lecture01

Knowledge Representationin

Digital HumanitiesAntonio Jiménez Mavillard

Department of Modern Languages and LiteraturesWestern University

Lecture 1

Knowledge Representation in Digital HumanitiesAntonio 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

Knowledge Representation in Digital HumanitiesAntonio 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 Humanitiesand

Knowledge Representation

1. The landscape of Digital Humanities2. 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



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



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



* Some approaches to the concept: · Patrick Svensson (2010): + humanities and information technology + humanities 2.0 + networking + decentralization of knowledge + interdisciplinarity and collaboration



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


Definition of Digital Humanities* Some approaches to the concept: · 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.


ReferencesSchreibman, 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


http://sylvadb.com/


* 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


http://ett.arts.uwo.ca/printersdevil/


* Deception Detection



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


http://publish.uwo.ca/~vrubin/lab/deceptdetect.html


* 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 · Public access to collections · NLP


http://www.oldbaileyonline.org/


* Alfred Escher



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


http://alfred-escher.ch/en/

Digital Humanities projects* 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


http://www.eaqua.net/en/

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


http://adho.org/

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/)


http://www.hastac.org/

http://www.arts-humanities.net/chain

http://www.dariah.eu/

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).


Definition of Knowledge Representation

* 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


Definition of Knowledge Representation* 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.




Knowledge Representation in Digital Humanities

* 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)


Representing data and procedures* 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



Antonio Jiménez Mavillard69


* 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


Overview of the course* 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


Overview of the course* 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.




lecture01

Technology

humanities computing

humanities disciplines

data knowledge representation

way humanities scholarship

inaugural ehumanities

definition of dh

dh projects

concepts of dh