Campus Ontology - Buildings and Building Occupancy

Introduction

The following dashboard is designed to demonstrate the queries (both analytical and transactional) that are now possible as a result of the development of the a linked data source for UT buildings and building-related information. Concretely, this data source is made up of 6 different datasets from across the University of Twente, including:

Please note, the source data is actually slightly broader and does also include data about people and their relations to buildings and departments but a demonstration of this can be found in another dashboard (see: People and Departments). This has only been separated for readability reasons but the source data is the same.

The underlying ontology which supports the linking of these data sources can be explored as a live graphical representation here.

The following SPARQL queries serve to show the results for various transactional or analytical questions regarding UT buildings and their occupancy. The underlying question being answered and the exact content of each query is defined below.

Building Location

The following query provides results showing the location of UT Buildings. The results either show the location of the building in the form of a polygon or in the form of a point. You will notice that there are different amount of results for each query and this is based on the fact that not every UT building in the dataset has a corresponding geometry which is based on inconsistencies across the different datasets that make up the linked dataset.

Building Geometry

The following query provides results showing the location of UT Buildings. With this query, it is possible to see the location of all UT buildings if no particular building name is filled in or a specific building if the search bar input is used and a building name is filled in. If you click on the geometry itself, you will be able to see building related information such as address, postcode and other information.

Please note:

  • the search functionality in this interface is sensitive so you need to input an exact name match for buildings in order for a building to be found.
  • not all buildings at the UT have a corresponding geometry in the linked data set. If a result is not returned, it is likely that a geometry for the building has not been defined.

UT Buildings and Rooms

The following queries provides information about all the rooms located within a building and then counts the number of rooms in buildings across the UT or for a particular building. For both queries, filling in a particular building name will provide you with filtered results.

Please note: the search functionality in this interface is sensitive so you need to input an exact name match for building in order for the results to be returned.

List of Rooms Within a Particular Building

The following query allows for a particular building to be searched for and for a list of all known rooms to be returned. As you will notice, the results do not seem as complete as possible so further enrichment of the dataset could improve the results.

Please note: As noted earlier, not all buildings have a geometry associated with them in the linked data source so the results seen here are only for buildings that do have a geometry. An additional query follows this one which presents a comparison of all buildings and their rooms counts across the UT without the dependency of having a geometry.

Count of Rooms within a Building

The following query allows for a particular building to be searched for and for the count of all rooms within the building to be returned. Leaving the building name blank will also allow for a count for all buildings across the UT to be returned. To see the room count, click on the geometry of the building and the information will be displayed in a pop-up.

Comparison of Room Count Across UT Buildings

The following query presents a comparison of room counts for each building at the UT. As can be seen from this result, some rooms have a surprisingly low count, highlighting the need to enrich the existing linked data source with more extensive information.

Building Occupancy

The following queries present some analytical results based on the occupancy of UT buildings. The data used for this analysis was originally displayed in the CampusCrowd Map and is, therefore, not live data.

The dataset used for these queries is relatively small based on the time insensitivity of converting this data to linked data. Including more data across a wider time range would make more analysis possible.

UT Buildings and Occupancy at a Given Time

The following query provides results for occupancy related information for all buildings at the UT. A particular timeslot can be input at the top of the query and all occupancy information for that timeslot across UT buildings will be displayed, supporting the user in making decisions on how to make use of the buildings during particular times. Although this is historical data and does not yet support live decision making, it does present insight into how the CampusCrowd map information could easily be included in a linked data format. Streaming this data would, therefore, support live decision making.

In this query, the percentage occupancy represents the amount of people in the building relative to the overall capacity of the building. The capacity is defined based on some rule associated with the amount of people a building can accommodate under certain circumstances. The total occupancy represents the total number of people in the building for a given timeslot. A comparison of these two measures as shown in the graph allows a user to see how busy a building is relative to its capacity (and, therefore, size).

Please note: Because the dataset use for this demonstration dashboard is relatively small, only the 9am timeslot is possible for the query below. When the data is extended, so too will be timeslot possibilities be extended.

Weekly Building Occupancy Trend

The following query allows the user to see the trend in occupancy for a particular building for a particular timeslot across a week. This might, for example, support a user in deciding which day in the week is most desirable to make use of a building or could support university staff in planning events in a building at a time where there is the most traffic. Unlike the former query, the inclusion of this historical data in the linked dataset extends the functionality of the CampusCrowdMap and supports richer analysis.

Please note: Because the dataset use for this demonstration dashboard is relatively small, only the 9am timeslot is possible for the query below. When the data is extended, so too will be timeslot possibilities be extended.

Daily Trend for a Particular Building

The following query allows the user to see what the daily trend for a particular building is for a particular day. This may support the user is planning their visit to a particular building based on the historical data. Like the previous query, the use of this historical data for analytics extends the CampusCrowdMap and supports the user in better decision making.

Please note: Because the dataset use for this demonstration dashboard is relatively small, it is only currently possible to perform this query on two buildings, Bastille and Spiegel. Extending the dataset would allow this to be done for more buildings across the UT.

Busiest Timeslot for a Particular Building

The following query allows the user directly query for the busiest timeslot for a particular building is for a particular day. This may support the user is planning their visit to a particular building based on the historical data. Like the previous query, the use of this historical data for analytics extends the CampusCrowdMap and supports the user in better decision making.

Please note: Because the dataset use for this demonstration dashboard is relatively small, it is only currently possible to perform this query on two buildings, Bastille and Spiegel. Extending the dataset would allow this to be done for more buildings across the UT and at more granular timeslots.