• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.6
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• pp.567-580
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• 2016

In recent years, our society, because of the arrival of a new paradigm according to the rapid changes in ICT has entered into future smart society and the ubiquitous era. So it can be a notable turning point in the marine disaster prevention system with big data, aspects of the era change. Therefore, this study was to derive a desirable vision for the big data marine disaster prevention informatization in terms of ICT maritime disaster prevention system development as preparedness for the maritime disaster by applying 'scenario planning' as a foresight method. Soon this study derived a successful marine disaster prevention informatization strategy as preparedness for the maritime disaster like Ferry Sewol Disaster. It proposed the big data marine disaster prevention informatization system with the use of the administrative aspects of information with spatial informatization as big data information. Also this study explored the future leadership strategy of the big data marine disaster prevention informatization in smart society. Eventually in 2030 to around, In order to still remain our marine disaster prevention informatization as a leading ICT nation, this study suggested the following strategy. It is important to ready the advanced Big Data administrative spatial informatization system In terms of prevention of incidents like Ferry Sewol Disaster.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.100-112
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• 2021

With the recent growth of the big data technology market, interest in visualization technology has steadily increased over the past few years. Data visualization is currently used in a wide range of disciplines such as information science, computer science, human-computer interaction, statistics, data mining, cartography, and journalism, each with a slightly different meaning. Big data visualization in smart cities that require multidisciplinary research enables an objective and scientific approach to developing user-centered smart city services and related policies. In particular, spatial-based data visualization enables efficient collaboration of various stakeholders through visualization data in the process of establishing city policy. In this paper, a user-centered spatial big data visualization expression request method was derived by examining the spatial-based big data visualization expression process and principle from the viewpoint of effective information delivery, not just a visualization tool.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.9
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• pp.827-840
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• 2016

In recent years, our society, because of the arrival of a new paradigm according to the rapid changes in ICT has entered into future smart society and the ubiquitous era. So it can be a notable turning point in the city disaster prevention system with big data, aspects of the era change. Therefore, this study was to derive a desirable vision for the big data city disaster prevention informatization in terms of ICT city disaster prevention system development as preparedness for the city disaster by applying 'scenario planning' as a foresight method. Soon this study derived a successful city disaster prevention informatization strategy as preparedness for the city disaster, for example, in terms of water pollution and disaster prevention of Busan Ecodeltacity. It proposed the big data city disaster prevention informatization system with the use of the administrative aspects of information with spatial informatization as big data information. Also this study explored the future leadership strategy of the big data city disaster prevention informatization in smart society and smart eco-city. Eventually in 2030 to around, in order to still remain our city disaster prevention informatization as a leading ICT nation, this study suggested the following strategy. It is important to ready the advanced ubiquitous administrative spatial informatization and ICT disaster prevention system with big data in terms of water pollution and disaster prevention of Busan Ecodeltacity.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.269-281
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• 2016

The process of spatial big data, such as social media, is being paid more attention in the field of spatial information in recent years. This study, as an example of spatial big data analysis, analyzed the spatial and temporal distribution of Tweet data based on the location and time information. In addition, the characteristics of its spatial pattern by times were identified. Tweet data in Busan city are collected, processed, and analyzed to identify the characteristics of the temporal and spatial pattern. Then, the results of Tweet data analysis were compared with the characteristics of the land type. This study found that spatial pattern of tweeting in the city was associated with given time periods such as daytime and nighttime in both weekdays and weekends. The spatial distribution patterns of individual time periods were compared with the characteristics of the land for the spatially concentrated area. The results of this study showed that tweeted data would be related to different spatial distribution depending on the time, which potentially reflects the daily pattern and characteristics of the land type of urban area to some extent. This study presented the possible incorporation of social media data, e. g. Tweet data, into the field of spatial information. It is expected that there will be more advantage to use a variety of social media data in areas such as land planning and urban planning.

• Journal of Cadastre & Land InformatiX
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• v.45 no.1
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• pp.169-179
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• 2015

Recently, as the amount of data increases rapidly, the development of IT technology entered the 'Big Data' era, dealing with large-volume of data at once. In the spatial field, a spatial data service technology is required to use that various and big amount of data. In this study, firstly, we explained the technology of typical spatial information data services abroad, and then we have developed large KML data processing techniques those can be applied as KML format to VWorld desktop. The test was conducted using a large KML data in order to verify the development KML partitioned methods and tools. As a result, the index file and the divided files are produced and it was visible in VWorld desktop.

• Spatial Information Research
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• v.22 no.5
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• pp.43-52
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• 2014

Recently, Big Data is a buzzword in the creative economy generation. The organizations related to spatial information society focus on building the spatial big data systems. As spatial big data is a combination of spatial information and big data, the data visualization is essential in order to utilize them efficiently. One of the great methodologies for data visualization is infographics. Nationally, Chousn.com initiated the infographics news in 2010. Korean Administration Branches also recognized the importance of infographic and they adopted infographics for their briefings from 2013. Internationally, Visual.ly is leading company in the infographics market and they produced noticeable interactive infographics for Egypt Parliamentary Elections results. In the defense part, Guardian's datajournalism of Afghanistan war log was a good example of utilizing infographics. Throughout the research, five requirements are extracted. First source data should have precision and accuracy in terms of time and space manner. Second, infographics images have a compressibility. Third, the infographics is properly processed for military commanders. Fourth, sharing, openness and communication are essential for high quality infographic. Lastly, infographics should be an analytic tool for predicting future event based on the past data. Infographics is not a direct representation of data but an analytic tool for helping user's choice and decision in critical moments.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.217-233
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• 2020

This study evaluated the urban vitality of Daegu metropolitan city in 2018 using emerging geographic data such as spatial big data, Wi-Fi AP(access points) and nighttime light satellite image. The emerging geographic data were used in this research to quantify human activities in the city more directly at various spatial and temporal scales. Three spatial big data such as mobile phone data, credit card data and public transport smart card data were employed to reflect social, economic and mobility aspects of urban vitality while public Wi-Fi AP and nighttime light satellite image were included to consider virtual and physical aspects of the urban vitality. With PCA (Principal Component Analysis), five indicators were integrated and transformed to the urban vitality index at census output area by temporal slots. Results show that five clusters with high urban vitality were identified around downtown Daegu, Daegu bank intersection and Beomeo intersection, Seongseo, Dongdaegu station and Chilgok 3 district. Further, the results unveil that the urban vitality index was varied over the same urban space by temporal slots. This study provides the possibility for the integrated use of spatial big data, Wi-Fi AP and nighttime light satellite image as proxy for measuring urban vitality.

• Spatial Information Research
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• v.19 no.4
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• pp.55-71
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• 2011

Recently, interest in cloud computing which provides IT resources as service form in IT field is increasing. As a result, much research has been done on the distributed data processing that store and manage a large amount of data in many servers. Meanwhile, in order to effectively utilize the spatial data which is rapidly increasing day by day with the growth of GIS technology, distributed processing of spatial data using cloud computing is essential. Therefore, in this paper, we review the representative distributed data processing techniques and we analyze the optimization requirements for performance improvement of the distributed processing techniques for a large amount of data. In addition, we uses the Hadoop and we evaluate the performance of the distributed data processing techniques for their optimization requirements.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.1-13
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• 2021

With the development of big data-related technologies, it has become possible to process vast amounts of data that could not be processed before. Accordingly, the establishment of an automated data selection and fusion process for the realization of big data-based services has become a necessity, not an option. In this paper, we propose an automation technique to create meaningful new information by fusing datasets containing spatial information. Firstly, the given datasets are embedded by using the Node2Vec model and the keywords of each dataset. Then, the semantic similarities among all of datasets are obtained by calculating the cosine similarity for the embedding vector of each pair of datasets. In addition, a person intervenes to select some candidate datasets with one or more spatial identifiers from among dataset pairs with a relatively higher similarity, and fuses the dataset pairs to visualize them. Through such semi-automatic data fusion processes, we show that significant fused information that cannot be obtained with a single dataset can be generated.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.2
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• pp.243-254
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• 2017

Recently, discussions about the guarantee of smart ecological environment have been started in S. Korea. These discussions are becoming more and more popular in the aspect of ubiquitous administrative spatial informatization in utilization using big data as a new paradigm due to the rapid change of information and communication technology, such as the start of smart society and the ubiquitous era. In addition, there is a growing interest in discussing environmental and disaster preservation in terms of ubiquitous smart city construction in smart society. In thisstudy, by applying 'scenario planning' as a foresight method, we have developed a desirable future vision for ubiquitous administrative spatial informatization in terms of preservation of disaster of Kori nuclear power plant like earthquake. In order to establish a high level of city disaster prevention level in S. Korea in 2030 when the big data and big data System will be further intensified in the future, it is necessary to develop advanced ICT city disaster prevention system with big data administrative spatial informatization in terms ofsmart ecological city construction.