AI for Data Rescue Workshop

Stuart Middleton

This workshop seeks to bring together researchers and practitioners working on data rescue from both the AI and citizen science communities.

Data rescue is a critical activity for any research area that requires access to historical data that is accurate and has good spatial and temporal coverage. Historical data, especially data that pre-dates 1900s, is typically recorded using typed or handwritten notes and logbooks in a wide variety of formats. Over the years, or centuries, documents are lost or damaged and the contextual metadata around data recordings often becomes separated from the data recordings themselves. To avoid losing this data many institutions, such as the UK Met Office, British Antarctic Survey and British Library, have run digitization projects where pages of historical documents are scanned into a digital image format. However, this work has now generated a big challenge of how to extract, or rescue, data from archives of 100,000's of scanned document pages so it can be used for scientific research such as climate science and weather forecasting. Excitingly, recent work in the areas of citizen science and AI, specifically image processing and natural language processing, are starting to effectively tackle this big challenge. One of the largest examples of citizen science is the 2020 [Rainfall Rescue] project involving the UK Met Office and University of Reading. This project developed a web platform for citizen science and was able to coordinate an incredible 16,000 volunteers over 16 days, manually transcribing over 66,000 pages of weather measurement data across a temporal span from 1677 to 1960. Recent examples of AI being used for data rescue includes the [Sphaera] project, using Large Language Models (LLMs) to extract pictures and diagrams from scanned historical texts, and the [GloSAT] project, using deep learning-based Region-based Convolutional Neural Networks (RCNN) models to detect table cells containing measurement data within scanned measurement logbooks. This workshop seeks to bring together researchers and practitioners working on data rescue from both the AI and citizen science communities, with the aim of sharing experience gained and lessons learnt between these often separate disciplines. We will discuss the key challenges AI and citizen science face today in the context of data rescue and attempt to signpost the current directions of travel that might overcome these challenges in the short and medium term. Workshop <a href="https://www.southampton.ac.uk/~sem03/AI-for-Data-Rescue-2024.html" title="https://www.southampton.ac.uk/~sem03/AI-for-Data-Rescue-2024.html" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">webpage</a>. This workshop is supported by the Natural Environment Research Council (grant NE/S015604/1) project GloSAT. This workshop is a AI UK-2024 fringe event.

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AI for Data Rescue Workshop

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AI for Data Rescue Workshop

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