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A Comparative Analysis of Modeling Approaches for the Association of FAIR Digital Objects Operations

Nicolas Blumenröhr, Jana Böhm, Philipp Ost, Marco Kulüke, Peter Wittenburg, Christophe Blanchi, Sven Bingert, Ulrich Schwardmann

TL;DR

The paper analyzes how to link FAIR Digital Objects to their operational capabilities by evaluating three typing mechanisms—record typing, profile typing, and attribute typing—within a graph-based formal framework. It defines a set of quantitative and qualitative quality indicators to compare simplicity, efficiency, flexibility, and interoperability, and illustrates implementations through concrete examples. The findings reveal trade-offs among the models: record typing offers maximum granularity and simplicity, while profile and attribute typing provide greater flexibility and scalability with different interoperability implications. The work suggests that graph-based representations and compatible type systems can enable interoperable, scalable FDO ecosystems, with adoption guided by specific data environments and constraints.

Abstract

The concept of FAIR Digital Objects represents a foundational step towards realizing machine-actionable, interoperable data infrastructures across scientific and industrial domains. As digital spaces become increasingly heterogeneous, scalable mechanisms for data processing and interpretability are essential. This paper provides a comparative analysis of various typing mechanisms to associate FAIR Digital Objects with their operations, addressing the pressing need for a structured approach to manage data interactions within the FAIR Digital Objects ecosystem. By examining three core models -- record typing, profile typing, and attribute typing -- this work evaluates each model's complexity, flexibility, versatility, and interoperability, shedding light on their strengths and limitations. With this assessment, we aim to offer insights for adopting FDO frameworks that enhance data automation and promote the seamless exchange of digital resources across domains.

A Comparative Analysis of Modeling Approaches for the Association of FAIR Digital Objects Operations

TL;DR

The paper analyzes how to link FAIR Digital Objects to their operational capabilities by evaluating three typing mechanisms—record typing, profile typing, and attribute typing—within a graph-based formal framework. It defines a set of quantitative and qualitative quality indicators to compare simplicity, efficiency, flexibility, and interoperability, and illustrates implementations through concrete examples. The findings reveal trade-offs among the models: record typing offers maximum granularity and simplicity, while profile and attribute typing provide greater flexibility and scalability with different interoperability implications. The work suggests that graph-based representations and compatible type systems can enable interoperable, scalable FDO ecosystems, with adoption guided by specific data environments and constraints.

Abstract

The concept of FAIR Digital Objects represents a foundational step towards realizing machine-actionable, interoperable data infrastructures across scientific and industrial domains. As digital spaces become increasingly heterogeneous, scalable mechanisms for data processing and interpretability are essential. This paper provides a comparative analysis of various typing mechanisms to associate FAIR Digital Objects with their operations, addressing the pressing need for a structured approach to manage data interactions within the FAIR Digital Objects ecosystem. By examining three core models -- record typing, profile typing, and attribute typing -- this work evaluates each model's complexity, flexibility, versatility, and interoperability, shedding light on their strengths and limitations. With this assessment, we aim to offer insights for adopting FDO frameworks that enhance data automation and promote the seamless exchange of digital resources across domains.

Paper Structure

This paper contains 22 sections, 1 theorem, 6 figures.

Table of Contents

  1. Introduction
  2. Background
  3. Foundations of FDOs and the Core Model
  4. Problem Description
  5. Models for Associating FDOs with their Operations
  6. Typing Mechanisms
  7. Record Typing
  8. Profile Typing
  9. Attribute Typing
  10. Implementation Examples
  11. Record Typing in Interactive Computing Environments
  12. Profile Typing with Multiple Registries
  13. Attribute Typing with Operation FDOs
  14. Model Evaluation and Discussion
  15. Modeling the Association Mechanisms as Graphs
  16. ...and 7 more sections

Key Result

Theorem 5

The measures specified in Definition def: quality indicators are evaluated to the following quantities:

Figures (6)

  • Figure 1: The FDO Core model.
  • Figure 2: Typing Mechanisms. The conceptual typing mechanism to associate FDOs and their operations in analogy to OOP.
  • Figure 3: Record typing example. The conceptual workflow for interacting with an FDO based on record typing.
  • Figure 4: Profile typing example. The conceptual workflow for interacting with an FDO based on profile typing. Irrespective of the service architecture that is used to implement and execute operations such as the three registries in this example, the FDO service must infer the association between the profile of an FDO and its set of operations.
  • Figure 5: Attribute Typing example. The conceptual workflow for interacting with an FDO based on attribute typing. Irrespective of how the operation is finally performed (requested by the service in this example), the FDO service must infer the association based on the information record contents and reference of the data- and operation FDOs.
  • ...and 1 more figures

Theorems & Definitions (6)

  • Definition 1: Components
  • Definition 2: Graph Models
  • Definition 3
  • Definition 4: Measures for Quantitative Quality Indicators
  • Theorem 5: Evaluated Measures
  • proof