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Data visualisation

Data visualisation looks at the different technologies and tools that a researcher can use to visualise their data and enhance the communication of their findings

Resources

  • Photogrammetry 3D Digitisation

    EN
    This resource is an introduction to the photogrammetry technique to capture visual data about cultural heritage assets and produce associated 3D models.
    Authors
    • Karina Rodriguez Echavarria
    • Myrsini Samaroudi
    • Nicola Schiavottiello
    Read more
  • Sentiment Analysis with 'syuzhet' using R

    EN
    This lesson teaches you how to obtain and analyse narrative texts for patterns of sentiment and emotion. The 'syuzhet' sentiment analysis algorithm, along with the programming language R, will be used, demonstrating the techniques to allow learners to follow along.
  • Digitisation with 360 Degrees Photography

    EN
    This resource is an introduction to 360 degrees panorama photography. It explores different types of panoramic representations and examples of 360 degree panoramas in the cultural heritage domain. Practical advice and step by step guidance on how to capture data and process them is also included in order to produce and publish 360 degrees panorama images.
    Authors
    • Karina Rodriguez Echavarria
    • Nicola Schiavottiello
    Read more
  • A Basic Introduction to Geographic Information Systems (GIS)

    EN
    This pathfinder provides an introduction to Geographic Information Systems (GIS), covering analysis and visualization. It explains various spatial methods and each method is explained with a definition, practical examples and links to free resources online for further reading and exploration.
  • Digital Exhibition Design

    EN
    This resource provides guidance on digital practices to curate interactive experiences through a set of practical exercises. The resource aims to support GLAM’s researchers and practitioners to engage with their audiences through the design of multimedia applications, while making use of appropriate frameworks and tools.
  • Digitisation Methods for Material Culture

    EN
    This resource is an introduction to Digitisation Methods for Material Culture. The resource explores basic topics with regards to the study of material culture, while also looking at types of media as means to communicate and share information about it, as well as digitisation methods to capture material culture data.
    Authors
    • Karina Rodriguez Echavarria
    • Myrsini Samaroudi
    • Nicola Schiavottiello
    Read more
  • Creating Stories with 3D Data on the Web

    EN
    This resource provides guidance on how to use digital storytelling, deploying 3D data, annotations and combining media to enable users to access and explore information about digital heritage assets over the web.
    Authors
    • Karina Rodriguez Echavarria
    • Nicola Schiavottiello
    Read more
  • Historical Farm and People Registry in Iceland

    EN
    This presentation outlines the aim and scope of the Historical Farm and People Registry project, explains the development process and problems encountered on the way, and demonstrates a use case for the ‘final’ product.
  • Making an Interactive Web Application with R and Shiny

    EN
    This lesson demonstrates how to build a basic interactive web application using Shiny, a library (a set of additional functions) for the programming language R. In the lesson, you will design and implement a simple application, consisting of a slider which allows a user to select a date range, which will then trigger some code in R, and display a set of corresponding points on an interactive map.
  • Introduction to Map Warper

    EN
    This lesson from Programming Historian introduces basic use of Map Warper for historical maps. It guides you from upload to export, demonstrating methods for georeferencing and producing visualizations.
  • Digging for Gold - Knowledge Extraction from Text

    EN
    This three-day international training school in Knowledge Extraction from Text from the CLS Infra project offered a crash course in how to “Dig for Gold” in a corpus of texts. From Stylometry to Natural Language Processing, learners will be able to follow along using 'plug and play' tools, while also getting a brief introduction to Python and R.
    Authors
    • Guillermo Marco Remon
    • Alvaro Pérez
    • Artjoms Šeļa
    Read more
  • Regression Analysis with Scikit-learn (part 2 - Logistic)

    EN
    This lesson is the second in a two-part lesson focusing on regression analysis. It provides an overview of logistic regression, how to use Python (Scikit-learn) to make a logistic regression model, and a discussion of interpreting the results of such analysis.