Category: Spatial Analysis

Spatial Analysis refers to the discovery of trends or patterns in data pertaining to spatial or geographical aspects of the data. Spatial analysis is often based on techniques of annotation of data, such as Georeferencing or Named Entity Recognition, and may lead to visualization or modeling in the form of maps (see Modeling).

Navigating the centuries with the ‘Mapping of the Republic of Letters’ project.

Navigating the centuries with the ‘Mapping of the Republic of Letters’ project.

In this post, we reach back in time to showcase an older project and highlight its impact on data visualization in Digital Humanities as well as its good practices to make different layers of scholarship available for increased transparency and reusability.  

Developed at Stanford with other research partners (‘Cultures of Knowledge’ at Oxford, the Groupe d’Alembert at CNRS, the KKCC-Circulation of Knowledge and Learned Practices in the 17th-century Dutch Republic, the DensityDesign ResearchLab), the ‘Mapping of the Republic of Letters Project’ aimed at digitizing and visualizing the intellectual community throughout the XVI and XVIII centuries known as ‘Republic of Letters’ (an overview of the concept can be found in Bots and Waquet, 1997), to get a better sense of the shape, size and associated intellectual network, its inherent complexities and  boundaries.

Below we highlight the different, interrelated
layers of making project outputs available and reusable on the long term (way before FAIR data became a widespread policy imperative!): methodological reflections, interactive visualizations, the associated data and its data model schema. All of these layers are published in a trusted repository and are interlinked with each other via their Persistent Identifiers.

[Click ‘Read more’ for the full post!]

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Approaching Linked Data

Approaching Linked Data

Introduction: Linked Data and Linked Open Data are gaining an increasing interest and application in many fields. A recent experiment conducted in 2018 at Furman University illustrates and discusses some of the challenges from a pedagogical perspective posed by Linked Open Data applied to research in the historical domain.

“Linked Open Data to navigate the Past: using Peripleo in class” by Chiara Palladino describes the exploitation of the search-engine Peripleo in order to reconstruct the past of four archeologically-relevant cities. Many databases, comprising various types of information, have been consulted, and the results, as highlighted in the contribution by Palladino, show both advantages and limitations of a Linked Open Data-oriented approach to historical investigations.

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Old Periodicals, a New Datatype and Spiderfied Query Results in Wikidata

Old Periodicals, a New Datatype and Spiderfied Query Results in Wikidata

Introduction: This blog post describes how the National Library of Wales makes us of Wikidata for enriching their collections. It especially showcases new features for visualizing items on a map, including a clustering service, the support of polygons and multipolygons. It also shows how polygons like the shapes of buildings can be imported from OpenStreetMap into Wikidata, which is a great example for re-using already existing information.

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The Migrant Letter Digitised: Visualising Metadata

Introduction: The article discusses how letters are being used across the disciplines, identifying similarities and differences in transcription, digitisation and annotation practices. It is based on a workshop held after the end of the project Digitising experiences of migration: the development of interconnected letters collections (DEM). The aims were to examine issues and challenges surrounding digitisation, build capacity relating to correspondence mark-up, and initiate the process of interconnecting resources to encourage cross-disciplinary research. Subsequent to the DEM project, TEI templates were developed for capturing information within and about migrant correspondence, and visualisation tools were trialled with metadata from a sample of letter collections. Additionally, as a demonstration of how the project’s outputs could be repurposed and expanded, the correspondence metadata that was collected for DEM was added to a more general correspondence project, Visual Correspondence.

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