On the Representativeness of OpenStreetMap for the Evaluation of Country Tourism Competitiveness

被引:7
作者
Bustamante, Alexander [1 ,2 ]
Sebastia, Laura [1 ]
Onaindia, Eva [1 ]
机构
[1] Univ Politecn Valencia, Valencia Res Inst Artificial Intelligence VRAIN, Valencia 46022, Spain
[2] Univ Magdalena, Fac Ingn, Santa Marta 470001, Colombia
关键词
collaborative data; open data analysis; tourism competitiveness; tourism statistics; SOCIAL MEDIA; BIG DATA; INFORMATION;
D O I
10.3390/ijgi10050301
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Since 2007, the World Economic Forum (WEF) has issued data on the factors and policies that contribute to the development of tourism and competitiveness across countries worldwide. While WEF compiles the yearly report out of data from governmental and private stakeholders, we seek to analyze the representativeness of the open and collaborative platform OpenStreetMap (OSM) to the international tourism scene. For this study, we selected eight parameters indicative of the tourism development of each country, such as the number of beds or cultural sites, and we extracted the OSM objects representative of these indicators. Then, we performed a statistical and regression analysis of the OSM data to compare and model the data emitted by WEF with data from OSM. Our aim is to analyze the tourist representativeness of the OSM data with respect to official reports to better understand when OSM data can be used to complement the official information and, in some cases, when official information is scarce or non-existent, to assess whether the OSM information can be a substitute. Results show that OSM data provide a fairly accurate picture of official tourism statistics for most variables. We also discuss the reasons why OSM data is not so representative for some variables in some specific countries. All in all, this work represents a step towards the exploitation of open and collaborative data for tourism.
引用
收藏
页数:22
相关论文
共 38 条
[1]   Analyzing the Tagging Quality of the Spanish OpenStreetMap [J].
Almendros-Jimenez, Jesus M. ;
Becerra-Teron, Antonio .
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2018, 7 (08)
[2]  
Anderson, 2016, OPENSTREETMAP CONTRI
[3]  
Arsanjani JJ, 2015, LECT NOTES GEOINF CA, P37, DOI 10.1007/978-3-319-14280-7_3
[4]   Is OpenStreetMap a good source of information for cultural statistics? The case of Italian museums [J].
Balducci, Francesco .
ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE, 2021, 48 (03) :503-520
[5]   The world's user-generated road map is more than 80% complete [J].
Barrington-Leigh, Christopher ;
Millard-Ball, Adam .
PLOS ONE, 2017, 12 (08)
[6]   Analysing spatiotemporal patterns of tourism in Europe at high-resolution with conventional and big data sources [J].
Batista e Silva, Filipe ;
Herrera, Mario Alberto Marin ;
Rosina, Konstantin ;
Barranco, Ricardo Ribeiro ;
Freire, Sergio ;
Schiavina, Marcello .
TOURISM MANAGEMENT, 2018, 68 :101-115
[7]  
Bustamante A, 2019, EDUCATION EXCELLENCE AND INNOVATION MANAGEMENT THROUGH VISION 2020, P4161
[8]   Can Tourist Attractions Boost Other Activities Around? A Data Analysis through Social Networks [J].
Bustamante, Alexander ;
Sebastia, Laura ;
Onaindia, Eva .
SENSORS, 2019, 19 (11)
[9]  
Chareyron Gael, 2014, 2014 IEEE International Conference on Big Data (Big Data), P5, DOI 10.1109/BigData.2014.7004475
[10]   Mapping Cilento: Using geotagged social media data to characterize tourist flows in southern Italy [J].
Chua, Alvin ;
Servillo, Loris ;
Marcheggiani, Ernesto ;
Moere, Andrew Vande .
TOURISM MANAGEMENT, 2016, 57 :295-310