Digitization of historical records has produced a significant amount of data for analysis and interpretation. A critical challenge is the ability to relate historical information across different archives to allow for the data to be framed in the appropriate historical context. This paper presents a real-world case study on historical information integration and record matching with the goal to improve the historical value of archives containing data in the period 1800 to 1920. The archives contain unique information about Métis and Indigenous people in Canada and interactions with European settlers. The archives contain thousands of records that have increased relevance when relationships and interconnections are discovered. The contribution is a record linking approach suitable for historical archives and an evaluation of its effectiveness. Experimental results demonstrate potential for discovering historical linkage with high precision enabling new historical discoveries.
The Paterno' Castello Principi di Biscari Archive, preserved at the State Archives of Catania, amongst one of the most crucial family archives, is, in the light of a digital historical methodology, the best computable historical heritage for demonstrating the applicability of applying an HTR tool, such as Transkribus, to digitised historical documents.
Historians and archivists often find and analyze the occurrences of query words in newspaper archives, to help answer fundamental questions about society. But much work in text analytics focuses on helping people investigate other textual units, such as events, clusters, ranked documents, entity relationships, or thematic hierarchies. Informed by a study into the needs of historians and archivists, we thus propose ClioQuery, a text analytics system uniquely organized around the analysis of query words in context. ClioQuery applies text simplification techniques from natural language processing…
Web archives preserve unique and historically valuable information. They hold a record of past events and memories published by all kinds of people, such as journalists, politicians and ordinary people who have shared their testimony and opinion on multiple subjects. As a result, researchers such as historians and sociologists have used web archives as a source of information to understand the recent past since the early days of the World Wide Web. The typical way to extract knowledge from a web archive is by using its search functionalities to find and analyse historical content. This can be …
Investigating Correlations of Inter-coder Agreement and Machine Annotation Performance for Historical Video Data
Leibniz Information Centre for Science and Technology (TIB)（莱布尼茨科学技术信息中心（TIB））；L3S Research Center（L3S研究中心）；University of Marburg（马尔堡大学）；German Broadcasting Archive (DRA)（德国广播档案馆（DRA））
Web archives are a historically valuable source of information. In some respects, web archives are the only record of the evolution of human society in the last two decades. They preserve a mix of personal and collective memories, the importance of which tends to grow as they age. However, the value of web archives depends on their users being able to search and access the information they require in efficient and effective ways. Without the possibility of exploring and exploiting the archived contents, web archives are useless. Web archive access functionalities range from basic browsing to a…
University of Torino（都灵大学）；Stuttgart Media University（斯图加特媒体大学）；University of Mannheim（曼海姆大学）
The progressive digitization of historical archives provides new, often domain specific, textual resources that report on facts and events which have happened in the past; among these, memoirs are a very common type of primary source. In this paper, we present an approach for extracting information from Italian historical war memoirs and turning it into structured knowledge. This is based on the semantic notions of events, participants and roles. We evaluate quantitatively each of the key-steps of our approach and provide a graph-based representation of the extracted knowledge, which allows to…
Layout-Aware OCR for Black Digital Archives with Unsupervised Evaluation
Department of Computer Science and Engineering（计算机科学与工程系）；The Pennsylvania State University（宾夕法尼亚州立大学）；Department of Industrial and Manufacturing Engineering（工业与制造工程系）
This essay aims to bid analogue historians assume that digitisation is the first step to creating historical heritage based on the new language of Science: Computer Science. As we know, Humanities disciplines cannot easily be encapsulated in a few understandable numbers and names. However, historians must boost Artificial Intelligence (such as Transkribus) and Neural Networks to let the Machine infer meaning from the digitised historical primary source and become the most powerful tool to help historians understand what happened in the Past. Historians (collaborating with data scientists, expe…
