Lecture01

Knowledge Representation
in
Digital Humanities
Antonio Jiménez Mavillard
Department of Modern Languages and Literatures
Western University

Lecture 1
Knowledge Representation in Digital Humanities
Antonio Jiménez Mavillard
* Contents:
1. Why this lecture?
2. Justification and goals of the course
3. Chapter 1
4. Overview of the course
5. Assignment
6. Bibliography
2

Why this lecture?
* This lecture...
· presents this course, its justification,
contents and goals
· introduces the concepts of DH and KR,
and justify why the latter is so
important for the former
Antonio Jiménez Mavillard3

Justification and goals of the course
* Why DH?
· It is an emergent field
· Its rich heritage from Humanities
· The wide range of problems it addresses

* Skills in DH:
· Modelling
· Knowledge Representation
. Programming
. Natural Language Processing
· History

* Why KR?
· KR is becoming a key dimension of DH
· KR is the first and essential step for
further computer processing
· KR has the potential to change the way
humanities scholarship is done

* Why programming?
· It improves modelling and KR skills
· It allows to create new solutions for old
problems by providing a more versatile
way to manipulate data

* Why NLP?
· Most of the humanities disciplines rely on
texts
· Methods and tools for digitization and
processing of texts

* Why Historical Texts?
· Answer research questions from the
humanities

* Why Historical Texts?
· Similar to current media:
+ sms
+ forum posts
+ chats
+ social networkings
· Sentiment Analysis is applicable

* Why Sentiment Analysis?
· market trends
· recommendation systems
· targeted advertising

* Aim of the course:
· Abstract relevant aspects of a problem
· Model those relevant aspects into a
formal representation
· Solve formalized problems by means of
programming

References
“Digital Humanities Forum 2011.” N. p., n.d. Web. 16 June 2013.
Piotrowski, Michael. “Chapter 2: NLP and Digital Humanities.” Natural Language Processing for Historical Texts. [San
Rafael, Calif.]: Morgan & Claypool, 2012. Open WorldCat. Print.
Steven Bird, Ewan Klein, and Edward Loper. “Preface.” Natural Language Processing with Python. O’Reilly Media, 2009.
Print.
Svensson, Patrik. “Humanities Computing as Digital Humanities.” Digital Humanities Quarterly 003.3 (2009): n. pag. Print.
Svensson, Patrik. “The Landscape of Digital Humanities.” Digital Humanities Quarterly 4.1 (2010): n. pag. Web. 30 May
2013.

References
The Alliance of Digital Humanities Organizations et al. Digital Humanities 2012 - Conference Abstracts. Proceedings
(Komplette Ausgabe einer Konferenz etc.). 2008. Print.
Unsworth, John. “Knowledge Representation in Humanities Computing.” Inaugural E-humanities Lecture at the National
Endowment for the Humanities (2001): n. pag.

Chapter 1
Digital Humanities
and
Knowledge Representation
1. The landscape of Digital Humanities
2. Modelling and Knowledge Representation

Chapter 1
1 The landscape of Digital Humanities
1.1 Definition of DH
1.2 DH projects
1.3 Skills in DH
1.4 The DH community

Chapter 1
2 Modelling and Knowledge Representation
2.1 Definition of KR
2.2 KR in DH
2.3 Representing data and procedures

The landscape of Digital Humanities

Definition of Digital Humanities
* What is DH?
· No agreement in what DH is, open
debate in the discipline
· It descends from Humanities Computing:
formal representations of the human
record

* DH is a wide field that involves:
· data mining and visualization
· modelling and conceptualization
· formalization and representation
· programming
· conservation
· linguistics, history, literature...

* In the specific area of text processing:
· digitization of documents
+ conservation
· annotation with metadata
+ modelling
+ representation

* In the specific area of text processing:
· public access to collections
+ visualization
· text mining
+ data mining
· natural language processing
+ programming

* Some approaches to the concept:
· Susan Schreibman, Ray Siemens and John
Unsworth (2002):
+ preservation of physical artifacts
+ knowledge representation

· Andrew Prescott (2012):
+ conservation of culture through
transformation of original objects ==>
modelling and representation
+ interdisciplinar collaboration ==>
“universal science”

· Matthew G. Kirschenbaum (2010):
+ networking and collaboration
· Michael Piotrowski (2012):
+ traditional humanities &
new computer-based methods and tools

· Patrick Svensson (2010):
+ humanities and information technology
+ humanities 2.0
+ networking
+ decentralization of knowledge
+ interdisciplinarity and collaboration

· Tod Presner (2009):
+ print is no longer “the” medium
+ digital tools, techniques, new media
+ new production and dissemination of
knoledge

· Wikipedia:
+ intersection of computing and
humanities
+ digitization, curation, data mining...
+ linguistics, history, literature...
· Digital Humanities Quarterly journal:
+ still emerging field

* Some common ideas:
· intersection of computing and humanities
· conservation
· knowledge representation
· interdisciplinar collaboration

References
“Digital Humanities.” Wikipedia, the free encyclopedia 9 Aug. 2013. Wikipedia. Web. 12 Aug. 2013.
“DHQ: Digital Humanities Quarterly.” N. p., n.d. Web. 20 Dec. 2013.
Kirschenbaum, Matthew G. “What Is Digital Humanities and What’s It Doing in English Departments?” ADE Bulletin 150
(2010): n. pag.
Piotrowski, Michael. “Chapter 2: NLP and Digital Humanities.” Natural Language Processing for Historical Texts. [San
Rafael, Calif.]: Morgan & Claypool, 2012. Open WorldCat. Print.
Prescott, Andrew. “An Electric Current of the Imagination: What the Digital Humanities Are and What They Might
Become.” Journal of Digital Humanities (2012): n. pag. Web. 29 May 2013.

References
Schreibman, Susan, Ray Siemens, and John Unsworth, eds. “The Digital Humanities and Humanities Computing:
Introduction.” A Companion to Digital Humanities. Hardcover. Oxford: Blackwell Publishing Professional, 2004. Wiley
Online Library. Web. 3 June 2013. Blackwell Companions to Literature and Culture.
2013.
“The Digital Humanities Manifesto 2.0.” 2009.

Digital Humanities projects
* The Sylva Project

* The Sylva Project (http://sylvadb.com/)
The CulturePlex Lab, Western University
· Modelling and conceptualization
· KR: Graph databases
· Data visualization
· Data mining
· Collaboration

* The Printer's Devil Project

* The Printer's Devil Project
(http://ett.arts.uwo.ca/printersdevil/)
The Research Group for Electronic
Textuality and Theory, Western University
· Online communities
· Digitization
· Public access to collections

* Deception Detection

* Deception Detection
(http://publish.uwo.ca/~vrubin/lab/deceptdetect.html)
Language and Information Technology
Research Lab, Western University
· NLP
· Machine Learning

* The Proceedings of the Old Bailey, 1674·1913

* The Proceedings of the Old Bailey, 1674·1913
(http://www.oldbaileyonline.org/)
Universities of Hertfordshire and Sheffield
and the Open University
· Digitization
· NLP

* Alfred Escher

* Alfred Escher (http://alfred-escher.ch/en/)
Alfred Escher Foundation
· Digitization

* Extraction of structured knowledge from
ancient sources

* Extraction of structured knowledge from
ancient sources (http://www.eaqua.net/en/)
Institute for Computer Science, University
Leipzig
· Text mining
· NLP

Skills in Digital Humanities
* From the analisys of the DH's landscape:

* Most important skills in DH:

* Modelling
* Knowledge Representation
* Programming
* Natural Language Processing
* History

The Digital Humanities community
* Communities of Digital Humanists (“DHers”)
· ADHO (http://adho.org/)
+ ALLC
+ ACH
+ CSDH/SCHN
+ centerNet
+ aaDH
+ JADH

The Digital Humanities community
* Communities of Digital Humanists (“Dhers”)
· Others
+ HASTAC (http://www.hastac.org/)
+ CHAIN (http://www.arts-humanities.net/chain)
+ DARIAH (http://www.dariah.eu/)
+ Twitter (https://twitter.com/)

Modelling and Knowledge Representation

Definition of Knowledge Representation
* What is KR?
· KR is a sub-discipline in the field of
artificial intelligence, but also an
interdisciplinary methodology that
combines logic and ontology to produce
models of human understanding that are
tractable to computation (Unsworth,
2001).

* What is KR?
· In other words, it is the representation
of knowledge by means of a formal
language that enables automated
processing.

* KR entails:
1. abstraction and modelling
2. a formal language

* Abstraction and modelling
· substitution for the thing itself
· determine important aspects to represent
· ignore irrelevant details
· reasoning about the world rather than
taking action in it

* A formal language
· a language to say things about the
world
· a medium of human expression to
represent the model
· formalized morphology, syntax and
semantics
· computationally processable

References
Davis, Randall, Howard Shrobe, and Peter Szolovits. “What Is a Knowledge Representation?” AI Magazine 14.1 (1993): 17.
www.aaai.org. Web. 13 Aug. 2013.

* Representation of:
· cultural objects
· archival materials
+ printed-based (e.g. manuscripts)
+ visual-based (e.g. paintings)
+ audio-based (e.g. sound films)

* KR is a critical and self-conscious activity
* KR requires humanists
· to make explicit what they know about
the object
· to understand the relationship between
the object and its representation

* Examples:
· electronic edition of a text
· model of an artwork

* Electronic edition of a text
<text title:”Romeo and Juliet” author:”William Shakespeare”>
<act index:1>
  <scene index:1 title:”A public place”>
   <actor>Sampson</actor>:
   Gregory, o' my word, we'll not <note meaning:”take
   insults”>carry coals</note>.
   <actor>Gregory</actor>:
   No, for then we should be <note meaning:”coal
   miners”>colliers</note>.
   <actor>Sampson</actor>:
   I mean, if we be <note meaning:”angered”>in
   choler</note>, we'll <note meaning:draw our
   weapons>draw</note>.
   ...
  </scene>
</act>
</text>

* Model of an artwork

References
Schreibman, Susan, Ray Siemens, and John Unsworth, eds. “The Digital Humanities and Humanities Computing:
Introduction.” A Companion to Digital Humanities. Hardcover. Oxford: Blackwell Publishing Professional, 2004. Wiley
Online Library. Web. 3 June 2013. Blackwell Companions to Literature and Culture.

Representing data and procedures
* Data:
· Facts
· Items
· Objects
* Data:
· Facts
· Items
· Objects
* Procedures:
· Recipes
· Methods
· Algorithms

* Data representation:
· Bit
· Number
· String
· Abstract data type

* Data representation:
· Database
· Conceptual map
· Markup language
· Other formats: CSV, RGB...

* Procedure representation:
· Flow diagram
· Pseudocode
· Programming language implementation

* Data + Procedure = Problem solution
* Example:
Count how many words are written in plural
(ends with s) in a text.

* Data:
· text (list of words)
· word (string of letters)
· letter (single character)
· counter (number)

* Procedure:
1. The counter starts with 0
2. Separate the text in a list of words
3. For each word, get its last letter
4. If the last letter is the letter s,
increment the counter in 1
5. Repeat the process for the next word
6. The result is the value of the counter

* Result of the program

References
Miller, Bradley N, and David L Ranum. “Chapter 1: Introduction.” Problem Solving with Algorithms and Data Structures
Using Python. 2nd edition. Sherwood, Or.: Franklin, Beedle & Associates, 2011. Print.
Sperberg-McQueen, C. M., and David Dubin. “Data Representation.” DH Curation Guide (2012): n. pag. Print.

Overview of the course
* NLP with Python
· A natural language...
+ is used for communication among
humans (e.g. English, Spanish...)
+ is hard to pin down with explicit rules

* NLP with Python
· NLP to cover any kind of computer
manipulation of natural language
+ counting word frecuencies
+ “understanding” complete human
utterances

* NLP with Python
· Students will learn:
+ how to program
+ how to analyze/manipulate language
+ how data structures and algorithms are
used in NLP
+ how data is stored in standard
formats

* NLP with Python
· Why Python?
+ simple yet powerful programming
language
+ excellent functionality for NLP
+ highly readable for humans

* Contents
· Chapter 1. DH and KR
· Chapter 2. Principles of Computing
· Chapter 3. Fundamentals of Programming
· Chapter 4. Python Programming Language
· Chapter 5. Text Representation
· Chapter 6. Domain Modelling and Complex
Object Representation

* Contents
· Chapter 7. Raw Text Processing
· Chapter 8. Accessing Text Corpora and
Lexical Resources
· Chapter 9. NLP
· Chapter 10. Historial Texts
· Chapter 11. Sentiment Analysis

* Contents
· Chapter 12. Final Project Development
· Chapter 13. Final Project Presentations

Assignment
* Assignment 1: DH & KR
· Readings
+ What Is Digital Humanities and What's
it Doing in English Departments?
+ DH2012 – Conference Abstracts (one
project)

Assignment
* Assignment 1: DH & KR
· Project
+ From what you have learnt in this
lecture and the first reading, give
your own definition for DH
+ Pick up a project from the second
reading and explain what its knowledge
is about and how it is modelled

References
(2010): n. pag.

Bibliography
“Digital Humanities.” Wikipedia, the free encyclopedia 9 Aug. 2013. Wikipedia. Web. 12 Aug. 2013.
“Digital Humanities Forum 2011.” N. p., n.d. Web. 16 June 2013.
“DHQ: Digital Humanities Quarterly.” N. p., n.d. Web. 20 Dec. 2013.
(2010): n. pag.
Miller, Bradley N, and David L Ranum. Problem Solving with Algorithms and Data Structures Using Python. 2nd edition.
Sherwood, Or.: Franklin, Beedle & Associates, 2011. Print.

Bibliography
Piotrowski, Michael. Natural Language Processing for Historical Texts. [San Rafael, Calif.]: Morgan & Claypool, 2012. Open
WorldCat. Print.
Prescott, Andrew. “An Electric Current of the Imagination: What the Digital Humanities Are and What They Might
Become.” Journal of Digital Humanities (2012): n. pag. Web. 29 May 2013.
Schreibman, Susan, Ray Siemens, and John Unsworth, eds. A Companion to Digital Humanities. Hardcover. Oxford: Blackwell
Publishing Professional, 2004. Wiley Online Library. Web. 3 June 2013. Blackwell Companions to Literature and
Culture.
Sperberg-McQueen, C. M., and David Dubin. “Data Representation.” DH Curation Guide (2012): n. pag. Print.
Steven Bird, Ewan Klein, and Edward Loper. Natural Language Processing with Python. O’Reilly Media, 2009. Print.

Bibliography
Svensson, Patrik. “Humanities Computing as Digital Humanities.” Digital Humanities Quarterly 003.3 (2009): n. pag. Print.
2013.
“The Digital Humanities Manifesto 2.0.” 2009.

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