Images annotated according to their content: a study on the description of data in image format in multiple domains

Data description is a fundamental step in Research Data Management (RDM). When it comes to images, the challenge is increased, as they have characteristics that differentiate them from other typologies. We conducted a study in which we obtained a set of 27 images described according to their content, by researchers of the projects where they are inserted. After obtaining the ground-truth that would support the analysis, we proceeded to two more stages of description, one through an automatic processing tool (Vision AI) and the other through researchers with no knowledge of the images. We concluded that the human description is more elucidative of the images' content, namely at a semantic level. In turn, the automatic tools enhance a more literal description. This study allowed us to reflect on the description of images in a research context and to discuss the potential of formal analysis and analysis of the semantic expression of images.

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필드 값
저자 Joana Rodrigues, Pedro Oliveira, Carla Teixeira Lopes
최종 업데이트 4월 29, 2024, 13:14 (UTC)
생성됨 6월 16, 2021, 14:52 (UTC)
Citation Rodrigues, J., Oliveira, P., Lopes, C. T. (2021). Images annotated according to their content: a study on the description of data in image format in multiple domains [dataset]. INESC TEC. https://doi.org/10.25747/szch-ve91
DOI https://doi.org/10.25747/szch-ve91
Date 31/07/2021
포맷 *.txt; *.jpg; *.png
Instrument Type Online forms
언어 EN
NameInstrument Google Forms
Project Elaboração de um dataset de imagens científicas anotadas segundo o conteúdo - Information Science Degree Internship Report
Sample The dataset contains 27 images from 6 researchers from different fields of work. A text file with the description is associated with each image.
Size 3,28 MB
Software text editor/reader; image editor/viewer
Spatial Coverage Porto
Temporal Coverage 26/04/2021 - 15/06/2021
타입 scientific images; *.txt documents