Workflows
Workflows are often overlooked in the arts and humanities but are essential for research. Workflows describe specific research scenarios to provide researchers with a clear step-by-step guide to help them integrate different tools and methods to achieve their goals.
ATRIUM develops and shares workflows that help researchers integrate digital methods into their work. These guides outline how to navigate the research data lifecycle from start to finish.
ATRIUM workflows are hosted and built using templates from the SSH Open Marketplace . Browse the ATRIUM Workflow catalogue below:
3 workflows
-
ATR (4) - Layout Analysis
Layout analysis is a computer vision tasks that allows us to identify the structure of a document and localize the lines of text. We generate a series of x and y coordinates corresponding to regions/lines on the image, which we associate to a corresponding labels.
Text line segmentation is mandatory in most ATR systems, but without a good line segmentation, transcription performances will not be sufficient. For example, lines can be missed, read in the wrong order, or even broken down into several lines.
Synonyms: “segmentation”, “zoning”, “document analysis”, “optical layout analysis”.
More info -
Automatic Text Recognition Roadmap
Work-in-progress: this workflow is not finalised yet.
Automatic Text Recognition (ATR) uses Artificial Intelligence (AI), in particular machine learning (ML), to extract text from a scanned image. It encompasses two main techniques: Optical Character Recognition (OCR), extracting text from printed documents, and Handwritten Text Recognition (HTR), exracting text from manusripts.
More info
This workflow presents the main steps of an ATR workflow and how to integrate it in your research project. -
LLM-Powered Mapping of Keywords of a Research Article to Linked Data
Suppose you have a research article which is written in a language other than English and you have a set of keywords for that article. How could you grasp the main topics of the article from the keywords? First, you would like to translate them, but this is not a trivial task since words can be ambiguous, and finding the exact sense requires an understanding of the whole article! Moreover, suppose you want to link your article to other resources, for example other articles that share the same topic. Now suppose you want to make your resource accessible so that people can find keywords in different languages. This workflow provides a solution to all this scenarios, since it gives you a way to map keywords to linked data (Wikidata and DBPedia entities).
More info