This project contains the Common Greenhouse Ontology (CGO) and the documentations about the ontology.
The Common Greenhouse Ontology is developed in the Dutch DDINGS project to capture the different data, constructional, and systemic elements used in a Greenhouse.
Cornelis Bouter, TNO ([email protected])
Joris van Duijneveldt, TNO ([email protected])
Jack Verhoosel, TNO ([email protected])
Klaas Andries de Graaf, TNO ([email protected])
Roos Bakker, TNO ([email protected])
Romy van Drie, TNO ([email protected])
The ontology can be found in the folder Ontologies.
If you want to make changes to the ontology or other content in this repository, please read the CGO manual and this readme first. If you want to make small changes:
- checkout the dev branch
- bring it up to date with the master
- make your changes and document them in a commit message
- open a new merge request for merging your changes in the master
- One of the maintainers will approve the changes and merge
For larger changes create a new branch and regularly commit with descriptive commit messages. If your changes are related to an issue, use #issuenumber (e.g. #7) to tag your issue in the commit message.
Greenhouses are used to grow vegetables and plants year-round. The climate in the greenhouse has a considerable influence on the growth of the crops. Therefore, it is important to optimally control the climate. Increasingly more tools become available to help with this, such as a climate computer, sensors, and other systems. All these systems produce different data, such as temperatures, crop growth, weather statistics, which is stored in different databases. In this repository, you can find the Common Greenhouse Ontology (CGO). It provides semantic alignment of different databases, as well as a standard on high-tech greenhouses and their components. The CGO was created in a national project Data-Driven Integrated Greenhouse Systems (DDINGS). In this project, a platform was created to connect databases and perform data analysis [1]. In that work, we also introduced a first version of the CGO. Since then, we fully developed the CGO with different modules, a broad set of classes that describe the components of greenhouses, and an integration with other ontologies such as the Semantic Sensor Network ontology [2] and the Ontology of units of Measure [3]
The CGO was developed with domain experts and focuses on greenhouse-related concepts and measurements. Several ontology development methods were consulted and applied at various stages of development, including SABiO [4], and Ontology 101 [5]. The CGO also makes use of other ontologies: the Semantic Sensor Network ontology (SSN), which includes the Sensor, Observation, Sample, and Actuator ontology (SOSA), and the Ontology of units of Measure (OM).
Observations are an important aspect of the CGO. In the CGO, the SOSA ontology is used to model observations. In Figure 1, a simplified version of SOSA’s architecture of observations is shown in green. The example observation is the thickness of a stem (of a flower). The stem is the part that is observed, the Feature of Interest. The property we are observing is its thickness, the Observable Property. The Feature of Interest and the Observable Property, but also the result, are linked to the Observation, the center of the architecture to which all elements are connected.
The Ontology of units of Measure (OM) is an OWL ontology for the domain of quantities, measurements and units of measure [3]. OM provides the possibility to link aspects of an observation to a quantity and a unit. A schematic overview of how this is implemented in CGO is given in Figure 1. From a cgo:Class (e.g. thickness), a link to an om:Quantity (e.g. om:Width) can be provided. The results are linked to a numerical value through om:NumericalValue (this is not shown in Figure 1 for reasons of simplification) and to a unit through om:hasUnit.
The CGO contains 382 classes, 99 properties (both data and object properties), and 12 individuals.1 This includes the classes and properties from the SOSA ontology. We can divide the content into four main categories: the greenhouse, which is the center concept of the ontology, features, which are set properties of the greenhouse such as its dimensions, parts, which are the objects that can be found in greenhouses, and finally, measurements. The measurements in the greenhouse are modelled using SOSA [2] and OM [3] as could be seen in Figure 1. SOSA classes are connected to CGO classes by being superclasses of possible Features of Interest and Observable Properties, OM classes are connected to data properties of CGO and as a subtype of sosa:Result. Each of the categories contain a variety of classes. The parts category contains over 150 classes and provides an elaborate, yet not complete, overview of parts of a high-tech greenhouse. Important subsets are systems and construction hierarchies. The systems subset describes a wide set of systems in a greenhouse ranging from broader ventilation systems to specific geothermal heat pumps. The construction subset includes classes such as screens and ventilation vents. These classes are all connected to the center of CGO, the greenhouse class, by the object property part of. As mentioned above, measurements are modelled through SOSA, but features of the greenhouse such as its orientation and location are expressed with data properties.
For testing the completeness of the CGO, we created competency questions (CQ) in collaboration with greenhouse experts. For querying, SPARQL queries were made from these CQ's, and restrictions were expressed using SHACL constraints.
A visualisation of the ontology gives a quick overview and can add to the understanding of the design choices described above. For displaying the ontology, first download the ontology to your device. Then go to the following link:
Upload the ontology by going to the tab Ontology in the toolbar at the bottom of your screen. Click select ontology file, and select the CGO ontology.
For editing the ontology for reuse we recommend using Protégé or Topbraid.
For more development information on how to find and add concepts to the CGO, checkout the CGO manual. For a more elaborate theoretical description, read our paper on the CGO (submitted) [7].
Athanasios Sapounas, TNO
Bart Slager, TNO
Roos Bakker, TNO
Romy van Drie, TNO
Barry Nouwt, TNO
Cornelis Bouter, TNO
Han Kruiger, TNO
Ellen van Bergen, TNO
Sander van Leeuwen, WUR
Lorijn van Rooijen, WUR
Jack Verhoosel, TNO
Jan Top, WUR
- Verhoosel, J.P.C.; Nouwt, B.; Bakker, R.M.; Sapounas, A.; Slager, B. A Datahub for Semantic Interoperability in Data-Driven Integrated Greenhouse Systems. EFITA conference 2019.
- Neuhaus, H.; Compton, M. The semantic sensor network ontology. AGILE workshop on challenges in geospatial data harmonisation, Hannover, Germany. 2009.
- Rijgerberg, H.; Wigham, M.L.I.; Top, J.L. How semantics can improve engineering processes: A case of units of measure and quantities. Adv. Eng. Inform 2011, 25, 276-287.
- de Almeida Falbo, R. Experiences in using a method for building domain ontologies. The 16th International Conference on Software Engineering and Knowledge Engineering, SEKE. 2004.
- Noy, N.; McGuinness, D. Ontology development 101: A guide to creating your first ontology. Development 2001, 32, 1-25.
- Bouter, C.; Kruiger, H.; Verhoosel, J. Domain-Independent Data Processing in an Ontology Based Data Access Environment using the SOSA Ontology, Demonstration track of the 2021 Formal Ontology in Informations Systems Conference, 2021, Submitted.
- Bakker, R.M.; van Drie, R.A.N.; Bouter, C.A.; van Leeuwen, S.; van Rooijen, L.; Top, J. The Common Greenhouse Ontology: an ontology describing components, properties, and measurements inside the greenhouse. EFITA conference 2021, submitted
CGO is released under Apache 2.0, for more information see the LICENSE.
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