# Structuring Reference Architectures for the Industrial Internet of Things
## 1 Introduction  
The expected disruptive developments collectively referred to as the Internet of Things (IoT) have drawn significant attention in many industries, disciplines and organizations. While the concrete benefits and requirements are still not sufficiently clear, the general agreement on its relevance and impact is undeniable. As a result, a large number of initiatives and consortia from industry and research have been formed to all set the de facto standards and best practices. Especially the manufacturing industry is actively involved in numerous activities related to this topic. Organizing this area and enabling effective discussions and design decisions are the targets of several standardization efforts. Many of them provide reference frameworks and architecture models. Reference frameworks in this context provide the necessary structure to transform the combined experiences and best practices, the opportunities of available technologies and the expected implications into understandable guidance for the involved stakeholders [1]. As a common understanding has not yet been reached, the current situation is characterized by the variety of proposed models and frameworks, created by groups of experts from different countries and domains. Whereas the goal of each approach is to overcome the current confusion, the huge amount of published models is again becoming a source of heterogeneity and misunderstanding. Newcomers and non-experts are overwhelmed by the amount of published recommendations and suggestions, contradicting terminology, inconsistent structuring and proposed best practices. The uncountable efforts intended to structure the domain have by now created another dimension of complexity. The thereby created barriers aggravate the adaption of crucial developments and decelerate further progress. Moreover, the rising difficulty to find and classify relevant information undermines the further propagation of the core principles. Therefore, a consistent alignment of the different frameworks and a structured organization of the main concepts are a pressing need, in order to create a sufficiently complete picture of the current state of the specification processes. Following the assumption that a single model can not cover all requirements, we annotated and interlinked the frameworks and models of the most influential initiatives, which cope with the digitization of the manufacturing domain. An openly available knowledge graph with self-defined and both human and machine-readable concepts, serves as the representation of the derived facts. Based on this grounded mapping of discovered relations, variances and commonalities we illustrate the different scopes and strengths. This paper contributes to the mentioned challenges by:  
1. Providing a methodology to structure, align and compare the various reference frameworks;
2. Presenting a collection of relevant concerns, their hierarchical structure and relationships;
3. Providing configurable visual views of the characteristics and relations between the concerns and the reference frameworks ([[http://i40.semantic-interoperability.org/sto-visualization/](http://i40.semantic-interoperability.org/sto-visualization/)]([http://i40.semantic-interoperability.org/sto-visualization/](http://i40.semantic-interoperability.org/sto-visualization/)));
4. Offering an analysis of the thereby gained insights, for example, frequently covered areas or inconsistencies, which need further attention from the community. The remainder of this paper is structured as follows: Section 2 gives an overview of other approaches to structure the observed frameworks and of surveys of the IIoT domain. The used methodology and data model is introduced in Section 3, followed by a description how the IIoT reference frameworks have been selected (Section 4) and an introduction of the most relevant ones in Section 5.