To determine and manage the maintenance process well, An OWL Ontology for School Building Maintenance is required. School Building Maintenance Ontology includes School Construction Units, School Functional Units, School Space Units, School Usage, and their subclasses. A top-down development process (Uschold and Gruningen, 1996) was used to classify This Ontology, and it was prepared to help Maintenance Project managers and decision makers to decide on maintenance scenarios. The OWL Ontology for School Building Maintenance has three scenarios (the number of these scenarios may be increased by users), and these scenarios are intended to use for a better understanding of the system and improve the decision-making process (Jeong, 2018).

Ontology for School Building Maintenance has four subclasses such as School Construction Units, School Functional Units, School Space Units, and School Usage. Furthermore, there are School Building Maintenance and its subclass Maintenance Scenarios with Space Units, Construction Units, and Functional Units existential restrictions as shown in figure 1 below.

Figure 1: The condition of the classroom’ beam.

All instances of School Space Units of these four subclasses are domains of the Ontology and their ranges are instances of School Usage.  Domains and their ranges in details; Boiler Room(Service) -> Heating, Elevator(Service) -> Accessing, HVAC(Service) -> Cooling+Heating, Utility(Service) -> Lighting, Canteen -> Eating, Corridor(Access) -> Accessing, Lobby(Access) -> Accessing, Loggia -> Rest, Classroom(Room) -> Education, Common Room(Room) -> Rest, Computer Room(Room) -> Education, Managers Room(Room) -> Administrative, Restroom(Room) -> Personal Cleaning, and they are all shown in figure 2 below.

Figure 2: Domains and ranges of the Ontology for School Building Maintenance (by Protégé).

Managing maintenance projects are always challenging.  The hardest and most significant parts of maintenance projects are describing maintenance-required elements of the system and their relations and importance. After a clear explanation of these elements, it would be easy to make better decisions. Many maintenance projects have cost limits, and some of them need to be completed in a limited time as well so mastering the system’s instances helps to stay within cost, time, and quality boundaries. School Building Maintenance also must be finished in a short time to not prevent essential education processes, and it has some cost and quality limits. Therefore, usage of Space Units’ description improves to prioritize maintenance elements, for example, Education purpose is more important than the Rest purpose so if there has to be one option to select, then decision-makers will probably choose to repair an education-based part. On the other hand, to determine maintenance requirements, a good definition of School Construction Units and School Functional Units’ conditions is needed. The percentage of tools can explain to users which condition the related instance is in as shown in an example of ClassroomBeam’s condition in figure 3.

Figure 3: The condition of the classroom’ beam.

All in all, School Space Units describe the places, and each place of the school has a specific usage purpose that is a vital part for decision makers (users). Furthermore, Construction Units and School Functional Units are tools in use, and their conditions tell the requirement of repairment. Hence, users can make advanced maintenance decisions for Construction and School Functional Units considering the usage priority using 3 scenarios Effective Minimum Maintenance, Mandatory Minimum Maintenance, and Required Maintenance (will be described in the last section of this paper). On the other hand, the OWL Ontology for School Building Maintenance can help to improve the deterioration models of school buildings, and it may optimize and expand their lifetimes. Moreover, it may cause managing the school projects far more advanced so school projects may be completed with less money and time. Finally, it may result in more sustainable and environmentally friendly projects thanks to optimizing the material’s usage of the system in whole life.In order to do all of these, a well-defined and optimum quantified Ontology is needed. The OWL Ontology for School Building Maintenance has four subclasses like School Functional Units, School Usage, School Construction Units, and School Space Units in level 2 as shown in figure 4 below.

Figure 4: Main Titles of The OWL Ontology for School Building Maintenance.

Besides, School Functional Units has Equipment and Furniture subtitles, School Construction Units has NonLoadBearingElement and LoadBearingElement subclasses, and School Space Units has six subtitles such as Loggia, Service, Canteen, Room, Access, and Void in level 3 as shown in figure 5 below.

Figure 5: Level 3 Subclasses of The OWL Ontology for School Building Maintenance.

Additionally, School Functional Units has two parts Furniture including Locker, Chair, Board, Table, Desk and Equipment including Cooler, Cable, Generator, Refrigerator, Air conditioner, Boiler, Computer in level 4 as shown in figure 6 below.

Figure 6: Level 4 Subclasses of School Functional Units.

Plus, School Construction Units has two parts Load Bearing Element including Beam, Bearing Wall, Column, and Slab and Non-Load Bearing Element including Ceiling, Interior Wall, Opening, Partition, and Roof in level 4 as shown in figure 7 below.

Figure 7: Level 4 Subclasses of School Construction Units.

In addition, School Space Units has Corridor(Access), Lobby(Access), Canteen, Loggia, Classroom(Room), Common room(Room), Computer room(Room), Managers room(Room), Restroom(Room), Void, Boiler room(Service),  Elevator(Service), HVAC(Service), and Utility(Service) parts in level 4 as shown in figure 8 below.

Figure 8: Level 4 Subclasses of School Space Units.

Furthermore, School Usage has Accessing, Administrative, Cooling, Eating, Education, Heating, Lighting, Personal Cleaning, and Rest subclasses in level 4 as shown in figure 9 below.

Figure 9: Level 4 Subclasses of School Usage.

Finally, there are several individuals that includes conditions (%) of the Construction and Functional Units to be used for different maintenance scenarios. According to these conditions, three maintenance scenarios were created in this study (various scenarios may be created for users) considering Load Bearing Elements Conditions < 70% and Other Elements Conditions < 50%. First of all, Mandatory Minimum Maintenance Boiler room’s beam, Lobby’s beam, Loggia’s beam, and Elevator’s bearing wall that have Load Bearing Elements Conditions < 70% as shown in figure 10 below.

Figure 10: Individuals of Mandatory Minimum Maintenance Scenario.

The second scenario focusing on repairing especially education-related construction and functional units is Effective Minimum Maintenance that includes Load Bearing Elements Conditions =< 70% (mentioned above) + Other Elements Conditions =< 50% (Education Based) such as Classroom Ceiling(50%), Classroom Wall(40%), Classroom Window(40%), Classroom Air Conditioner(40%), Classroom Board(30%), Classroom Chair(40%), HVAC Air Conditioner(40%), Computer Room Computer(40%), and Generator(45%), 13 units in total. The last scenario (Required Maintenance) is focusing on repairing the previous two scenarios and Boiler Room Ceiling, Canteen Ceiling, Restroom Ceiling, Boiler Room Interior Wall, Corridor Interior Wall, Lobby Interior Wall, Loggia Interior Wall, Restroom Interior Wall, Canteen Partition, Restroom Partition, Canteen Air Conditioner, Common Room Air Conditioner, Managers Room Air Conditioner, Canteen Refrigerator, Corridor Board, Canteen Chair, and Canteen Table 30 units in sum (all detailed data in the Protégé file, Appendix 1).

 

 

 

 

 

 

 

 

 

 

References

Uschold, M., & Grüninger, M. (1996). Ontologies: Principles, Methods and Applications. The Knowledge Engineering Review, 11, 93-136. https://doi.org/10.1017/S0269888900007797

Yacob, ShahAli & Au-Yong (2022). Managing Building Deterioration Prediction Model for Public Schools in Developing Countries. Low Sui Pheng, National University of Singapore, Singapore, Singapore. Springer Nature Singapore Pte Ltd. 2022            https://doi.org/10.1007/978-981-16-5860-0