Development of Semantic Web-based Imaging Database for Biological Morphome

TL;DR

This paper presents a semantic web-based imaging database that efficiently manages large-scale biological microstructural images and metadata, enabling advanced visualization and analysis of morphological phenotypes.

Contribution

It introduces the RIKEN Microstructural Imaging Metadatabase using RDF and Linked Open Data, facilitating large-scale image management and detailed biological data representation.

Findings

Successfully managed vast microstructural imaging data

Enabled detailed morphological phenotype interpretation

Provided a user-friendly large-scale imaging viewer

Abstract

We introduce the RIKEN Microstructural Imaging Metadatabase, a semantic web-based imaging database in which image metadata are described using the Resource Description Framework (RDF) and detailed biological properties observed in the images can be represented as Linked Open Data. The metadata are used to develop a large-scale imaging viewer that provides a straightforward graphical user interface to visualise a large microstructural tiling image at the gigabyte level. We applied the database to accumulate comprehensive microstructural imaging data produced by automated scanning electron microscopy. As a result, we have successfully managed vast numbers of images and their metadata, including the interpretation of morphological phenotypes occurring in sub-cellular components and biosamples captured in the images. We also discuss advanced utilisation of morphological imaging data that can be promoted by this database.