TESTINg OF THE EVALUATION METHODOLOGY FOR SHIP’S PLANNED MAINTENANCE SYSTEM DATABASE
This is an open access article distributed under the CC BY-NC-ND 4.0 terms and conditions.
Volume 17 article 606 pages: 273 - 279
Ship’s Planned Maintenance Systems are in use for a long period of time, but database quality, configuration and content are still not standardized. Factors affecting the database quality, configuration and content are the quality of raw data, experience and knowledge of database creation team, importance given to computerized PMS and care assigned to evaluation of finished product. Evaluation of finished product, i.e. ship’s Planned Maintenance System Database is an action requiring specified knowledge and qualifications, as well as experience in performing the task. Even when evaluators fulfill all needed requirements, credibility of the obtained results is questionable due to their subjectivity. One of the tools to decrease that problem is the Evaluation Methodology for Ship’s Planned Maintenance System Database. A research, described in the paper, has been performed to test that aspect of the Methodology. Three Ships Planned Maintenance System Databases were evaluated by four different evaluators, first using only their experience, then using the Methodology. Results of the research are presented in the paper together with comparison of findings. All presented points that usage of the Methodology is a necessity during evaluations of ship’s Planned Maintenance System Databases.
Part of the research for this article was performed using the equipment obtained through the Project named: “Functional integration of the University of Split, PMF-ST, PFST and KTF-ST through development of scientific and research infrastructure in Three faculties building’’, contract number KK.01.1.1.02.0018.
D.M.; Rumble, Jr. J. 2003. The essentials of a database quality process. Data
Science Journal, Vol 12, pp.35-46.
G.; Poljak, I.; Orović, J. 2018. Computerized Planned Maintenance System
Software Models, Pomorstvo: Scientific Journal of Maritime Research 32:
O. 2013. Methods for Database Quality Assessment, Forest Monitoring,
Developments in Environmental Science Book 12, Chapter 23. Elsevier, Dordrecht,
pp 455-467, 10.1016/B978-0-08-098222-9.00023-6.
O., Trigano, P., &Crozat, S. (1999). Considerating Subjectivity in
Softwares Evaluation. In J. Vanderdonckt& A. Puerta (Eds.), Computer-Aided
Design of User Interfaces II. (pp. 331-336). Dordrecht: Springer Science and
Business Media LLC. doi:10.1007/978-94-011-4295-3_29.
A.; Stazić, L.; Stanivuk, T.; Komar, I. 2019. Verification of the Evaluation
Methodology for Ship’s Planned Maintenance System Database, Book of
Proceedings, 8th International Maritime Science Conference / Ivošević, Špiro;
Vidan, Pero - Kotor: CIP - NacionalnabibliotekaCrne Gore, 2019, 441-445.
B. 2011. Data Quality Improvement Impeded by Lack of Automation,
M. 2002. Inference by believers in the law of small numbers. Quarterly
Journal of Economics 117: 775–816.
C. 2002. Subjectivity and Objectivity in Qualitative Methodology, Forum:
Qualitative Social Research, 3(3), Art. 16,
P.H., Lipsey, M.W., & Henry, G.T. (2018). Evaluation: A Systematic
Approach. USA: SAGE Publications Inc.
L.; Komar, I.; Mihanović, L.; Mišura, A. 2018. Shipowner’s Impact on Planned
Maintenance System Database Quality Grades Resemblance Equalization, Transactions
on Maritime Science, 07(01), 5 - 22.
L.; Komar, I.; Račić, N. 2017. Evaluation Methodology for Ship’s Planned
Maintenance System Database, Transactions on Maritime Science, 06(02):
109 – 116, https://doi.org/10.7225/toms.v06.n02.002.
P.; Oberhofer, M.; Borek, A. 2014. A Classification of Data Quality Assessment
and Improvement Methods, International Journal of Management Information
Systems, 12(4): 5-33
R. Y.; Strong, D. M. 1996. Beyond Accuracy: What Data Quality Means to Data
Consumers, Journal of Management Information Systems, 12(4): 5–33.