Louai Alarabi, A. Eldawy, Rami Alghamdi, M. Mokbel
{"title":"TAREEG:一个基于mapreduce的系统,用于从OpenStreetMap中提取空间数据","authors":"Louai Alarabi, A. Eldawy, Rami Alghamdi, M. Mokbel","doi":"10.1145/2666310.2666403","DOIUrl":null,"url":null,"abstract":"Real spatial data, e.g., detailed road networks, rivers, buildings, parks, are not easily available for most of the world. This hinders the practicality of many research ideas that need a real spatial data for testing and experiments. Such data is often available for governmental use, or at major software companies, but it is prohibitively expensive to build or buy for academia or individual researchers. This paper presents TAREEG; a web-service that makes real spatial data, from anywhere in the world, available at the fingertips of every researcher or individual. TAREEG gets all its data by leveraging the richness of OpenStreetMap data set; the most comprehensive available spatial data of the world. Yet, it is still challenging to obtain OpenStreetMap data due to the size limitations, special data format, and the noisy nature of spatial data. TAREEG employs MapReduce-based techniques to make it efficient and easy to extract OpenStreetMap data in a standard form with minimal effort. Experimental results show that TAREEG is highly accurate and efficient.","PeriodicalId":153031,"journal":{"name":"Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"163 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"TAREEG: a MapReduce-based system for extracting spatial data from OpenStreetMap\",\"authors\":\"Louai Alarabi, A. Eldawy, Rami Alghamdi, M. Mokbel\",\"doi\":\"10.1145/2666310.2666403\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Real spatial data, e.g., detailed road networks, rivers, buildings, parks, are not easily available for most of the world. This hinders the practicality of many research ideas that need a real spatial data for testing and experiments. Such data is often available for governmental use, or at major software companies, but it is prohibitively expensive to build or buy for academia or individual researchers. This paper presents TAREEG; a web-service that makes real spatial data, from anywhere in the world, available at the fingertips of every researcher or individual. TAREEG gets all its data by leveraging the richness of OpenStreetMap data set; the most comprehensive available spatial data of the world. Yet, it is still challenging to obtain OpenStreetMap data due to the size limitations, special data format, and the noisy nature of spatial data. TAREEG employs MapReduce-based techniques to make it efficient and easy to extract OpenStreetMap data in a standard form with minimal effort. Experimental results show that TAREEG is highly accurate and efficient.\",\"PeriodicalId\":153031,\"journal\":{\"name\":\"Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems\",\"volume\":\"163 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2666310.2666403\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2666310.2666403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
TAREEG: a MapReduce-based system for extracting spatial data from OpenStreetMap
Real spatial data, e.g., detailed road networks, rivers, buildings, parks, are not easily available for most of the world. This hinders the practicality of many research ideas that need a real spatial data for testing and experiments. Such data is often available for governmental use, or at major software companies, but it is prohibitively expensive to build or buy for academia or individual researchers. This paper presents TAREEG; a web-service that makes real spatial data, from anywhere in the world, available at the fingertips of every researcher or individual. TAREEG gets all its data by leveraging the richness of OpenStreetMap data set; the most comprehensive available spatial data of the world. Yet, it is still challenging to obtain OpenStreetMap data due to the size limitations, special data format, and the noisy nature of spatial data. TAREEG employs MapReduce-based techniques to make it efficient and easy to extract OpenStreetMap data in a standard form with minimal effort. Experimental results show that TAREEG is highly accurate and efficient.