# The CLEAR Principle: organizing data and metadata into semantically meaningful types of FAIR Digital Objects to increase their human explorability and cognitive interoperability

## TL;DR

This paper introduces the CLEAR Principle to improve human usability and cognitive interoperability of FAIR data and metadata through semantic units and FAIR Digital Objects.

## Contribution

The CLEAR Principle is proposed as a new framework to enhance human explorability and cognitive interoperability of data and metadata.

## Key findings

- Semantic units structure knowledge graphs into meaningful subgraphs represented as FAIR Digital Objects.
- CLEAR supports cognitive interoperability by organizing data into levels of representational granularity.
- User interfaces based on semantic units can optimize human exploration of knowledge graphs.

## Abstract

Ensuring the FAIRness (Findable, Accessible, Interoperable, Reusable) of data and metadata is an important goal in both research and industry. Knowledge graphs and ontologies have been central in achieving this goal, with interoperability of data and metadata receiving much attention. This paper argues that the emphasis on machine-actionability has overshadowed the essential need for human-actionability of data and metadata, and provides three examples that describe the lack of human-actionability within knowledge graphs.

The paper propagates the incorporation of cognitive interoperability as another vital layer within the European Open Science Cloud Interoperability Framework and discusses the relation between human explorability of data and metadata and their cognitive interoperability. It suggests adding the CLEAR Principle to support the cognitive interoperability and human contextual explorability of data and metadata. The subsequent sections present the concept of semantic units, elucidating their important role in attaining CLEAR. Semantic units structure a knowledge graph into identifiable and semantically meaningful subgraphs, each represented with its own resource that constitutes a FAIR Digital Object (FDO) and that instantiates a corresponding FDO class. Various categories of FDOs are distinguished. Each semantic unit can be displayed in a user interface either as a mind-map-like graph or as natural language text.

Semantic units organize knowledge graphs into levels of representational granularity, distinct granularity trees, and diverse frames of reference. This organization supports the cognitive interoperability of data and metadata and facilitates their contextual explorability by humans. The development of innovative user interfaces enabled by FDOs that are based on semantic units would empower users to access, navigate, and explore information in CLEAR knowledge graphs with optimized efficiency.