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Professor: [http://people.epfl.ch/frederic.kaplan Frédéric Kaplan]
Professor: [http://people.epfl.ch/frederic.kaplan Frédéric Kaplan]


Assistant: [https://people.epfl.ch/raphael.barman Raphaël Barman]
Assistants: Alexander Rusnak, Tristan Karch, Tommy Bruzzese


Rooms: Wednesday (CM1113) and Thursday (BC03)
Rooms: Wednesday (CM1110) and Thursday (BC03)


==Links==
==Links==
*[https://moodle.epfl.ch/course/view.php?id=15281 Moodle]
*[https://www.dropbox.com/scl/fi/j0xoe45dp0km4do41kk9c/FDH_Textbook.pdf?rlkey=mr5hdplu5ai7qts3tk0n4k5a0&dl=0 Textbook]
*[https://www.dropbox.com/scl/fo/tu5waw0623hcp4537lx6u/AKx-eznaH6BRddo1goaF7OE?rlkey=jiewdfpk5ysyv92m1817sk5qc&st=01697apo&dl=0 Slides]
*[https://annuel2.framapad.org/p/fdh Framapad]
*[https://annuel2.framapad.org/p/fdh Framapad]
*[https://pov-dev.up.railway.app/ Application Parcels of Venice (Dev version)]
*[https://pov.up.railway.app/ Application Parcels of Venice (Stable version)]
*[[Projects]]
*[[Projects]]
* Sources
** [https://www.dropbox.com/scl/fi/oekkk9ts0pnjyiqaezz7m/Toponomastica-Veneziana.pdf?rlkey=wfky7ht9ckxa1w1qo6c69bo98&dl=0 Tassini PDF], [https://www.dropbox.com/scl/fi/lfu8ugk25re333gca65g7/Toponomastica-Veneziana_with_pages_delim.txt?rlkey=fouht7678vs102918hn9fuxs1&dl=0 Tassini OCR]
** [https://www.dropbox.com/scl/fo/netqhm40dyw046withu8q/AJO_CPupJwuLw4Zvg1JF2jc?rlkey=ldswph81gb0n9xgi5qzz1b1i8&dl=0 Guido Commerciale PDF]
** [https://onlinebooks.library.upenn.edu/webbin/metabook?id=sanudodiary Sanudo PDF]
<!--  
<!--  
*[https://conference.timemachine.eu Time Machine Conference 2018]
*[https://conference.timemachine.eu Time Machine Conference 2018]
Line 29: Line 36:


==Plan ==
==Plan ==
=== Part I : Core concepts ===
=== Part I : Concepts ===


==== Week 1 : What are Digital Humanities? ====
==== Week 1 : What are Digital Humanities? ====
16.09 (2h) Welcome and Introduction to the course
* FDH-0 (1h)  Introduction to the course and Digital Humanities, structure of the course. Introduction to Framapad with a simple exercise. Principle of collective note talking and use in the course. State of the Digital Humanities at EPFL, in Switzerland and in Europe. [https://tube.switch.ch/videos/e422bc1a Video recording link].


17.09 (4h) What are Digital Humanities? What is their object of study?
11.09 :
* FDH-1-1 (1h) What Are Digital Humanities :  Digital Humanities, Digital Studies, Humanities Computing and Studies about Digital Culture. Digital Humanism vs. Digital Humanities. Why digital methods tend to dissolve traditional disciplinary frontiers. A focus on practice. Translation issues. [https://tube.switch.ch/videos/f9472d5e Video recording link].
 
* FDH-1-2 (1h) Digital Humanities as a field : Big Data Digital Humanities vs Small Data Digital Humanities. The 3 circles.  Exercise on relationship between elements in Digital Culture schema. [https://tube.switch.ch/videos/867c0795 Video recording link].
(2h) Welcome and Introduction to the course
* FDH-1-3 (2h) Big Data of the Past. [https://tube.switch.ch/videos/c2a637c2 Video recording link].
* FDH-0 (1h)  Introduction to the course and Digital Humanities, structure of the course. Introduction to Framapad and Slido with a simple exercise. Principle of collective note talking and use in the course. State of the Digital Humanities at EPFL.
 
12.09 :
 
(4h) What are Digital Humanities? What is their object of study?
* FDH-1-1 (1h) What Are Digital Humanities :  Digital Humanities, Digital Studies, Humanities Computing and Studies about Digital Culture. Digital Humanism vs. Digital Humanities. Why digital methods tend to dissolve traditional disciplinary frontiers. A focus on practice. Translation issues.
* FDH-1-2 (1h) Digital Humanities as a field : Big Data Digital Humanities vs Small Data Digital Humanities. The 3 circles.  Exercise on relationship between elements in Digital Culture schema.
* FDH-1-3 (2h) Big Data of the Past. Data acceleration regime. Inferred Patterns. Redocumentation. Fictional Spaces.


==== Week 2 :  Patrimonial Capitalism and Commons  ====
==== Week 2 :  Patrimonial Capitalism and Commons  ====


23.09 :   
18.09 :   
* FDH 1-4 Patrimonial Capitalism (1h) Introduction to the DH circle linking the digitisation of sources, their processing, their analysis, visualisation and the creation of societal value (insight, culture) leading ultimately to the digitisation of new sources. Presentation of some sustainable DH circles (genealogy, image banks). Patrimonial capitalism and the risk of monopolistic companies. Parallelism with the race for sequencing the Human Genome. [https://tube.switch.ch/videos/e02cfdd0 Video recording link].
 
* FDH 1-5 The Commons (1h) What are the commons ? What is the public domains ? History and evolution. Copyright overreaching. Frontal collision. Governing with the commons [https://tube.switch.ch/videos/79fa0d4e Video recording link].
* FDH 1-4 Patrimonial Capitalism (1h) Introduction to the DH circle linking the digitisation of sources, their processing, their analysis, visualisation and the creation of societal value (insight, culture) leading ultimately to the digitisation of new sources. Presentation of some sustainable DH circles (genealogy, image banks). Patrimonial capitalism and the risk of monopolistic companies. Parallelism with the race for sequencing the Human Genome.  
 
* FDH 1-5 The Commons (1h) What are the commons ? What is the public domains ? History and evolution. Copyright overreaching. Frontal collision. Governing with the commons.
 
19.09 :


24.09
* FDH 1-6 Anatomy of a large-scale project (1h) Venice Time Machine. European Time Machine.  
* FDH 1-6 Anatomy of a large-scale project (1h) Venice Time Machine. European Time Machine. [https://tube.switch.ch/videos/93a6e77b Video recording link (pre-recorded)]. [https://tube.switch.ch/videos/61b8d58f Video recording link (live)]
* Venice Datasets
* Past projects presentation. [https://tube.switch.ch/videos/64542a60 Video recording link].
* FDH 1-7 Projects. [https://tube.switch.ch/videos/86de590d Video recording link (pre-recorded)]. [https://tube.switch.ch/videos/e9c89123 Video recording link (pre-recorded)].


=== Part II : Pipelines ===
=== Part II : Pipelines ===
Line 55: Line 69:
==== Week 3:  Digitisation  ====
==== Week 3:  Digitisation  ====


30.09  
25.09 :
* (1h) Introduction to the Digitization Process. Document digitization as a problem of conversion of dimensions. Digitization is logistic optimization. Alienation. Digitization on demand.  
 
* (1h) Questions and answers about projects
* FDH 1-7 Venice Data presentation (Paul Guhennec)
 
26.09 :
 
* (2h) FDH 2-1 Introduction to the Digitization Process. Document digitization as a problem of conversion of dimensions. Digitization is logistic optimization. Alienation. Digitization on demand. FDH 2-2 Document Structure. General presentation of the pipeline. Content and Structure. Circulation. Standards. Open Annotation Data Model. Shared Canvas. IIIF.
 
* (2h)  Project presentation by prof and TA.
 
==== Week 4: Writing Systems and Text Encoding  ====
 
2.10 :
 
(2h) FDH 2-3 : Writing Systems
 
3.10 :
- (2h) FDH 2-4 : Text Encoding
 
* (2h)  [[Projects]] presentations. 5' per project with max 3 slides. Write to Tristan before the course. You can find a group using the [https://annuel2.framapad.org/p/fdh framapad].
 
==== Week 5: Text Processing and Understanding ====
 
9.10 :
 
(2h) FDH 2-5 Text Processing : Diachronic and synchronic analysis. n-grams, TF-IDF, Topic Modeling, Word Space Models and Word embeddings (2h)
 
10.10 :
 
(2h) FDH 2-6 Text Understanding : Close, surface, distant and machine reading, Information extraction, Named Entities, Resources, Large-Scale Projects (2h)  Work on Project (2h).
 
==== Week 6:  Images  ====
 
16.10 :
 
(2h) FDH 2-7 : Image systems.
 
17.10 :
 
(2h) FDH 2-8 : Image processing  (2h) Work on project.


01.10
(FDH 2-9 : Image understanding not done this year)
* (1h) Standards. Open Annotation Data Model. Shared Canvas.
* (3h) [[Projects]] presentations. 5' per project with max 3 slides. Fill out the [[Projects#Groups|group table]] before the course. You can find a group using the [https://annuel2.framapad.org/p/fdh framapad].


==== Week 4: Projects ====


07.10 (2h) Presentation of the [[Gallica wrapper]].
==== Week Off  ====


08.10 (4h) Presentation of [http://bibnum.bnf.fr/alto_prod/documentation/alto_prod.html BNF XML ALTO] and [https://www.primaresearch.org/tools/PAGELibraries PAGE XML], [https://transkribus.eu/Transkribus/ Transkribus] and [http://www.robots.ox.ac.uk/~vgg/software/via/ VGG Image annotator] (VIA). Work on [[Projects|projects]]
23.10 :


==== Week 5: Image (2D) Pipeline ====
No course


14.10 (2h) Pipeline for Artworks photographs. Image banks and phototarchives. Photography as documentation. Scanning techniques for photographs. Segmentation. Visual similarity vs visual connections.
24.10 :


15.10 (4h)  Introduction to deep learning analysis of image similarity.  Exercises with the Replica database and search engine. 5 mn presentation. Work on projects.
No Course


==== Week 6: Maps (2D) Pipeline ====
==== Week 7: Maps ====


21.10 (2h) What are cartographic documents. Exercice on ancient maps. History of cartography. Odometry. Triangulation. Coordinate systems. Metric systems. Projection. Cadaster. Aerial photography.
30.10 :


22.10 (1-2h) Introduction to GIS. Points, Lines, Polygons. Coordinate Sytems. [[Georefencing exercice]] (2-3h) Work on [[Projects]].
(2h) FDH-2-10 Map systems


==== Week 7: Object/Environment (3D) Pipeline ====
31.10 :


26.10 (2h) Pipeline for 3D spaces. Modelling vs Sampling : Part I : Modelling. Photogrammety. Demo Sketchup. Model-based Procedural methods. Architectural grammars. Class I and Class II elements. The question of realism. Part II : Sampling. Principles of Phtogrammetry
(2h) FDH-2-11 Map processing (Remi Petitpierre and Beatrice Vaienti) presentations
(2h) Work on project


27.10 (2h) Photogrammetric tutorial. Video to 3D pipelines. [[3D modelisations]] of past years. (2h) Introduction to the Mirror Worlds concept
==== Week 8: 3D Models  ====


=== Part II : Algorithms ===
06.11 :
(2h) FDH-2-12: 3D Models Systems and Encoding
07.11 :


==== Week 8 : Deep Learning algorithms ====
(2h) FDH-2-13: 3D Models Processing : Alex Rusnak Thesis
  (2h)Work on project


02.11 (2h) A panorama of Deep learning methods. Successes. Fundamental principles. Neurons. Receptive Fields. Hierarchical representation / texture. Gradient descent. Credit Assignment Path. Most important architectures. Convolutional neural networks. Recurrent neural networks. Siamese Networks. Word2Vec. Generative Adversarial Networks. Style Transfer. Importance of Deep learning for Digital Humanities. Can Deep Learning networks and Big Data of the Past lead to new forms of Artificial Intelligence ?
=== MidTerm Presentations ===


03.11 (2h) Computer vision and deep learning tutorial (Sofia). Conditional Random Fields (CRF) tutorial. Both are available on [https://github.com/dhlab-epfl/fdh-tutorials this Github repository].
13.11 :


==== Week 9 : Project  ====
No course


10.11 (2h) '''Midterm presentation''' (10%)
14.11 Midterm presentations


{|class="wikitable"
{|class="wikitable"
! style="text-align:center;"| Time
! style="text-align:center;"| Time
! First student name
! Second student name
! Third student name
! Project name
! Project name
|-
|-
|10:15-10:30
|10:20-10:40
|
| Group 8
|
|-
|
|10:40-11:00
|
| Group 9
|-
|11:00-11:20
| Group 7
|-
|-
|10:30-10:45
|11:20-11:40
|
| Group 6
|
| -
|
|-
|-
|10:45-11:00
|11:40-12:00
|
| Group 3
|
|}
| -
 
|
{|class="wikitable"
! style="text-align:center;"| Time
! Project name
|-
|-
|11:15-11:30
|13:15-13:35
|
| Group 2
|
| -
|
|-
|-
|11:30-11:45
|13:35-13:55
|
| Group 5
|
| -
|
|-
|-
|13:55-14:15
|  Group 4
|-
|14:15-14:35
|  Group 1
|-
|14:35-14:55
|  Group 10
|}
|}


=== Part III : Knowledge modelling and processing ===
==== Week 9 : Semantic modelling, Rule systems, simulations and parallel worlds  ====
20.11 :
- (1h) FDH-3-0 Summary of the concept viewed so far and introduction to part 3


11.11  (4h) Project development
- (1h) FDH-3-1 Semantic modelling. RDF, Metaknowledge


==== Week 10 : Knowledge modelling ====
21.11 :


18.11 (2h) The beauty of Knowledge modelling. Tables. Databases. Semantic web, Ontologies, URI, RDF, CIDOC-CRM, How to code event, places and influence. Metaknowledge. The Hypergraph
(2h) FDH 3-2 Universal Ontologies  


19.11  (4h) (a) Exercise in semantic modelling and inference (Maud). Graph writing. Presentation of some interesting ontologies: SKOS, VIAF, Geonames, TGN, W3C Time Ontology. SPARQL and SPARQL endpoint. Exercice on SPARQL endpoints: DBPedia [http://dbpedia.org/sparql], Talk of Europe  [http://linkedpolitics.ops.few.vu.nl/yasgui/index.html], Persée [http://data.persee.fr/explorer/ ], Le Temps ARchive [http://iccluster052.iccluster.epfl.ch:8899/sparql], available on [https://github.com/dhlab-epfl/fdh-tutorials this Github repository].  (b) Work on projects
(2h) FDH 3-3 Rule systems, simulations and parallel worlds


-- Project plan and milestones deliverable on the Wikipage of each project (10%)


=== Part III : Platform management ===
==== Week 10 : Non conceptual knowledge systems and topological data science  ====


27.11 :


==== Week 11 : Work on Project ====
(2h) FDH 3-4 Non conceptual knowledge systems


28.11 :


25.11 (2h) Work on project
(2h) Work on Projects / Publication of Study Guide
(2h) Work on Projects


26.11 (4h) Work on project
=== Part IV : Platforms ===


==== Week 12 : Data, User and Bot  Management  ====
==== Week 12 : Data, User and Bot  Management  ====


02.12 (2h) Data Management  : FAIR principle, Creative Commons,  Data Management models, Sustainability,  Right to Forgotten. Management of uncertainty, incoherence and errors. Iconographic principle of precaution
4.12 :
 
(2h) Study Guide Discussion
 
5.12 :
 
(2h) Work on Project
 
(2h) Work on Project


03.12 (2h) User Management : Part I: Persona. Part II: Motivation and onboarding dynamics. Three case studies: Twitter. Quora. Wikipedia. Part III: "Wisdom" of the crowds. Collectivism vs Liberalism. Open source as a form of liberalism for engineering. The ambiguous of fork. Part IV: The "power" of the crowds. Mechanical Turk. Crowdflower. Crowdfunding (2h) Bot Management : Three case studies on bot management : Twitter, Wikipedia, Google.
==== Course Exam and Project work  ====


==== Week 13 : Work on projects  ====
11.12 In class exam


09.12 (2h) Work on project
12.12 Work on project


10.12 (4h) work on project
==== Final Week : Project Presentation ====


-- Deadline for GitHub repository (10%)
18.12


-- Deadline for Report writing (40%)
-- Due: GitHub repository (10%)


==== Week 14 : Exam  ====
-- Due: Report writing (40%)


16.12 (2h) Final project presentation (20%)
19.12


17.12 (2h) ----
(4h) Final project presentation  (20%)


<!--
{|class="wikitable"
==References==
! style="text-align:center;"| Time
-->
! Project Name
|-
| 10:15 - 10:40
| Group 1
|-
| 10:40 - 11:05
| Group 2
|-
| 11:05 - 11:30
| Group 3
|-
| 11:30 - 11:55
| Group 4
|-
| 11:55 - 12:20
| Group 5
|}
 
{|class="wikitable"
! style="text-align:center;"| Time
! Project Name
|-
| 1:15 - 1:40
| Group 6
|-
| 1:40 - 2:05
| Group 7
|-
| 2:05 - 2:30
| Group 8
|-
| 2:30 - 2:55
| Group 9
|-
| 2:55 - 3:20
| Group 10
|}


== Resources ==
== Resources ==
Line 190: Line 298:
*[[Feature matching code]]
*[[Feature matching code]]
*[https://www.mediawiki.org/wiki/Help:Formatting Wiki Syntax]
*[https://www.mediawiki.org/wiki/Help:Formatting Wiki Syntax]
*[https://annuel2.framapad.org/p/r.664b6addb1d73a5242943f306814e898 Introduction to Rhino and Grasshopper]


==Assessment and Notation grid ==
==Assessment and Notation grid ==




* 2 oral presentations (30%)
* (Group work) 2 oral presentations (30%)
** 1 midterm presentation of the project (10%)
** 1 midterm presentation of the project (10%)
** 1 final discussing the project result (20%)
** 1 final discussing the project result (20%)
* Written deliverables (Wiki writing) (40%)
* (Group work) Written deliverables (Wiki writing) (20%)
* Quality of the project (30%)
* (Group work) Quality of the project (30%)
* (Individual work) Exam on Course Content (20%)


=== 2 collective oral presentations (30%) ===
=== 2 collective oral presentations (30%) ===
Line 222: Line 332:
* + 0.5 The students answer well to the questions
* + 0.5 The students answer well to the questions


=== Written deliverables (Wiki writing) (40%) ===
=== Written deliverables (Wiki writing) (20%) ===


* Projet plan and milestones (10%) (>300 words)
* Project plan and milestones (5%) (>300 words)
* Historical introduction to the source(s) (5%) (>200 words)
* Motivation and description of the deliverables (5%) (>300 words)
* Detailed description of the methods (10%) (>500 words)
* Detailed description of the methods (5%) (>500 words)
* Quality assessment  (10%) (>300 words)
* Quality assessment and discussion of limitations (5%) (>300 words)
* Motivation and description of the website (5%) (>200 words)
 
The indicated number of words is a minimal bound. Detailed description can in particular be extended if needed.


=== Production  (30%) ===
=== Production  (30%) ===
Line 234: Line 345:
* Quality of the realisation 20%
* Quality of the realisation 20%
* Code deliverable on github  10%
* Code deliverable on github  10%
=== Exam on Course Content  (20%) ===
* A series of questions on the course to ensure the core concepts are understood.

Latest revision as of 10:48, 17 December 2024

Welcome to the wiki of the course Foundation of Digital Humanities (DH-405).

Contact

Professor: Frédéric Kaplan

Assistants: Alexander Rusnak, Tristan Karch, Tommy Bruzzese

Rooms: Wednesday (CM1110) and Thursday (BC03)

Links

Summary

This course gives an introduction to the fundamental concepts and methods of the Digital Humanities, both from a theoretical and applied point of view. The course introduces the Digital Humanities circle of processing and interpretation, from data acquisition to new understandings and services. The first part of the course presents the technical pipelines for digitising, analysing and modelling written documents (printed and handwritten), maps, photographs and 3d objects and environments. The second part of the course details the principles of the most important algorithms in particular deep learning approaches (for document analysis and image generation) and knowledge modelling (semantic web, ontologies, graph databases). The third part of the course focuses on platform management from the points of view of data, users and bots. Students will practise the skills they learn by engaging in a class-wide collective project.

Plan

Part I : Concepts

Week 1 : What are Digital Humanities?

11.09 :

(2h) Welcome and Introduction to the course

  • FDH-0 (1h) Introduction to the course and Digital Humanities, structure of the course. Introduction to Framapad and Slido with a simple exercise. Principle of collective note talking and use in the course. State of the Digital Humanities at EPFL.

12.09 :

(4h) What are Digital Humanities? What is their object of study?

  • FDH-1-1 (1h) What Are Digital Humanities : Digital Humanities, Digital Studies, Humanities Computing and Studies about Digital Culture. Digital Humanism vs. Digital Humanities. Why digital methods tend to dissolve traditional disciplinary frontiers. A focus on practice. Translation issues.
  • FDH-1-2 (1h) Digital Humanities as a field : Big Data Digital Humanities vs Small Data Digital Humanities. The 3 circles. Exercise on relationship between elements in Digital Culture schema.
  • FDH-1-3 (2h) Big Data of the Past. Data acceleration regime. Inferred Patterns. Redocumentation. Fictional Spaces.

Week 2 : Patrimonial Capitalism and Commons

18.09 :

  • FDH 1-4 Patrimonial Capitalism (1h) Introduction to the DH circle linking the digitisation of sources, their processing, their analysis, visualisation and the creation of societal value (insight, culture) leading ultimately to the digitisation of new sources. Presentation of some sustainable DH circles (genealogy, image banks). Patrimonial capitalism and the risk of monopolistic companies. Parallelism with the race for sequencing the Human Genome.
  • FDH 1-5 The Commons (1h) What are the commons ? What is the public domains ? History and evolution. Copyright overreaching. Frontal collision. Governing with the commons.

19.09 :

  • FDH 1-6 Anatomy of a large-scale project (1h) Venice Time Machine. European Time Machine.
  • Venice Datasets

Part II : Pipelines

Week 3: Digitisation

25.09 :

  • FDH 1-7 Venice Data presentation (Paul Guhennec)

26.09 :

  • (2h) FDH 2-1 Introduction to the Digitization Process. Document digitization as a problem of conversion of dimensions. Digitization is logistic optimization. Alienation. Digitization on demand. FDH 2-2 Document Structure. General presentation of the pipeline. Content and Structure. Circulation. Standards. Open Annotation Data Model. Shared Canvas. IIIF.
  • (2h) Project presentation by prof and TA.

Week 4: Writing Systems and Text Encoding

2.10 :

(2h) FDH 2-3 : Writing Systems

3.10 :

- (2h) FDH 2-4 : Text Encoding

  • (2h) Projects presentations. 5' per project with max 3 slides. Write to Tristan before the course. You can find a group using the framapad.

Week 5: Text Processing and Understanding

9.10 :

(2h) FDH 2-5 Text Processing : Diachronic and synchronic analysis. n-grams, TF-IDF, Topic Modeling, Word Space Models and Word embeddings (2h)

10.10 :

(2h) FDH 2-6 Text Understanding : Close, surface, distant and machine reading, Information extraction, Named Entities, Resources, Large-Scale Projects (2h) Work on Project (2h).

Week 6: Images

16.10 :

(2h) FDH 2-7 : Image systems.

17.10 :

(2h) FDH 2-8 : Image processing (2h) Work on project.

(FDH 2-9 : Image understanding not done this year)


Week Off

23.10 :

No course

24.10 :

No Course

Week 7: Maps

30.10 :

(2h) FDH-2-10 Map systems

31.10 :

(2h) FDH-2-11 Map processing (Remi Petitpierre and Beatrice Vaienti) presentations (2h) Work on project

Week 8: 3D Models

06.11 :

(2h) FDH-2-12: 3D Models Systems and Encoding 07.11 :

(2h) FDH-2-13: 3D Models Processing : Alex Rusnak Thesis 

  (2h)Work on project

MidTerm Presentations

13.11 :

No course

14.11 Midterm presentations

Time Project name
10:20-10:40 Group 8
10:40-11:00 Group 9
11:00-11:20 Group 7
11:20-11:40 Group 6
11:40-12:00 Group 3
Time Project name
13:15-13:35 Group 2
13:35-13:55 Group 5
13:55-14:15 Group 4
14:15-14:35 Group 1
14:35-14:55 Group 10

Part III : Knowledge modelling and processing

Week 9 : Semantic modelling, Rule systems, simulations and parallel worlds

20.11 :

- (1h) FDH-3-0 Summary of the concept viewed so far and introduction to part 3

- (1h) FDH-3-1 Semantic modelling. RDF, Metaknowledge

21.11 :

(2h) FDH 3-2 Universal Ontologies

(2h) FDH 3-3 Rule systems, simulations and parallel worlds


Week 10 : Non conceptual knowledge systems and topological data science

27.11 :

(2h) FDH 3-4 Non conceptual knowledge systems

28.11 :

(2h) Work on Projects / Publication of Study Guide (2h) Work on Projects

Part IV : Platforms

Week 12 : Data, User and Bot Management

4.12 :

(2h) Study Guide Discussion

5.12 :

(2h) Work on Project

(2h) Work on Project

Course Exam and Project work

11.12 In class exam

12.12 Work on project

Final Week : Project Presentation

18.12

-- Due: GitHub repository (10%)

-- Due: Report writing (40%)

19.12

(4h) Final project presentation (20%)

Time Project Name
10:15 - 10:40 Group 1
10:40 - 11:05 Group 2
11:05 - 11:30 Group 3
11:30 - 11:55 Group 4
11:55 - 12:20 Group 5
Time Project Name
1:15 - 1:40 Group 6
1:40 - 2:05 Group 7
2:05 - 2:30 Group 8
2:30 - 2:55 Group 9
2:55 - 3:20 Group 10

Resources

Assessment and Notation grid

  • (Group work) 2 oral presentations (30%)
    • 1 midterm presentation of the project (10%)
    • 1 final discussing the project result (20%)
  • (Group work) Written deliverables (Wiki writing) (20%)
  • (Group work) Quality of the project (30%)
  • (Individual work) Exam on Course Content (20%)

2 collective oral presentations (30%)

Midterm presenting the project planning (10%)

10' max presentation + 5' questions

Notation grid :

  • The presentation contains a planning (4)
  • + 0.5 The slides are clear and well presented
  • + 0.5 The oral presentation is dynamic and fluid
  • + 0.5 The planning is realistic.
  • + 0.5 The students answer well to the questions

Final discussing the project result (20%)

10-15' for presentation and 5-10' for questions

Notation grid :

  • The presentation presents the results of the project (4)
  • + 0.5 The slides are clear and well presented
  • + 0.5 The oral presentation is dynamic and fluid
  • + 0.5 The results are well discussed
  • + 0.5 The students answer well to the questions

Written deliverables (Wiki writing) (20%)

  • Project plan and milestones (5%) (>300 words)
  • Motivation and description of the deliverables (5%) (>300 words)
  • Detailed description of the methods (5%) (>500 words)
  • Quality assessment and discussion of limitations (5%) (>300 words)

The indicated number of words is a minimal bound. Detailed description can in particular be extended if needed.

Production (30%)

  • Quality of the realisation 20%
  • Code deliverable on github 10%


Exam on Course Content (20%)

  • A series of questions on the course to ensure the core concepts are understood.
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