Machine actionable metadata models

Abstract

Community-developed minimum information checklists are designed to drive the rich and consistent reporting of metadata, underpinning the reproducibility and reuse of the data. These reporting guidelines, however, are usually in the form of narratives intended for human consumption. Modular and reusable machine-readable versions are also needed. Firstly, to provide the necessary quantitative and verifiable measures of the degree to which the metadata descriptors meet these community requirements, a requirement of the FAIR Principles. Secondly, to encourage the creation of standards-driven templates for metadata authoring, especially when describing complex experiments that require multiple reporting guidelines to be used in combination or extended. We present new functionalities to support the creation and improvements of machine-readable models. We apply the approach to an exemplar set of reporting guidelines in Life Science and discuss the challenges. Our work, targeted to developers of standards and those familiar with standards, promotes the concept of compositional metadata elements and encourages the creation of community-standards which are modular and interoperable from the onset.

Modeling community standards for metadata as templates makes data FAIR

“…Because CEDAR provides an editor for creating these machine-actionable metadata templates, we typically refer to them as “CEDAR templates.” However, an important driver of our work is that templates are independent of any software system. In fact, the templates can be created by using simple text editors or by using more advanced applications developed by other groups 21 .…”

“…However, an important driver of our work is that templates are independent of any software system. In fact, the templates can be created by using simple text editors or by using more advanced applications developed by other groups 21 .…”

“…Traditional minimal information checklists cannot be processed by computers in a meaningful way. Most checklists exist as textual documents, written with all the ambiguity and imprecision of natural language 21 . These checklists enumerate the things that need to be said about experiments and their data, but they are not in a form that enables a computer to verify that a checklist has been followed; they are designed primarily so that humans can attempt to tick boxes to indicate that something has been mentioned about the given topic.…”

EGAsubmitter: A software to automate submission of nucleic acid sequencing data to the European Genome-phenome Archive

“…When developing EGAsubmitter, our design choices regarding user input aimed at keeping them as simple as possible, specifically we followed the metadata structure that is required by EGA and their specific dictionaries for different entries. For this reason we used YAML and a single CSV and we did not implement a dedicated layer to manage metadata adopting a specific library for it ( Chalk, 2016 ; Batista et al, 2022 ); future developments would definitely focus on integrating EGA requirements with an existing metadata model, striving to keep the user interface as easy as possible but at the same time reaching better interoperability and quality of annotations.…”

“…However, much less work has been devoted to making data deposition efficient and error-free. There are proposals for shared solutions to define and share experimental metadata ( González-Beltrán et al, 2014 ; Johnson et al, 2021 ), but right now different data repositories usually adopt their own ontologies and rules to create and manage metadata and a global consensus still has not been reached ( Batista et al, 2022 ). We postulate that the same level of automation and minimal human intervention that is now required to run state-of-the-art analytical pipelines ( Zhang and Jonassen, 2020 ) should be reached also in the context of data deposition.…”