A vast area of research in historical science concerns the analysis of historical archival sources. This involves activities such as digitizing the historical sources, usually using spreadsheets or simple relational databases, and then analyzing the transcribed data using a range of methods depending on the kind of data and the type of research question that needs to be answered. In this paper, we describe the process of digitizing, curating and visualizing original archival sources of maritime history, a process done in the context of a European (ERC) project called SeaLiT. In particular, we present a set of innovative tools that have been implemented for supporting historians in transcribing the original sources and curating the transcribed data as well as a web application that visualizes the curated data on an interactive map. The overall process is demonstrated for the case of 16 original ship logbooks from the nineteenth and twentieth centuries kept by seven archives in Greece and Spain.

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Descriptive and empirical sciences, such as History, are the sciences that collect, observe and describe phenomena to explain them and draw interpretative conclusions about influences, driving forces and impacts under given circumstances. Spreadsheet software and relational database management systems are still the dominant tools for quantitative analysis and overall data management in these these sciences, allowing researchers to directly analyse the gathered data and perform scholarly interpretation. However, this current practice has a set of limitations, including the high dependency of the collected data on the initial research hypothesis, usually useless for other research, the lack of representation of the details from which the registered relations are inferred, and the difficulty to revisit the original data sources for verification, corrections or improvements. To cope with these problems, in this article we present FAST CAT, a collaborative system for assistive data entry and curation in Digital Humanities and similar forms of empirical research. We describe the related challenges, the overall methodology we follow for supporting semantic interoperability, and discuss the use of FAST CAT in the context of a European (ERC) project of Maritime History, called SeaLiT , which examines economic, social and demographic impacts of the introduction of steamboats in the Mediterranean area between the 1850s and the 1920s.