJSON format. & Krings, G. A survey of results on mobile phone datasets analysis. The data are accessible from the Harvard Dataverse repository but also from a public API provided by Dandelion (http://dandelion.eu) which is the original platform where the data were published for the Big Data Challenge. Geo-located twitter as proxy for global mobility patterns. Unfortunately, since it was not possible to share the input (raw) files, this code can not be executed to perfectly reproduce the datasets. In the 2014 edition they provided data of two Italian areas: the city of Milan and the Province of Trentino. However, this information is summarized in the Customer site dataset where for each square grid the number of customer sites is recorded along with the information about the power line they are connected to. A plain language summary of the ODbL is available on the Open Data Commons website. Weekly spatial behaviour of the six selected areas in Milan and Trentino. Journal of The Royal Society Interface 11, 20130789 (2014). Article The unique multi-source composition of the dataset makes it an ideal testbed for methodologies and approaches aimed at tackling a wide range of problems including energy consumption, mobility planning, tourist and migrant flows, urban structures and interactions, event detection, urban well-being and many others. Flexible Data Ingestion. The dataset describes precipitation intensity over the province of Trento.the spatial aggregation is the Trentino GRID squares.The temporal values are provided every ten minutes. It uses around 180 primary distribution lines (medium voltage lines) to bring energy from the national grid to Trentino's consumers. Gonzalez, M., Hidalgo, C. & Barabasi, A. 4 SETlayers. Identifying important places in peoples lives from cellular network data. arXiv preprint arXiv:1210.0137 (2012). The contest made available to developers, designers and scientists a large dataset of 30+ kinds of data (mobile, weather, energy, etc.) to share: to copy, distribute and use the database; to create: to produce works from the database; to adapt: to modify, transform and build upon the database. de Montjoye, Y., Smoreda, Z., Trinquart, R., Ziemlicki, C. & Blondel, V. D4d-senegal: The second mobile phone data for development challenge. At the beginning of 2014, Telecom Italia, in collaboration with several international partners, launched the Telecom Italia Big Data Challenge. It is a rich, open multi-source aggregation of telecommunications, weather, news, social networks and electricity data. (t) follows the rule: where k is a constant defined by Telecom Italia, which hides the true number of calls, SMS and connections. Many of them are repeated on a daily basis (e.g., eating at noon, jogging in the evening etc. The data are split into two datasets called Legend dataset and Weather Phenomena. 24)and 20142015 (ref. The private equity firm is debating whether it may need to eventually increase its offer to around 70 . Quantifying the impact of human mobility on malaria. 5) and the Boxplots shown in Fig. The data of Milan [Data citation 12] are split into two datasets called Legend dataset and Weather Phenomena. Introduction Cellular network is an important communication network, which provides call, message, and data services to the end users in the range covered by the base stations. https://doi.org/10.1038/sdata.2015.55, DOI: https://doi.org/10.1038/sdata.2015.55. Louail, T. et al. There is no spatial aggregation and the data is aggregated in 60min time-slots. SET manages almost the entire electrical network over the Trentino territory. The Telecommunications and Social pulse data make it possible to identify the hotspots of the city, defined as areas with high activity density with respect to the rest of the city. By. Similarly, this happened for the New Year eve in all areas of Milan and Trentino. Telecom Italia received late last year a preliminary bid of 50.5 euro cents a share from KKR. The images or other third party material in this article are included in the articles Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. 156 Recommendations 0 Learn more about stats on ResearchGate Abstract In this work, we are interested in the applications of big data in the telecommunication domain, analysing two weeks of. In order to get a first grasp of the geographical location of the grids, we suggest importing them into the free software QGIS, adding an OpenStreetMap layer as well. The Telecommunication datasets provide data about the telecommunication activity in the city of Milan and in the Province of Trentino. Some of the datasets referring to the Trentino territory are spatially aggregated using a grid. The data of Milan are collected by Agenzia Regionale per la Protezione dell'Ambiente (ARPA) (http://www2.arpalombardia.it/siti/arpalombardia/meteo/richiesta-dati-misurati/Pagine/RichiestaDatiMisurati.aspx) while Trentino's data are collected by Meteotrentino (http://www.meteotrentino.it). The technical quality validation of the datasets is limited due to the absence of similar datasets to compare our results with. The various grid systems employed in this project. This is achieved by treating the traffic volume data as a tensor, similar to an image, which is then fed to a convolutional neural network. Telecom Italia made a dataset of its own mobile phone data (millions of anonymized and geo-referenced records of calls from Milan and . 25). Kung, K., Greco, K., Sobolevsky, S. & Ratti, C. Exploring universal patterns in human home-work commuting from mobile phone data. This includes data collected from November to December 2013 for Milan and Trento. It uses around 180 primary distribution lines (medium voltage lines) to bring energy from the national grid and distribute it among Trentino users. The last set contains all the information about civic numbers and maps used in the census of 2011. Recently, the dataset used for the contest was made open to the public via their website. There are many types of CDRs and Telecom Italia has recorded the following activities: Received SMS a CDR is generated each time a user receives an SMS, Sent SMS a CDR is generated each time a user sends an SMS, Incoming Call a CDR is generated each time a user receives a call, Outgoing Call a CDR is generated each time a user issues a call.
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