scholarly journals An Approach Based on Customized Robust Cloaked Region for Geographic Location Information Privacy Protection

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Zhidong Shen ◽  
Siyuan Lu ◽  
Huijuan Huang ◽  
Meng Yuan ◽  
Guoming Tang ◽  
...  
Keyword(s):  
Information Science ◽  
Geographical Location ◽  
Geographic Location ◽  
Location Based Services ◽  
Geographical Information ◽  
Privacy Concerns ◽  
Degree Of Protection ◽  
Fast Development ◽  
Semantic Value ◽  
User Density

Location-based services (LBS) have gained huge popularity because of the easy availability of modern mobile devices and the fast development of geographical information science (GIS). However, the lack of protection for private user positions might give rise to privacy concerns. This kind of problem is especially serious in mobile application environment because many mobile applications tend to use LBS. In this paper, we propose a new privacy preserving approach using customized robust cloaked region (RCR), depending on a peer-to-peer structure and the premise that users do not trust each other when sharing their geographical locations. Two algorithms are used to generate the RCR with high user density. The area of the RCR is controlled by the user’s demanded degree of protection. To enhance the resistance to regional background knowledge attack, we incorporate a location semantic value into each unit of the user map. According to extensive simulations, our method can effectively obfuscate a user’s geographical location into a highly indistinguishable region because of the disturbance of nearby users and different equally possible locations.

scholarly journals OPPORTUNITIES AND CHALLENGES FOR AUGMENTED REALITY SITUATED GEOGRAPHICAL VISUALIZATION

2020 ◽  
Vol V-4-2020 ◽  
pp. 163-170
Author(s):  
M. J. Lobo ◽  
S. Christophe
Keyword(s):  
Augmented Reality ◽  
Human Computer Interaction ◽  
Information Science ◽  
Geographical Location ◽  
Geographical Information ◽  
Geographical Distance ◽  
Geographic Locations ◽  
Computer Interaction

Abstract. Augmented reality (AR) enables to display situated geographical visualizations, i.e visualizations that use virtual elements that are displayed in a geographical location. The place where the data is displayed complements the visualization. Many applications that take advantage of AR and situated visualizations exist, but they differ in the visualizations they present, their relationship to the geographic locations and goals. To better understand why and how AR based situated geovisualization is used, we review 45 papers coming from Human Computer Interaction, Visualization and Geographical Information Science venues that present such applications. Inspired by existing classifications, we characterize these papers according to the data they visualize and the geographical distance between the visualization and the data the visualization represents. This analysis reveals existing opportunities for situated geovisualization applications using AR.

scholarly journals Semantics of Voids within Data: Ignorance-Aware Machine Learning

2021 ◽  
Vol 10 (4) ◽  
pp. 246
Author(s):  
Vagan Terziyan ◽  
Anton Nikulin
Keyword(s):  
Spatial Data ◽  
Information Science ◽  
Nearest Neighbor ◽  
Geographical Information ◽  
Two Dimensional ◽  
Prototype Selection ◽  
Data Space ◽  
Important Concern ◽  
Traditional Classification ◽  
Nearest Neighbor Classifiers

Operating with ignorance is an important concern of geographical information science when the objective is to discover knowledge from the imperfect spatial data. Data mining (driven by knowledge discovery tools) is about processing available (observed, known, and understood) samples of data aiming to build a model (e.g., a classifier) to handle data samples that are not yet observed, known, or understood. These tools traditionally take semantically labeled samples of the available data (known facts) as an input for learning. We want to challenge the indispensability of this approach, and we suggest considering the things the other way around. What if the task would be as follows: how to build a model based on the semantics of our ignorance, i.e., by processing the shape of “voids” within the available data space? Can we improve traditional classification by also modeling the ignorance? In this paper, we provide some algorithms for the discovery and visualization of the ignorance zones in two-dimensional data spaces and design two ignorance-aware smart prototype selection techniques (incremental and adversarial) to improve the performance of the nearest neighbor classifiers. We present experiments with artificial and real datasets to test the concept of the usefulness of ignorance semantics discovery.

scholarly journals A Geospatial database of gastric cancer patients and associated potential risk factors including lifestyle and air pollution

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Fatemeh Hashemi Amin ◽  
Mahtab Ghaemi ◽  
Sayyed Mostafa Mostafavi ◽  
Ladan Goshayeshi ◽  
Khadijeh Rezaei ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gastric Cancer ◽  
Cancer Patients ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
Dietary Habits ◽  
Age Groups ◽  
Geographical Location ◽  
Geographical Information ◽  
Point Feature

Abstract Objectives Gastric cancer (GC) is a multifactorial disease and the fifth most frequent diagnosed cancer worldwide. It accounts for one third of cancer-related mortalities. Geospatial analysis using geographical information systems (GIS) can provide an efficient solution to identify spatial disparities associated with GC. As such, GIS enables policymakers to control cancer in a better way and identify the regions where interventions are needed. This study aims to publish a comprehensive dataset, which was applied to conduct a spatial analysis of GC patients in the city of Mashhad, Iran. Data description We provide a personal geodatabase, a Microsoft Access database that can store, query, and manage both spatial and non-spatial data, which contains four feature classes. “Male_Stomach_Cancer_Patients” and “Female_Stomach_Cancer_Patients” are point feature classes, which show the age and geographical location of 1156 GC cancer patients diagnosed between 2014 and 2017. “Air_Polution_Mashhad” is another point feature class that reveals the amount of six air pollutants, which was taken from Mashhad Environmental Pollutants Monitoring Center between 2017 and 2018. Finally, “Stomach_Cancer_and_Risk_Factors” is a polygon feature class of neighborhood division of Mashhad, consisting of contributor risk factors including dietary habits, smoking, alcohol use, body mass index and population by age groups for all 165 city neighborhoods.

scholarly journals Privacy vs. Reward in Indoor Location-Based Services

2016 ◽  
Vol 2016 (4) ◽  
pp. 102-122 ◽  
Author(s):  
Kassem Fawaz ◽  
Kyu-Han Kim ◽  
Kang G. Shin
Keyword(s):  
Location Privacy ◽  
Indoor Localization ◽  
Service Providers ◽  
Location Based Services ◽  
Location Information ◽  
Privacy Concerns ◽  
Indoor Location ◽  
Location Data ◽  
Personalized Services ◽  
Privacy Risks

AbstractWith the advance of indoor localization technology, indoor location-based services (ILBS) are gaining popularity. They, however, accompany privacy concerns. ILBS providers track the users’ mobility to learn more about their behavior, and then provide them with improved and personalized services. Our survey of 200 individuals highlighted their concerns about this tracking for potential leakage of their personal/private traits, but also showed their willingness to accept reduced tracking for improved service. In this paper, we propose PR-LBS (Privacy vs. Reward for Location-Based Service), a system that addresses these seemingly conflicting requirements by balancing the users’ privacy concerns and the benefits of sharing location information in indoor location tracking environments. PR-LBS relies on a novel location-privacy criterion to quantify the privacy risks pertaining to sharing indoor location information. It also employs a repeated play model to ensure that the received service is proportionate to the privacy risk. We implement and evaluate PR-LBS extensively with various real-world user mobility traces. Results show that PR-LBS has low overhead, protects the users’ privacy, and makes a good tradeoff between the quality of service for the users and the utility of shared location data for service providers.

Geographical Information Science and Maps

Cartography ◽  
2020 ◽  
pp. 1-21
Author(s):  
Menno-Jan Kraak ◽  
Ferjan Ormeling
Keyword(s):  
Information Science ◽  
Geographical Information

scholarly journals EXPRESSION AND ORGANIZATION OF GEOGRAPHIC SPATIAL RELATIONS BASED ON TOPIC MAPS

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1257-1261
Author(s):  
H. J. Liang ◽  
H. Wang ◽  
T. J. Cui ◽  
J. F. Guo
Keyword(s):  
Information Science ◽  
Spatial Database ◽  
Spatial Relation ◽  
Spatial Relations ◽  
Geographical Information ◽  
Knowledge Network ◽  
Effective Management ◽  
Topic Maps ◽  
Complex Knowledge ◽  
Topic Map

Spatial Relation is one of the important components of Geographical Information Science and Spatial Database. There have been lots of researches on Spatial Relation and many different spatial relations have been proposed. The relationships among these spatial relations such as hierarchy and so on are complex and this brings some difficulties to the applications and teaching of these spatial relations. This paper summaries some common spatial relations, extracts the topic types, association types, resource types of these spatial relations using the technology of Topic Maps, and builds many different relationships among these spatial relations. Finally, this paper utilizes Java and Ontopia to build a topic map among these common spatial relations, forms a complex knowledge network of spatial relations, and realizes the effective management and retrieval of spatial relations.

scholarly journals SISTEM INFORMASI GEOGRAFIS WILAYAH RAWAN BANJIR DI KOTA PEKANBARU

2019 ◽  
Vol 4 (2) ◽  
pp. 109-119
Author(s):  
Luluk Elvitaria Elvitaria ◽  
Miftahul Khasani
Keyword(s):  
Geographical Information Systems ◽  
Geographical Location ◽  
Geographical Information ◽  
Daily Activities ◽  
Flood Events ◽  
Rain Intensity ◽  
The City ◽  
Term Rain ◽  
Flood Prone Areas

Based on the geographical location of Pekanbaru City is one of the areas included in flood-prone areas, even said that the city of Pekanbaru is included in the red zone related to flooding, seeing from the majority of the existing area is the rawah and river banks. The National Flood Mitigation Agency (BNPB) noted that the city of Pekanbaru is one of the flood-prone cities on the island of Sumatra. In addition to determining flood-prone areas for the Regional BPBD Office in Pekanbaru City, the community also wants to know the location that often floods and determine the long-term rain intensity capacity that will cause flooding, so that it does not hinder the daily activities. To deal with this problem, a Geographical Information System needs to be developed that can determine areas that often occur in natural flooding. Geographical information systems are expected to be able to assist the BPBD Office in managing flood data that has occurred in the city of Pekanbaru, and help provide information about floods that are needed by the community to anticipate further flood events.  

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