• Journal of the Korean Society for information Management
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• v.30 no.3
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• pp.297-315
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• 2013

Anyone curious to easily access and learn Korean history has become interested in Korean history data bases, which will provide accurate and reliable historical information. Furthermore, user demands for information sharing and reusability, available through setting up a semantic web, have been increased, which have taken the shape of linked data. Efforts have been made to construct public data bases containing readily usable contents a user can understand and utilize with ease. They have been produced by several organizations, portal sites, and individuals, trying to deviate from existing mainstreams - expert-based text data bases. A problem with those data bases is that they have not considered such vital factors as the sharing and utilizing of information as a whole. This study suggests a LOD-based Korean history contents implementation system, providing rich information environment by way of multi-dimensional web-data connections. In doing so, this system has tried a historic information circulation service system which is based on information sharing and connecting.

• Journal of Information Science Theory and Practice
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• v.9 no.2
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• pp.66-82
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• 2021

Recommender Systems have gained immense popularity due to their capability of dealing with a massive amount of information in various domains. They are considered information filtering systems that make predictions or recommendations to users based on their interests and preferences. The more recent technology, Linked Open Data (LOD), has been introduced, and a vast amount of Resource Description Framework data have been published in freely accessible datasets. These datasets are connected to form the so-called LOD cloud. The need for semantic data representation has been identified as one of the next challenges in Recommender Systems. In a LOD-enabled recommendation framework where domain awareness plays a key role, the semantic information provided in the LOD can be exploited. However, dealing with a big chunk of the data from the LOD cloud and its integration with any domain datasets remains a challenge due to various issues, such as resource constraints and broken links. This paper presents the challenges of interconnecting and extracting the DBpedia data with the MovieLens 1 Million dataset. This study demonstrates how LOD can be a vital yet rich source of content knowledge that helps recommender systems address the issues of data sparsity and insufficient content analysis. Based on the challenges, we proposed a few alternatives and solutions to some of the challenges.

• Asia pacific journal of information systems
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• v.14 no.3
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• pp.169-187
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• 2004

Self-maintainability of data warehouse(DW) views is an ability to maintain the DW views without requiring an access to (i) any underlying databases or (ii) any information beyond the DW views and the delta of the databases. With our proposed method, DW views can be updated by using only the old views and the differential files such as different files, referential integrity differential files, linked differential files, and backward-linked differential files that keep the truly relevant tuples in the delta. This method avoids accessing the underlying databases in that the method achieves self-maintainability even in preparing auxiliary information. We showed that out method can be applicable to the DW views that contain joins over relations in a star schema, a snowflake schema, or a galaxy schema.

• The Journal of Korean Physical Therapy
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• v.28 no.5
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• pp.321-327
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• 2016

Purpose: The purpose was to link items of questionnaires that measure functioning and disability of persons with Low Back Pain (LBP) into the International Classification of Functioning, Disability and Health (ICF). Methods: The Oswestry Disability Index (ODI), Roland and Morris Disability Questionnaire (RM), Fear-Avoidance Beliefs Questionnaire (FABQ), and Short Form-36 health survey (SF-36) were evaluated to map items of those questionnaires into the ICF categories. The linking rule was employed and linking was performed independently by 10 health professionals. One-hundred and two patients with LBP were recruited from 19 medical institutes to this study for a field test to examine relations between the scale and its linked ICF category set. Pearson correlation coefficient was used to analyze their relationships. Results: Walking was only found to be one-to-one linking between the scale and the ICF. Sixty questions in FABQ were to be linked to 9 of ICF categories. Ten and 14 ICF categories were able to be linked to RM and ODI respectively. It was found that majority of items from ODI and RM scale had similar concept and linked to the same ICF category. SF-36 had only 15 categories of the ICF linked. Strong relationship was observed between measurement scales and linked ICF code sets (r=0.79, r=0.65, r=0.47, and r=-0.31 for ODI, RM, FABQ and SF-36 respectively). Conclusion: It was found that commonly used clinical tools for LBP may be linked to ICF. The study results may suggest that clinical data can be standardized to communicate between related professionals.

• The Journal of Korean Physical Therapy
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• v.30 no.6
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• pp.239-245
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• 2018

Purpose: This study was to identify international classification of functioning, disability and health (ICF) categories that could be linked conceptually to disability of arm, shoulder and hand (DASH) items and short form of health survey 36 (SF-36) items for persons with shoulder pain. Methods: Linkage between each item in DASH and SF-36 and the categories in the ICF were assessed. The linking process was performed by ten health professionals following the linking rule. One hundred four patients with shoulder pain were enrolled from 12 private clinic outpatient departments and participated in this study. Pearson correlation coefficients were used to assess the relationships between each scale item and the linked ICF code. Results: Thirty DASH items were able to be linked to 30 ICF codes, whereas the 36 items in SF-36 were only linked to 17 ICF codes. General health items included in SF-36 could not be linked to a relevant ICF concept. There was a high correlation between the two measurement tools and the linked ICF codes, DASH and its ICF code list (r =0.91), SF-36-Physical Health and its code list (r =-0.62), and SF-36-Mental Health and its code list (r =-0.72). Conclusion: The results suggest that concepts within each item in DASH can be linked to ICF codes for patients with shoulder pain, however, the concepts in the SF-36 items had limited linkage to ICF codes. The shoulder-specific functional tool, DASH can be expressed with ICF codes and, therefore, its use can promote data standardization and improve communication between professionals.

• The Journal of Korean Institute of Information Technology
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• v.17 no.5
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• pp.1-12
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• 2019

Unlike existing Open APIs, Linked Data are made as a huge intelligent base to perform high-level SPARQL queries, and it is possible to create efficiently a new content by mashuping different information from various datasets. This paper implements a responsive web application for location-based semantic search. We mashup DBpedia, a kind of Linked Data, and GoogleMap API provided by Google, and provide a semantic browser function to confirm detail information regarding retrieved objects. Our system can be used in various access environments such as PC and mobile by applying responsive web design idea. The system implemented in this paper compares functional specifications with existing systems with similar functions. The comparison results show the superiority of our system in various aspects such as using semantic, linked-based browser, and mashup function.

• The Journal of Korean Academic Society of Nursing Education
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• v.5 no.1
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• pp.72-85
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• 1999

The paper presents a review of three data sets(Uniform Hospital Discharge Data Set, Nursing Minimum Data Set, and Nursing Management Minimum Data Set) and six major nursing classifications(the North American Nursing Diagnoses Association Taxonomy I, Omaha System, Nursing Interventions Classification, Nursing Intervention Lexicon and Taxonomy, Nursing Outcome Classification, Nursing Outcomes Classification, and Classification of Patient Outcome). The reviewed data sets and nursing classifications were different from each other in the purpose, structure, and user. Nursing Interventions Classification and Nursing Outcomes Classification were linked to North American Nursing Diagnosis Association, but others not. The data set and nursing classifications need to be linked to other data sets and classifications.

• Journal of KIISE:Databases
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• v.41 no.4
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• pp.226-241
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• 2014

LOD(Linked Open Data) is composed of RDF triples which are based on ontologies. They are identified, linked, and accessed under the principles of linked data. Publications of LOD data sets lead to the extension of LOD cloud and ultimately progress to the web of data. However, if ontologically the same things in different LOD data sets are identified by different URIs, it is difficult to figure out their sameness and to provide trustworthy links among them. To solve this problem, we suggest a Trustworthiness Improving Link Evaluation, TILE for short, technique. TILE evaluates links in 4 steps. Step 1 is to consider the inference property of syntactic elements in LOD data set and then generate RDF triples which have existed implicitly. In Step 2, TILE appoints predicates, compares their objects in triples, and then evaluates links between the subjects in the triples. In Step 3, TILE evaluates the predicates' syntactic property at the standpoints of subject description and vocabulary definition and compensates the evaluation results of Step 2. The syntactic elements considered by TILE contain RDFS, OWL, OWL2 which are recommended by W3C. Finally, TILE makes the publisher of LOD data set review the evaluation results and then decide whether to re-evaluate or finalize the links. This leads the publishers' responsibility to be reflected in the trustworthiness of links among the data published.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.4
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• pp.501-510
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• 2023

The importance of using construction data is increasing in accordance with the recent trend in the smart construction. However, construction project and maintenance information is distributed on the web, and the existing BIM(Building Information Modeling) information exchange and linking method using IFC(Industry Foundation Classes) cannot support connection with BIM data and web resources. This study aims to establish the BIM-based port facility data integration system using linked data(LD) technology in order to integrate BIM and heterogeneous data in the port maintenance domain. To this end, the port BIM-based ifcOWL and port facility maintenance ontology were designed, and LD was built for the BIM and maintenance information of Busan New Port 2-1 Pier3, a BIM pilot project. In addition, service prototypes such as search, statistics and SPARQL(SPARQL Protocol and RDF Query Language) endpoint functions were implemented using the issued LD. The LD-based information utilization system is expected to improve the reusability of information by converting the existing closed information system into an open system and BIM and maintenance data as a web resource in a standard format.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.203-219
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• 2011

Previously common users just want to watch the video contents without any specific requirements or purposes. However, in today's life while watching video user attempts to know and discover more about things that appear on the video. Therefore, the requirements for finding multimedia or browsing information of objects that users want, are spreading with the increasing use of multimedia such as videos which are not only available on the internet-capable devices such as computers but also on smart TV and smart phone. In order to meet the users. requirements, labor-intensive annotation of objects in video contents is inevitable. For this reason, many researchers have actively studied about methods of annotating the object that appear on the video. In keyword-based annotation related information of the object that appeared on the video content is immediately added and annotation data including all related information about the object must be individually managed. Users will have to directly input all related information to the object. Consequently, when a user browses for information that related to the object, user can only find and get limited resources that solely exists in annotated data. Also, in order to place annotation for objects user's huge workload is required. To cope with reducing user's workload and to minimize the work involved in annotation, in existing object-based annotation automatic annotation is being attempted using computer vision techniques like object detection, recognition and tracking. By using such computer vision techniques a wide variety of objects that appears on the video content must be all detected and recognized. But until now it is still a problem facing some difficulties which have to deal with automated annotation. To overcome these difficulties, we propose a system which consists of two modules. The first module is the annotation module that enables many annotators to collaboratively annotate the objects in the video content in order to access the semantic data using Linked Data. Annotation data managed by annotation server is represented using ontology so that the information can easily be shared and extended. Since annotation data does not include all the relevant information of the object, existing objects in Linked Data and objects that appear in the video content simply connect with each other to get all the related information of the object. In other words, annotation data which contains only URI and metadata like position, time and size are stored on the annotation sever. So when user needs other related information about the object, all of that information is retrieved from Linked Data through its relevant URI. The second module enables viewers to browse interesting information about the object using annotation data which is collaboratively generated by many users while watching video. With this system, through simple user interaction the query is automatically generated and all the related information is retrieved from Linked Data and finally all the additional information of the object is offered to the user. With this study, in the future of Semantic Web environment our proposed system is expected to establish a better video content service environment by offering users relevant information about the objects that appear on the screen of any internet-capable devices such as PC, smart TV or smart phone.