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Big data

Big data refers to extremely large and/or complex datasets, and the methods used to manage and analyse them

Resources

  • Text Analysis - Linguistics Meets Data Science

    EN
    What are the differences between a data scientist and a corpus linguist? This course provides an overview of the different perspectives on language and different types of tools that can be used for text analytics. It also introduces topic modelling and sentiment analysis as approaches to textual data.
  • The Learning Curve in Sharing Data with the EHRI Project

    EN
    A partnership between Kazerne Dossin and EHRI was established to enable sharing of metadata with a broader audience. This partnership resulted in changes to the practices of cataloguing archival materials within Kazerne Dossin. Using the example of the Lewkowicz family collection, this article focuses on the revolution Kazerne Dossin went through while standardising descriptions, and on the tools EHRI provided to optimise the workflow for collection holding institutes.
    Authors
    • Dorien Styven
    • Marius Caragea
    • Veerle Vanden Daelen
    Read more
  • Data Journalism and AI: New frontiers in investigation and storytelling

    EN
    Data is now an indispensable part of investigative work and storytelling for journalists and newsrooms. Computational methods and artificial intelligence are making their way to newsrooms more than ever before, and promise to open up new opportunities for journalists, as well as new challenges. This talk provides an overview of how data and Artificial Intelligence can be used in the journalism workflow, investigative reporting and storytelling.
  • What Can I Do With This Messy Spreadsheet? Converting from Excel Sheets to Fully Compliant EAD-XML files

    EN
    Many Galleries, Libraries, Archives, and Museums (GLAMs) face difficulties sharing their collections metadata in standardised and sustainable ways, meaning that staff rely on more familiar general purpose office programs such as spreadsheets. However, while these tools offer a simple approach to data registration and digitisation they don’t allow for more advanced uses. This blogpost from EHRI explains a procedure for producing EAD (Encoded Archival Description) files from an Excel spreadsheet using OpenRefine.
  • Using Named Entity Recognition to Enhance Access to a Museum Catalog

    EN
    This blog discusses the applicability of services such as automatic metadata generation and semantic annotation for automatic extraction of person names and locations from large datasets. This is demonstrated using Oral History Transcripts provided by the United States Holocaust Memorial Museum (USHMM).
  • Spatial Queries and the First Deportations from Slovakia

    EN
    In the late 1930s, just before war broke in Europe, a series of chaotic deporations took place expelling thousands of Jews from what is now Slovakia. As part of his research, Michel Frankl investigates the backgrounds of the deported people, and the trajectory of the journey they were taken on. This practical blog describes the tools and processes of analysis, and shows how a spatially enabled database can be made useful for answering similar questions in the humanities, and Holocaust Studies in particular.
  • quod: A Tool for Querying and Organising Digitised Historical Documents

    EN
    This blog post from EHRI introduces 'quod' (querying OCRed documents), a prototype Python-based command line tool for OCRing and querying digitised historical documents, which can be used to organise large collections and improve information about provenance. To demonstrate its use in context, this blog takes the reader through a case study of the International Tracing Service, showing workflows and the steps taken from start to finish.
  • EHRI in TEITOK

    EN
    This blog examines TEITOK, which is a corpus framework used as an alternative to Omeka. TEITOK is centered around texts and is similar to the Omeka interface – both allow you to search through the documents, and display the transcription. The main difference is that Omeka treats the transcription as an object description, whereas TEITOK not only shows that a word appears in a document, but also where it appears and how it is used.
  • Computational Museology

    EN
    This keynote lecture delivered at the DARIAH Annual Event 2021 by Sarah Kenderdine explores how computation has become ‘experiential, spatial and materialized; embedded and embodied’.