Digitizing, Curating and Visualizing Archival Sources of Maritime History: the case of ship logbooks of the nineteenth and twentieth centuries

Petrakis, Kostas; Samaritakis, Georgios; Kalesios, Thomas; Domingo, Enric García; Delis, Apostolos; Tzitzikas, Yannis; Doerr, Martin; Fafalios, Pavlos

doi:10.51829/drassana.28.649

Cited by 8 publications

(7 citation statements)

References 4 publications

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“…The curated data derived by this step, together with the original transcribed data, can be directly exploited by other applications before their transformation. For example, Petrakis et al [24] show how the data of ship logbooks of the 19 and 20 centuries, digitised and curated using FAST CAT, are visualised on a web-accessible map application called Ship Voyages. 3…”

Section: Data Curationmentioning

confidence: 99%

“…Research in this case typically starts with the definition of the kind and formal structure of the data that needs to be extracted and/or transcribed from one or more data sources, for evaluation and further analysis of aggregated facts. This type of research is noticed in a wide range of disciplines, including History (e.g., analysis of historical archival sources [2,24]; our use case in this article), Archaeology/Anthropology (e.g., isotope or DNA analysis of ancient bone remains found in a particular area [6]), or Biodiversity (e.g., analysis of data from mesocosm experiments [25]).…”

Section: Introductionmentioning

confidence: 99%

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Fafalios

Petrakis

Samaritakis

et al. 2021

J. Comput. Cult. Herit.

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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.

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Section: Data Curationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fast Cat

Fafalios

Petrakis

Samaritakis

et al. 2021

J. Comput. Cult. Herit.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The curated data derived by this step, together with the original transcribed data, can be directly exploited by other applications before their transformation. For example, the work in [24] shows how the data of ship logbooks of the nineteenth and twentieth centuries, digitised and curated using FAST CAT, are visualised on a web-accessible map application called Ship Voyages. 3…”

Section: Data Curationmentioning

confidence: 99%

“…Research in this case typically starts with the definition of the kind and formal structure of the data that needs to be extracted and/or transcribed from one or more data sources, for evaluation and further analysis of aggregated facts. This type of research is noticed in a wide range of disciplines, including History (e.g., analysis of historical archival sources [2,24]; our use case in this paper), Archaeology/Anthropology (e.g., isotope or DNA analysis of ancient bone remains found in a particular area [6]), or Biodiversity (e.g., analysis of data from mesocosm experiments [25]).…”

Section: Introductionmentioning

confidence: 99%

FAST CAT: Collaborative Data Entry and Curation for Semantic Interoperability in Digital Humanities

Fafalios,

Petrakis,

Samaritakis

et al. 2021

Preprint

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Descriptive and empirical sciences, such as History, are the sciences that collect, observe and describe phenomena in order 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 paper 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.

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“…A vast area of research in this field concerns the discovery, collection, organisation, presentation, and interpretation of information about historical events. This includes either the digitization (and then curation) of archival sources, like in [14,5] for the case of Maritime History, or the detailed documentation of cultural artefacts and related evidence [1], with the latter being the focus of this paper.…”

Section: Introductionmentioning

confidence: 99%

Towards Semantic Interoperability in Historical Research: Documenting Research Data and Knowledge with Synthesis

Fafalios,

Konsolaki,

Charami

et al. 2021

Preprint

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A vast area of research in historical science concerns the documentation and study of artefacts and related evidence. Current practice mostly uses spreadsheets or simple relational databases to organise the information as rows with multiple columns of related attributes. This form offers itself for data analysis and scholarly interpretation, however it also poses problems including i) the difficulty for collaborative but controlled documentation by a large number of users, ii) the lack of representation of the details from which the documented relations are inferred, iii) the difficulty to extend the underlying data structures as well as to combine and integrate data from multiple and diverse information sources, and iv) the limitation to reuse the data beyond the context of a particular research activity. To support historians to cope with these problems, in this paper we describe the Synthesis documentation system and its use by a large number of historians in the context of an ongoing research project in the field of History of Art. The system is Web-based and collaborative, and makes use of existing standards for information documentation and publication (CIDOC-CRM, RDF), focusing on semantic interoperability and the production of data of high value and long-term validity.

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Digitizing, Curating and Visualizing Archival Sources of Maritime History: the case of ship logbooks of the nineteenth and twentieth centuries

Cited by 8 publications

References 4 publications

Fast Cat

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FAST CAT: Collaborative Data Entry and Curation for Semantic Interoperability in Digital Humanities

Towards Semantic Interoperability in Historical Research: Documenting Research Data and Knowledge with Synthesis

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