Cm-Rwl1-O15S16 Daily Refugee Arrivals And Weather Data, Italy/Central Med., Oct.2015 - Sept.2016

======================================================== <strong>Dataset: CM-RWL1-O15S16</strong> <strong> Daily refugee arrivals and weather data<br> Italy/Central Med., Oct.2015 - Sept.2016</strong><br> <br> Release Notes Copyright (c) 2018 by Harris V. Georgiou ========================================================<br> Release: Apr 14, 2018 - Version: 1.1a<br> - Format: .xlsx/.csv/.txt<br> ======================================================== <br> This file contains important information about the<br> current version of the dataset package. Downloading and using this material hints that you<br> accept the EULA/Terms-of-Use (please read carefully). We welcome your comments and suggestions. _______________________________________________<br> WHAT'S IN THIS PACKAGE? - Overview<br> - Available file formats<br> - Files and Datasets<br> - License Agreement _______________________________________________<br> OVERVIEW Since early January 2015, Europe has witnessed an unprecedented influx of refugees<br> from regions of war and conflict in the Middle East, primarily Syria, Afghanistan<br> and Iraq. The rapid allocation of proper resources is the most critical factor in<br> the success or failure of any rescue and relief operations, especially in the "hot"<br> zones. In order to do so, proper tools of predictive analytics mus be available,<br> specifically for forecasting the intensity and, if possible, the location of the<br> next refugee influx waves, so that the rescue elements and the logistical support<br> is properly prepared beforehand. This package contains a set of data regarding daily refugee arrivals at the general<br> area of the Central Mediterranean Sea, more specifically towards Italy, for the most<br> intense period of influx waves, from the beginning of October 2015 until the end of<br> September 2016 (one full year). The sources of the data are:<br> 1) For daily arrivals (Italy):<br> UNHCR Refugees/Migrants Emergency Response (Data mashups)<br> http://data2.unhcr.org/en/situations/mediterranean/location/5205<br> 2) For weather:<br> Weather Underground Database (mashup of NOAA, aviation, local)<br> https://www.wunderground.com/about/data The datasets from (1) have already been used in various publications describing<br> such predictive analytics models. Detailed description and related conclusions<br> can be found at: * Harris V. Georgiou, "Identification of refugee influx patterns in Greece via<br> model-theoretic analysis of daily arrivals" (9-May-2016),<br> https://arxiv.org/abs/1605.02784 _______________________________________________<br> AVAILABLE FILE FORMATS The datasets are available in the following formats (included): *.xlsx : MS-Excel/LibreOffice native spreadsheets<br> *.csv : comma-separated plaintext spreadsheets<br> *.txt : raw plaintext files with full column headers These data formats are equivalent, i.e., they contain the exact same<br> sets of data. Normally, at least one of them should be compatible<br> with any major programming platform (e.g. Matlab, Octave, R) or any<br> native programming language for arbitrary handling (e.g. C, Java). _______________________________________________<br> FILES AND DATASETS Root folder: CM-RWL1-O15S16\ Dataset 1: Arrivals\(csv,xlsx)<br> "Italy-DailyArrivals-Oct2015Sept2016.*"<br> : Complete data series for refugee influx arrivals for Italy Dataset 2: Weather\(xlsx,txt)<br> Habib Bourguiba, Tunisia<br> Sfax El-Maou, Tunisia<br> Lampedusa, Italy<br> Luqa, Malta<br> Tripoli Mitiga, Libya<br> : Weather data (temp,wind,gust,w.dir,...) at local airports The Mitiga airport station at Tripoli, Libya, is the most critical regarding<br> the construction of analytics and predictive modeling of the daily influx series<br> towards Italy. However, due to adverse conditions and lack of maintenance,<br> there are several blocks of consecutive days with missing weather data. Thus,<br> the other four reliable weather stations in the area should be used to build<br> regression models for filling-in these gaps. The satellite map(*) in the \Suppl folder shows the situation of Search &amp; Rescue<br> (SAR) operations, density of shipwrecks by the end of Sept. 2015, as well as<br> the location of these weather stations and how these relate spatially to the<br> target area of Tripoli, which is still the departing spot with the highest<br> density of boats. (*) SAR map source: https://blamingtherescuers.org/report/ <br> _______________________________________________<br> LICENSE AGREEMENT This program was produced primarily for academic research and educational purposes.<br> Downloading and using this material implies acceptance of the Creative Commons<br> License: Attribution-NonCommercial-ShareAlike 4.0 International (BY-NC-SA), 2016.<br> * http://creativecommons.org/licenses/by-nc-sa/4.0/ Copyright (c) 2018 by Harris V. Georgiou (MSc,PhD) -- http://xgeorgio.info <br> --