# DTAG: A Methodology for Aggregating Digital Twins Using the WOTDT Ontology
## 1 Introduction  
Current technological advancements and the increasing complexity of modern systems have driven the adoption of digital twins (DTws) as a powerful solution to address a variety of challenges [1], such as high-fidelity modelling, data acquisition and processing, and unified development platforms and tools. DTws offer a virtual representation of physical assets, processes, or systems, enabling real-time monitoring, simulation, and optimisation. This technology has become widely accepted in various domains due to its potential to help decision-making, improve operational efficiency, and increase overall performance [2]. DTws can be differentiated in multiple levels [2], such as DTw at the unit level (representing individual components or assets), DTw at the system level (modelling a collection of interconnected units), and DTw at the system-of-systems level (representing complex interconnected systems). Furthermore, these levels can be represented as a digital twin instance (DTwI) for the unit level and a digital twin aggregate (DTwA) for the system and system-of-systems level [3]. Although DTws offer many benefits, such as providing solutions to the challenges explained previously, a considerable challenge lies in the interoperability between different levels of DTws [4; 5; 6]. Furthermore, even though DTws can be represented on different levels, a challenging problem arises when trying to aggregate and connect lower-level DTws (DTwI) to create higher-level representations (DTwA). In many cases, these DTws are developed independently, using different data formats, architectures [7; 8], modelling methodologies, and sometimes ontologies [2]. This results from a lack of interoperability between the data generated at each DTw level. In this article, an extension of the W3C standard thing description (TD) ontology [9], proposed by the Web of Things (WoT) group, called the WoTDT ontology (WoTDT ontology v2: [https://w3 id.org/def/dtw](https://w3 id.org/def/dtw), accessed on 18 May 2024) (WoT digital twin ontology) is presented. The goal of the WoTDT ontology is to provide formal semantics to represent the five-dimensional architecture model approach [8] and its features, allowing semantic discovery by reusing the TD ontology and a common approach to describe the capabilities of a DTw allocated by dimensions. Furthermore, this ontology was developed using the LOT methodology [10], following good practices in ontology engineering. In addition, this article also includes an aggregation methodology called DTAG (digital twin aggregation methodology), used to aggregate DTws of different levels to obtain an aggregated DTw (DTwA), taking into consideration whether the DTws contain semantics or not. DTAG methodology follows dimensional aggregation according to the five-dimensional approach [8], where WoTDT ontology is applied to conceptualise the architecture and features of the resultant DTwA. Thus, this aggregation approach enables the aggregation of both metadata and data (whether semantic or not) from multiple DTws, resulting in a DTwA that contains all the metadata, centralised through the WoTDT ontology, and incorporates the data related to the DTws involved in the aggregation. The rest of this article is structured as follows. Section 2 provides an overview of the literature and research proposals related to DTws in terms of architectures, different levels, aggregation, and ontologies. Section 3 includes the development of the WoTDT ontology using the LOT methodology. Section 4 provides the aggregation methodology based on the dimensions described in the WoTDT ontology and provides examples of aggregation by two DTws, which are aggregated into a DTwA extracted from the European H2020 COGTO (COGTO project: [[https://cogito-project.eu/](https://cogito-project.eu/)]([https://cogito-project.eu/](https://cogito-project.eu/)), accessed on 18 May 2024.