scholarly journals MATCHING ALTERNATIVE ADDRESSES: A SEMANTIC WEB APPROACH

Author(s):  
S. Ariannamazi ◽  
F. Karimipour ◽  
F. Hakimpour

Rapid development of crowd-sourcing or volunteered geographic information (VGI) provides opportunities for authoritatives that deal with geospatial information. Heterogeneity of multiple data sources and inconsistency of data types is a key characteristics of VGI datasets. The expansion of cities resulted in the growing number of POIs in the OpenStreetMap, a well-known VGI source, which causes the datasets to outdate in short periods of time. These changes made to spatial and aspatial attributes of features such as names and addresses might cause confusion or ambiguity in the processes that require feature’s literal information like addressing and geocoding. VGI sources neither will conform specific vocabularies nor will remain in a specific schema for a long period of time. As a result, the integration of VGI sources is crucial and inevitable in order to avoid duplication and the waste of resources. Information integration can be used to match features and qualify different annotation alternatives for disambiguation. This study enhances the search capabilities of geospatial tools with applications able to understand user terminology to pursuit an efficient way for finding desired results. Semantic web is a capable tool for developing technologies that deal with lexical and numerical calculations and estimations. There are a vast amount of literal-spatial data representing the capability of linguistic information in knowledge modeling, but these resources need to be harmonized based on Semantic Web standards. The process of making addresses homogenous generates a helpful tool based on spatial data integration and lexical annotation matching and disambiguating.

2021 ◽  
Vol 251 ◽  
pp. 01030
Author(s):  
Qinqi Kang ◽  
Zhao Kang

With the rapid development of artificial intelligence in the current era of big data, the construction of translation corpus has become a key factor in effectively achieving a highly intelligent translation. In the era of big data, the data sources and data types of translation corpus are becoming more and more diversified, which will inevitably bring about a new revolution in the construction of translation corpus. The construction of the translation corpus in the era of big data can fully rely on third-party open source data, crowd-sourcing translation, machine closed-loop, human-machine collaboration and other multiple modes to comprehensively improve the quality of translation corpus construction to better serve translation practice.


2020 ◽  
Vol 2 ◽  
pp. 1-1
Author(s):  
Timothy Trainor

Abstract. The world is at a crossroads. The current global pandemic has had an impact on every person, their national and global economies, and their ability to preserve a sustainable environment. To understand the health impacts of such an intrusive consequence requires understanding of the pandemic’s cause, its spread among populations, preventive measures to contain its spread and plans for protecting people from future outbreaks. Each one of these factors requires specific types of data and each data point requires location to make it meaningful. This is complicated because of the extent of the challenges. It is further complicated by the lack of timely data, the required location precision, and concerns over policy issues like privacy. Maps, mapping, and cartographers are needed as part of the formula for finding solutions on each of these factors.The International Cartographic Association (ICA) is positioned to help in providing solutions. The structure of the ICA, through its various programs, is sufficiently flexible to respond to these critical issues in practical ways that yield useful results. As an example, new ICA Working Groups were recently established to focus on sustainability and bolstering national mapping and national geospatial organizations while a longer-term commitment centers on a revised research agenda to meet current and future cartographic and GIScience needs. These examples are in addition to other components of the ICA program including the ICA Commissions, conferences, and publications.As the pandemic is global, local to global solutions are needed. The ICA has been actively engaged with the United Nations through the UN Committee of Experts on Global Geospatial Information Management. Three UN initiatives, two of which are geospatial frameworks, call out to the cartographic community for their help. The first is the Sustainable Development Goals that began in 2015 with a 2030 target to focus on a better understanding of national populations, their economies and their environments. Measuring and monitoring progress requires data, processes, systems, leadership, and commitment to be effective. The second effort is the Integrated Geospatial Information Framework, the next rendition of National Spatial Data Infrastructures (NSDI), that focuses on nine Strategic Pathways that are needed to create and maintain a sustainable geospatial program. The third initiative responds to the statistical and geospatial communities working together to create the Global Statistical Geospatial Framework which focuses on the integration of these two linked data types.Cartographers can contribute in two areas. The first calls on their knowledge and expertise in working with different data types. For example, geospatially referenced statistical data oftentimes benefits from basic generalization principles such as combination, simplification, exaggeration and displacement. The absence of a small-area global geography sometimes inhibits the usefulness of statistical information which has become painfully evident during this pandemic. The second area that calls out to cartographers is to use their skills in making as many useful maps as possible. These maps need to show current local conditions, illuminate deficiencies, tell a story, and/or inform strategies and plans for addressing the many challenges we face between the pandemic and the underlying conditions of people, their communities, and circumstances oftentimes outside of their control.The presentation shows examples of some of these points and the ICA’s participation thus far. Opportunities for involvement are left to the imaginations of each of us. What is needed now is for cartographers and the cartographic community to act in ways that help in solving current challenges, informing some of the root causes and systemic problems that need attention while outlining approaches for a path forward in our ever increasingly complex world.


2019 ◽  
Vol 2 ◽  
pp. 1-5
Author(s):  
Deguo Su ◽  
Beibei Tan ◽  
Debao Yuan ◽  
Yong Wang ◽  
Jiping Liu

<p><strong>Abstract.</strong> With the rapid development of geographic information technology, the web-based 3D visualization technology is constantly updated with the development of computers. However, the traditional 3D geographic data visualization software based on the rich-client model it has significant limitations in the display and analysis of geospatial information and it is difficult to install and use, result in that difficult to meet the application of Geo-dynamic simulation, visual analysis, and collaborative decision-making of the geographic process. In order to show the realism of spatial data more directly, this paper introduces a 3D visualization process design method of geographic information and analyses the 3D data modelling building and visualization efficiency. The process combines multiple data sources are loaded automatically, cross platform, 2D &amp;amp; 3D integration, and make a wider range of customers easily access to the visualization effect of 3D spatial data.</p>


Author(s):  
Seán O’Riain ◽  
Andreas Harth ◽  
Edward Curry

With increased dependence on efficient use and inclusion of diverse corporate and Web based data sources for business information analysis, financial information providers will increasingly need agile information integration capabilities. Linked Data is a set of technologies and best practices that provide such a level of agility for information integration, access, and use. Current approaches struggle to cope with multiple data sources inclusion in near real-time, and have looked to Semantic Web technologies for assistance with infrastructure access, and dealing with multiple data formats and their vocabularies. This chapter discusses the challenges of financial data integration, provides the component architecture of Web enabled financial data integration and outlines the emergence of a financial ecosystem, based upon existing Web standards usage. Introductions to Semantic Web technologies are given, and the chapter supports this with insight and discussion gathered from multiple financial services use case implementations. Finally, best practice for integrating Web data based on the Linked Data principles and emergent areas are described.


Author(s):  
R. Arabsheibani ◽  
S. Ariannamazi ◽  
F. Hakimpour

The Web and its capabilities can be employed as a tool for data and information integration if comprehensive datasets and appropriate technologies and standards enable the web with interpretation and easy alignment of data and information. Semantic Web along with the spatial functionalities enable the web to deal with the huge amount of data and information. The present study investigate the advantages and limitations of the Spatial Semantic Web and compare its capabilities with relational models in order to build a spatial data infrastructure. An architecture is proposed and a set of criteria is defined for the efficiency evaluation. The result demonstrate that when using the data with special characteristics such as schema dynamicity, sparse data or available relations between the features, the spatial semantic web and graph databases with spatial operations are preferable.


Author(s):  
Janet Nackoney ◽  
Jena Hickey ◽  
David Williams ◽  
Charly Facheux ◽  
Takeshi Furuichi ◽  
...  

The endangered bonobo (Pan paniscus), endemic to the Democratic Republic of Congo (DRC), is threatened by hunting and habitat loss. Two recent wars and ongoing conflicts in the DRC greatly challenge conservation efforts. This chapter demonstrates how spatial data and maps are used for monitoring threats and prioritizing locations to safeguard bonobo habitat, including identifying areas of highest conservation value to bonobos and collaboratively mapping community-based natural resource management (CBNRM) zones for reducing deforestation in key corridor areas. We also highlight the development of a range-wide model that analysed a variety of biotic and abiotic variables in conjunction with bonobo nest data to map suitable habitat. Approximately 28 per cent of the range was predicted suitable; of that, about 27.5 per cent was located in official protected areas. These examples highlight the importance of employing spatial data and models to support the development of dynamic conservation strategies that will help strengthen bonobo protection. Le bonobo en voie de disparition (Pan paniscus), endémique à la République Démocratique du Congo (DRC), est menacé par la chasse et la perte de l’habitat. Deux guerres récentes et les conflits en cours dans le DRC menacent les efforts de conservation. Ici, nous montrons comment les données spatiales et les cartes sont utilisées pour surveiller les menaces et prioriser les espaces pour protéger l’habitat bonobo, inclut identifier les zones de plus haute valeur de conservation aux bonobos. En plus, la déforestation est réduite par une cartographie collaborative communale de gestion de ressources dans les zones de couloirs essentiels. Nous soulignons le développement d’un modèle de toute la gamme qui a analysé un variété de variables biotiques et abiotiques en conjonction avec les données de nid bonobo pour tracer la carte d’un habitat adéquat. Environ 28 per cent de la gamme est prédit adéquat; de cela, environ 27.5 per cent est dans une zone officiellement protégée. Ces exemples soulignent l’importance d’utiliser les données spatiales et les modèles pour soutenir le développement de stratégies de conservations dynamiques qui aideront à renforcer la protection des bonobos.


2016 ◽  
Vol 206 (1) ◽  
pp. 605-629 ◽  
Author(s):  
T. Bodin ◽  
J. Leiva ◽  
B. Romanowicz ◽  
V. Maupin ◽  
H. Yuan

2021 ◽  
pp. 026666692110484
Author(s):  
Asmat Ali ◽  
Muhammad Imran ◽  
Munazza Jabeen ◽  
Zahir Ali ◽  
Syed Amer Mahmood

Spatial data is one of the core components in all information retrieval processes for decision-making. Spatial data acquisition consumes enormous monetary resources and time. The Integrated Geospatial Information Framework (IGIF) provides a basis and guide for developing, integrating, strengthening, and maximizing geospatial information management and related resources in all countries. To this, governments all over the world are establishing national spatial data infrastructures (SDIs). However, such initiatives face a considerable amount of resistance as organizations often do not want to share their data assets. The present study investigates these barriers in the establishment of national SDI in Pakistan. The constraints studied through the IGIF pathways and past studies were adapted via a pilot study and conceptualized in a hypothesized model. We collected primary data via the administration of 520 questionnaire surveys to 280 public and private organizations. Partial least squares structural equation modeling (PLS-SEM) was applied to statistically confirm the conceptual model of the barriers to disseminating spatial data. The results indicate institutional barriers from the absence of national data policy, lack of specified roles of stakeholders, poor inter-organizational coordination, missing data-sharing policy, and weak organizational partnerships, with coefficients 0.26, 1.555, 1.305, 8.288, and 0.136, respectively, at the p < 0.001 significance level. The PLS-SEM R2 0.65 indicates a good explanatory power of the model. The methodology developed in the present study will allow devising more sustainable policies for spatial data management and dissemination in Pakistan and beyond.


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