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"Culture & Technology" European Summer University in Digital Humanities
University of Leipzig

All About Data – Exploratory Data Modelling and Practical Database Access

One of the main challenges in Digital Humanities is to determine which data actually is relevant to a given research question, and how this data can be stored, analysed and processed. Modern database technologies provide technical solutions to data storage and access, but they require that data be organised in specific ways. The workshop will focus on identifying the data objects of interest, on deriving a database schema from these objects, and on querying relational or graph database systems.

Relational databases organize their data in flat tables. SQL is the standard query language to search for and extract data from the database. The technology is mature, there are many excellent database systems available, and most programming languages and application programs provide easy access to relational databases.

Graph databases organize data objects as unique information nodes linked via named arcs. Cypher is a popular query language for graph databases; its queries are compact but easy to read. In graph databases, the database schema evolves with the data inserted into the database. This makes graph databases ideal for exploratory data modelling.

In the workshop the technologies will be introduced with sample data from a digital humanities field, e.g. discourse analysis. In hands-on exercises, participants will work on their own data, or with the sample data provided. We will discuss ways of asking questions to the data and then try to express them in the query languages.

The first week will cover data modelling in graph databases. Given a collection of documents, we will identify the objects of interest. Typical questions we have to answer concern the objects' required or optional properties, whether we can we find common features, and what type of relationships exist between the objects. We will formulate queries using the visualisation provided by the graphical user interface.

The second week will cover relational databases. We will develop an entity relationship model of our data and systematically convert this into a relational database schema. We will then learn to formulate SQL queries, including aggregate functions. Finally, we will have a look at accessing relational databases from external applications, e.g. statistics packages or programming languages.

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2022

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2021

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2020

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2019

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    • XML-TEI document encoding, structuring, rendering and transformation
    • Hands on Humanities Data Workshop - Creation, Discovery and Analysis
    • Manuscripts in the Digital Age: XML-Based Catalogues and Editions
    • Digital Annotation and Analysis of Literary Texts with CATMA 6.0
    • Compilation, Annotation and Analysis of Written Text Corpora. Introduction to Methods and Tools
    • Searching Linguistic Patterns in Text Corpora for Digital Humanities Research
    • All About Data – Exploratory Data Modelling and Practical Database Access
    • Stylometrie
    • Humanities Data and Mapping Environments
    • Images of Image Machines. Theory and Practice of Interpretable Machine Learning for the Digitial Humanities
    • An Introduction to Neural Networks for Natural Language Processing - Applications and Implementation
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2018

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2017

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2016

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2015

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2014

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2013

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2012

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2010

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2009

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Leipzig

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What the ESU means to me

ESU in the Media

ESU 2019 Experiences (DARIAH-EU)
ESU 2018 Experiences (CLARIN-D)
ESU 2017 (CLARIN-D Blog)
CLARIN-D at ESU 2015 (YouTube)
CLARIN-D ESU 2015 (YouTube)
Mephisto 97.6 10.07.13
Campus Online 10.08.2012
Mephisto 97.6 26.07.2010
infotvleipzig 26.07.2010
In India 03.09.2010

Reviews

INFOtheka: Review of ESU DH 2009
INFOtheka: Review of ESU DH 2012
Infoclio.ch: Review of ESU DH
2013

Publications

Multimodal Analysis of “well”

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