- Volume 11 Issue 4
The public data portal provides various public data created by the government in the form of files and open APIs. In order to increase the usability of public open data, a variety of information should be provided to users and should be convenient to use for users. This requires the structured data design plan of the public data. In this paper, we propose a data design method to improve the usability of the Seoul subway public data. For the study, we first identify some properties of the current subway public data and then classify the data based on these properties. The properties used as classification criteria are stored properties, derived properties, static properties, and dynamic properties. We also analyze the limitations of current data for each property. Based on this analysis, we classify currently used subway public data into code entities, base entities, and history entities and present the improved design of entities according to this classification. In addition, we propose data retrieval functions to increase the utilization of the data. If the data is designed according to the proposed design of this paper, it will be possible to solve the problem of duplication and inconsistency of the data currently used and to implement more structural data. As a result, it can provide more functions for users, which is the basis for increasing usability of subway public data.
Supported by : Seokyeong University
- B.J. Jeon and H.W. Kim, “An Exploratory Study on the Sharing and Application of Public Open Big Data,” Information Policy, Vol. 24, No. 3, pp. 27-41, 2017. DOI: https://doi.org/10.22693/NIAIP.2017.24.3.027.
- B.H. Back and I.K. Ha, "A Method for Selective Storing and Visualization of Public Big Data Using XML Structure," Journal of the Korea Institute of Information and Communication Engineering, Vol. 21, No. 12, pp. 2305-2311, Dec 2017. DOI: https://doi.org/10.6109/jkiice.2017.21.12.2305.
- J.Y. Chang, “An Experimental Evaluation of Box office Revenue Prediction through Social Bigdata Analysis and Machine Learning,” The Journal of the Institute of Internet, Broadcasting and Communication (JIIBC), Vol. 17, No. 3, pp. 167-173, Jun 2017. DOI: https://doi.org/10.7236/JIIBC.2017.17.3.167.
- M.S. Kang, Y.G. Jung, and D.H. Jang, “A Study on the Search of Optimal Aquaculture farm condition based on Machine Learning,” The Journal of the Institute of Internet, Broadcasting and Communication (JIIBC), Vol. 17, No. 2, pp. 135-140, Apr 2017. DOI: https://doi.org/10.7236/JIIBC.2017.17.2.135. https://doi.org/10.7236/JIIBC.2017.17.2.135
- H.J. Seo and S.H. Myeong, “Policy Alternatives for User-oriented Public Data Utilization-Focusing on ICT Managers Perception in Private Sector,” Journal of Korean Association for Regional Information Society, Vol. 17, No. 3, pp. 61-86, Sep 2014.
- M.K. Min, “Classification of Seoul Metro Stations Based on Boarding/Alighting Patterns Using Machine Learning Clustering,” The Journal of The Institute of Internet, Broadcasting and Communication (JIIBC), Vol. 18, No. 4, pp. 13-18, Aug 2018. DOI: https://doi.org//10.7236/JIIBC.2018.18.4.13.
- J.S. Kim, “Subway Congestion Prediction and Recommendation System using Big Data Analysis,” Journal of Digital Convergence, Vol. 14, No. 11, pp. 289-295, Nov 2016. DOI: https://doi.org/10.14400/JDC.2016.14.11.289.
- M.W. Kim, Predicting Subway Passengers Flows by Spatio-Temporal Modeling, Master Thesis, Seoul National University, Korea, pp. 4-32, Aug 2017.
- M.K. Min, “Modeling and Implementation of Public Open Data in NoSQL Database,” International Journal of Internet, Broadcasting and Communication (IJIBC), Vol. 10, No. 3, pp. 51-58, Aug 2018. DOI: http://dx.doi.org/10.7236/IJIBC.2018.10.3.51.
- S.H. Lim, W.J. Jang, and S.M. Lee, "Improving Reuse of Public Transport Information in Open Government," Basic Research Report, The Korea Transport Institute, pp. 11-129, Oct 2014.
- B.H. Kim, “Recent Trend of Big Data Policy Abroad,” The Korea Contents Association Review, Vol. 12, No. 1, pp. 38-40, Mar 2014. DOI: http://doi.org/10.20924/CCTHBL.2014.12.1.038.