Introduction

Defined terminologies are key for any communication. They are paramount for any processes where information is exchanged, merged or analyzed and a prerequisite for scientific communication [1]. Finding and defining a common language between different disciplines or domains is the foundation for a robust exchange of information and knowledge. To prevent the bad and sometimes ugly fruits of miscommunication and foster the good synergy of such interaction, this holds particularly true for interdisciplinary work inside and outside academia. Especially in the case of transdisciplinary research the lack of a consistent language and terminology inhibits joint progress [2]. Nevertheless, all disciplines have defined and sharpened their terminologies over the course of the past centuries. Even supposedly common terms like ‘model’ may have different meanings in different disciplines. During industrialization, communication between different countries became more important and led to standardizations of technical and scientific terminology [1]. These terminologies can be embedded in everyday language but can also exceed to a pure domain-specific meaning. Within the approach of Cross Domain Fusion, many different disciplines are working on a common ground to find solutions by using a common language. Within this process, it is essential to have knowledge about the used terminologies of all actors. Nevertheless, different disciplines tend to use the same term with different meanings of facets of their interpretation. A common tool to overcome this hurdle is the definition of a common glossary, where terminologies are clearly defined and used in their specific context.

An excellent example of the difficulties in finding a common language is the concept of transdisciplinary science. If we define interdisciplinarity as a cooperation of academics from different disciplines, transdisciplinarity goes further and includes non-academics actors (stakeholders like citizens, administration or business) in the co-creation of knowledge [3]. The debate about the definition of transdisciplinary and related terms has been ongoing for decades [4], and experience shows that partners in new transdisciplinary projects still need time and efforts to develop a common understanding of basic terms. In the recent literature, there are different approaches to introduce more clarity. Searching for glossaries of transdisciplinary terminology, in sensu stricto we found only one glossary that focuses on knowledge transfer vocabulary and gives definitions, e.g. for “open access”, “open data”, “science communication”, “hackathon” or “crowdsourcing” [5]. Prominent examples of such glossaries and dictionaries include: handbooks containing glossary-like chapters, e.g. on “interdisciplinarity”, “transformative science” or “experiment” with extended academic discussions [6, 7]. Schmohl & Philipp (2021) [6] dedicate ten pages to each term and provide access to extended academic discussions, but there is no Wiki-like glossary offering short definitions. A Dialogue:Wiki would indeed fill a gap by offering working definitions for key terms.

We see a great need to advance this relatively “standard” procedure to be inclusive with all disciplines. Our suggestion is to setup a database of terminologies used in Cross Domain Fusion including their—often—different meanings. This will enable the user of each discipline to easily access terms and their usage and interpretation of the involved disciplines. We also see a great need to reduce any barriers posed by the interface design and usability of such database. To achieve this, we set up the Dialogue:Wiki (http://dialoguewiki.ceos.uni-kiel.de) with the prominent MediaWiki as the graphical user interface.

The Dialogue:Wiki

The largest open-source encyclopedia is Wikipedia, which is a product of the MediaWiki group. It allows users all over the globe to access, write and moderate content. Its open character enables a broad community to share and exchange knowledge. Today, it is the most used repository for any knowledge of humankind. The graphical user interface (GUI) of Wikipedia, which is designed by the MediaWiki group, was designed for its accessibility; many users are already used to the functionality of this product and adapting to a “new” system is comparatively intuitive. Hence, we decided to use the open-source MediaWiki to host our Cross Domain Fusion terminology database: the Dialogue:Wiki. In strong contrast to the original Wikipedia, we are not using an open format for the creation of articles within the wiki. At its start, it is hence a publicly accessible but closed system. We rather use a moderated procedure to implement terminologies into the database (Fig. 1). This procedure starts with the proposal of a term by a member of the involved actors. This term will then be evaluated and defined by a consortium of at least four different disciplines included—in this case—in the Cross Domain Fusion team. An editorial board finally quality checks and uploads the finalized term as an article into the Dialogue:Wiki. This process ensures and safeguards an interdisciplinary perspective of any term. If the interdisciplinary consortium spots different definitions for a term, the term will be attributed to its different definitions by each research domain.

Fig. 1
figure 1

Procedure of the implementation process of terms into the Dialogue:Wiki. The crosses indicate stages where decisions are taken by the editorial board. This also include loops, if no decision could be taken in a first round

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‘Model’ as an ambiguous term in Cross Domain Fusion

The Dialogue:Wiki aims to serve as a repository for terminologies and their different definitions in each discipline included in the approach of the Cross Domain Fusion. It is built to cope with a growing number of terminologies over the course of the next years. It is hence a living rather than a static database. In this article, we cannot show all terms that have already been implemented but present our idea based on an example. The term ‘model’ is heavily used in discussions and implementations of Cross Domain Fusion. All disciplines use the term “model” in a different fashion. From our understanding it is hence a suitable term to act as an example for different domain-specific perspectives and definitions. Even within a specific domain, the term ‘model’ may be shaped by the background, education and personal usage of individual scientists. Here we present a selection of definitions our editorial board (see Fig. 2) collected during personal interviews within the Cross Domain Fusion community.

Fig. 2
figure 2

Photo of the participatory mapping to approach the term ‘model’. Each tile represents an individual definition for the term ‘model’ from different scientists and disciplines

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Participatory mapping of the term ‘model’

Participatory mapping makes it possible to capture and document specific knowledge in a participatory way and is usually applied for spatially explicit data [8,9,10]. It can be a cost-effective option to visualize different views and perceptions [11]. In our case, a participatory mapping approach was applied not to collect geographically localized knowledge, but to disciplinary localized knowledge. Within the framework of three workshops within our interdisciplinary community, definitions of the ambiguous term ‘model’ were collected. We asked participants to state ad hoc their definition of ‘model’ either within their discipline or sub-discipline. We did not document all the affiliations to the disciplines to give a brief overview of mutual or deviant definitions. We cover the disciplines: computer sciences software engineering, (marine) geosciences, geophysics, geography, paleoceanography, climate modelling, oceanography, hydrology, medicine, systematic biology and political sciences.

In computer science all structured information can be seen as a model. Their shared building blocks are entities that have attributes and relationships. These can be used to describe program code, data structures, configurations, text documents, ontologies, software architectures and any number of domain-specific models; even the structure of models themselves can be modelled, hence they are called metamodels, as well as the relationship between models and their transformation, which are called megamodels. Models can be descriptive and prescriptive. A descriptive model describes how something is or comes to be, while a prescriptive model specifies how something will be and what is to be done to get there. Models can also be reconstructed or modified at runtime; these are called runtime models. They reflect the state of a (software) system and are descriptive models. The can be specified during software design, hence these are called design time models. Models can be represented in different ways, including the Essential Meta Object Facility (EMOF) that is used, among others, by the Unified Modeling Language (UML) as a foundation, which is itself a modeling notation, and description logic models, like the Web Ontology Language (OWL). In. contrast, a definition from the domain of political sciences defines a model as ‘a systematic abstraction of empirical data guided by specific theoretical assumptions’, leaving space for additional interpretation and abstraction level. Especially in Earth sciences, the term ‘model’ or ‘conceptual model’ is frequently used. These often define a ‘(conceptual) model’ as a synthesis of Earth system processes based on scientific observations and/or (sensor) data. These ‘models’ are then checked for their plausibility and probability based on the experience of the model creator. These models can be mathematical descriptions of real-world phenomena or visualizations of processes. Obviously, all mentioned definitions of the term ‘model’ are just a glimpse of the participatory mapping. A detailed presentation would go beyond the scope of this article. All findings from the participatory mapping will be implemented in the Dialogue:Wiki.

Discussion and conclusion

Many glossaries for interdisciplinary projects and approaches show the necessity of a repository of terminologies to find a common language by definitions [4]. From our experience, finding common definitions is often prevented by standard definitions within each discipline, which cannot be changed immediately. To overcome the hurdle of misunderstanding, we suggest setting up a repository of these ambiguous terminologies. The idea is the pairing of an easy-to-use GUI and the ability to access the different definitions of key terms. We hence created the Dialogue:Wiki. Our example ‘model’ shows the broad scale of the definition problem. We envisage a lively growth of the Dialogue:Wiki within the work on Cross Domain Fusion. The format is scalable and hence able to grow and adjust over the years ahead. With its ability to show the discourse between disciplines’ specific terminologies it will lead to a mutual understanding of different domains. This objective is more fruitful and realistic than finding one common definition of a term for multidisciplinary working groups. Such terms are often based on strong compromises and important insights, and knowledge may get lost. Nevertheless, we also see terms that can find a clear definition like ‘Cross Domain Fusion’. Also in this definition, the Dialogue:Wiki can act as a common ground for all interdisciplinary working groups.

In summary, the varying usage and definition of terminologies in individual disciplines is the result of scientific fields growing in parallel. Sometimes, there are good, bad and ugly aspects to this challenge in interdisciplinary work. Nevertheless, understanding your peer in an interdisciplinary team will foster any joint efforts and advance Cross Domain Fusion.