courses/AIProj.md

 ---
 layout: course
 
-title: Projekt zur Künstlichen Intelligenz
+title: AI Research Project
 instructors:
     - mkohlhase
-
+    - frabe
 semesters: 
-    - WS17/18
-    - SS17 
-    - WS16/17
     - SS16
+    - WS16/17
+    - SS17 
+    - WS17/18
+    - SS18 
+    - WS18/19
+    - SS19 
+    - WS19/20
+    - SS20 
+    - WS20/21
+    - SS21 
+    - WS21/22
+    - SS22 
 ---
+The KWARC group offers guided research projects in Artificial Intelligence either at the Bachelor's level or the Master's level.
+The topics of these projects are individually tailored to the student's interest and the
+projects themselves will be supervised closely by senior KWARC members.
+
+Projects will consist of a research/development project commensurable in size with the
+ECTS points awarded, and end in a research report that documents it. 
 
-The KWARC group (Wissensrepräsentation und Verarbeitung) conducts research in knowledge representation and reasoning techniques with a view towards applications in knowledge management. 
-We extend techniques from formal methods so that they can be used in settings where formalization is either infeasible or too costly. 
-We concentrate on developing techniques for marking up the structural semantics in technical documents. 
-This level of markup allows for offering interesting knowledge management services without forcing theauthor to formalize the document contents. 
-In contrast to courses with fixed topics, project topics are defined individually.
+Even though administratively, AI Projects are tied to particular semesters, the research
+itself can be conducted at any time, and we are quite flexible in scheduling.  
 
-See the [KWARC home page](http://kwarc.info) for a general introduction to the research and [the KWARC research topics list](http://gl.kwarc.info/kwarc/thesis-projects) for expemplary topics. 
+See the [KWARC research page](/research/) for a general introduction to the research
+conducted in the KWARC group and
+[the KWARC research topics list](http://gl.kwarc.info/kwarc/thesis-projects) for
+exemplary topics.

courses/KRMT.md

 ---
 layout: course
-
-title: Logik-Basierte Wissensrepräsentation für Mathematisch/Technisches Wissen
+title: Logic-Based Representation of Mathematical/Technical Knowledge
 instructors:
-    - mkohlhase
-
+  - mkohlhase
+  - frabe
 semesters:
-    - SS17
+    - SS17 
+    - SS18 
+    - SS19 
+    - SS20 
+    - SS21 
+    - SS22 
+    - SS23 
+    - SS25 
 ---
 
-Dieser Kurs behandelt Grundlagen der Mathematik, Modulare Formalisierung in
-Theoriegraphen, Narrative Strukturen in informellen mathematisch/technischen Dokumenten,
-Formalisierung von Logiksprachen in Metalogiken.
-
-Da wir nur wenige Studenten erwarten, wollen wir diesen Kurs sehr interaktiv und
-Projektorientiert aufbauen. Im wesentlichen werden wir gemeinsam mathematisches Wissen und
-Beschreibungssprachen in [OMDoc/MMT](http://uniformal.github.io) formalisieren.
+This course covers the foundations of mathematics, modular formalizations in theory graphs,
+narrative structures in informal mathematical/technical documents, and the formalization
+of logical languages in meta-logical frameworks. 
 
-Materialien:
+This is (tradictionally) a small course, so we can make it very interactive and
+project-like. The contents are split between 
+* lectures, where we discuss the concepts and
+* labs, where we jointly formalize mathematical knowledge and representation languages in
+  [OMDoc/MMT](http://uniformal.github.io).
 
-* [Course Notes (Computational Logic)](http://kwarc.info/teaching/KRMT)
-* [Tutorial zur Formalisierung](https://gl.mathhub.info/Teaching/KRMT/blob/master/source/tutorial/mmt-math-tutorial.pdf)
-* [Formalisierungen des letzten Kurses](https://gl.mathhub.info/Teaching/KRMT/tree/master/source)
+Materials:
 
+* [KRMT on StudOn](https://www.studon.fau.de/crs4499012.html)
+* [Course on zoom](Https://fau.zoom.us/j/65839665250)
+* [Videos on FAU.tv](Https://www.fau.tv/course/id/3065)
+* [Course Notes, Resources](http://kwarc.info/teaching/KRMT)
+* [Formalization Tutorialz](https://gl.mathhub.info/Tutorials/Mathematicians/blob/master/tutorial/mmt-math-tutorial.pdf)
+* [Formalizations of the last years](https://gl.mathhub.info/Teaching/KRMT/tree/master/source)
+ 

courses/ai1.md

 ---
 layout: course
 
-title: Künstliche Intelligenz I
+title: Artificial Intelligence I
 instructors:
     - mkohlhase
 
 semesters:
     - WS16/17
     - WS17/18
+    - WS18/19
+    - WS19/20 
+    - WS20/21 
+    - WS21/22 
+    - WS22/23 
+    - WS23/24
+    - WS24/25 
 ---
 
+This course is the first part of a two-semester introduction into the field of Artificial
+Intelligence (AI). It introduces the foundations of symbolic AI, in particular: 
+
+* Agent Models as foundation of AI
+* Logic Programming in Prolog
+* Heuristic Search as a methdod for problem solving
+* Adversarial Search (automating board games) via heuristic search
+* Constraint Propagation
+* Logical Languages for knowledge representation
+* Inference and automated theorem proving
+* Classical Planning
+* Planning and Acting in the real world. 
+
+The course follows the book
+[Artificial Intelligence: A Modern Approach](https://www.pearson.com/us/higher-education/program/Russell-Artificial-Intelligence-A-Modern-Approach-3rd-Edition/PGM156683.html)
+by Stuart Russell und Peter Norvig. We use the third edition. 
+
+The course materials (e.g. [Course Notes](http://kwarc.info/teaching/AI/notes.pdf) or
+[Assignments](http://kwarc.info/teaching/AI/assignments.pdf), but also old exams and
+(some) solutions) are [here](http://kwarc.info/teaching/AI/). 
+
+The course forum on [StudOn](https://studon.fau.de) is an important source for advice and
+discussions. The instrutor and tutors try to be present to help. 
+
+### German Version (possibly out of date)
+
 Diese Vorlesung ist der erste Teil einer zwei-semestrigen Einführung in die Künstlichen
 Intelligenz (KI). Sie beschäftigt sich mit den Grundlagen der symbolischen KI,
 insbesondere
 
 * Agentenmodelle als  Grundlagen der KI
+* Logisches Programmieren in Prolog
 * Heuristische Suche als Methode zum Problemlösen
-* Constraint-Propagierung
+* Adversarielle Suche (Strategiespiele)
+* Probleme unter Rand- oder Nebenbedingungen (Constraint Propagation)
 * Logische Sprachen zur Wissensrepräsentation,
-* Inferenz
-* Automatisches Planen
+* Inferenz und Logisches Programmieren
+* Klassisches Planen
+* Planen und Agieren in der realen Welt
 
 Die Vorlesung folgt dem Buch
 [Artificial Intelligence: A Modern Approach](https://www.pearson.com/us/higher-education/program/Russell-Artificial-Intelligence-A-Modern-Approach-3rd-Edition/PGM156683.html)
@@ -28,3 +64,8 @@ von Stuart Russell und Peter Norvig. Wir verwenden die dritte Ausgabe.
 Die Kursmaterialien (z.B. [Course Notes](http://kwarc.info/teaching/AI/notes.pdf) oder
 [Aufgaben](http://kwarc.info/teaching/AI/assignments.pdf), aber auch alte Klausuren)
 finden sich in [hier](http://kwarc.info/teaching/AI/). 
+
+Diskussionen finden auf dem
+[StudOn](https://studon.fau.de) statt. Dies ist
+eine wichtige Quelle von Rat und Tat. Wir bemühen uns, auf dem Forum präsent zu sein, und
+schnell auf Fragen zu antworten. Also das Forum abonnieren! 

courses/ai2.md

 ---
 layout: course
 
-title: Künstliche Intelligenz II
+title: Artificial Intelligence II
 instructors:
     - mkohlhase
 
 semesters:
-    - SS17
+    - SS17 
+    - SS18 
+    - SS19 
+    - SS20 
+    - SS21 
+    - SS22 
+    - SS23 
+    - SS24 
 ---
 
+This course is the second part of a two-semester introduction into the field of Artificial
+Intelligence (AI). It introducers the foundations of inference under uncertainty, machine
+learning and language understanding. The course builds on and continues the course 
+[Artificial Intelligence I](/courses/ai1/) from the winter semester. In particular, the course 
+covers
+
+* Inference under Uncertainty
+* Bayesian Networks
+* Rational Decision Theory (MDPs and POMDPs)
+* Machine Learning and Neural Networks
+* Natural Language Processing
+
+The course follows the book
+[Artificial Intelligence: A Modern Approach](https://www.pearson.com/us/higher-education/program/Russell-Artificial-Intelligence-A-Modern-Approach-3rd-Edition/PGM156683.html)
+by Stuart Russell und Peter Norvig. We use the third edition. 
+
+The course materials (e.g. [Course Notes](http://kwarc.info/teaching/AI/notes.pdf) or
+[Assignments](http://kwarc.info/teaching/AI/assignments.pdf), but also old exams and
+(some) solutions) are [here](http://kwarc.info/teaching/AI/). 
+
+The course forum on [StudOn](https://studon.fau.de) is an important source for advice and
+discussions. The instrutor and tutors try to be present to help. 
+
+### German Version (possibly out of date)
+
 Diese Vorlesung ist der zweite Teil einer zwei-semestrigen Einführung in die Künstlichen
 Intelligenz (KI). Sie beschäftigt sich mit den Grundlagen des Schliessens unter
 Unsicherheit, des maschinellen Lernens und des Sprachverstehens.  Der Kurs baut auf der
@@ -28,3 +60,8 @@ von Stuart Russell und Peter Norvig. Wir verwenden die dritte Ausgabe.
 Die Kursmaterialien (z.B. [Course Notes](http://kwarc.info/teaching/AI/notes.pdf) oder
 [Aufgaben](http://kwarc.info/teaching/AI/assignments.pdf), aber auch alte Klausuren)
 finden sich in [hier](http://kwarc.info/teaching/AI/). 
+
+Diskussionen finden auf dem
+[FSI Forum KI-I](https://fsi.cs.fau.de/forum/149-Kuenstliche-Intelligenz-II) statt. Dies ist
+eine wichtige Quelle von Rat und Tat. Wir bemühen uns, auf dem Forum präsent zu sein, und
+schnell auf Fragen zu antworten. Also das Forum abonnieren! 

courses/aisysproj.md

+---
+layout: course
+
+title: AI 1/2 Systems Project
+instructors:
+    - mkohlhase
+    - jfschaefer
+semesters:
+    - WS21/22 
+    - WS22/23 
+    - WS23/24 
+    - WS24/25 
+    - SS22
+    - SS23
+    - SS24
+    - SS25
+    - SS26
+---
+
+
+##### AI-1 and AI-2 systems project
+The AI systems projects are designed to provide hands-on experience for the topics covered in the AI lectures.
+The AI-1 Systems Project focuses on the symbolic methods discussed in the [AI-1 lecture](https://kwarc.info/courses/ai1/) (search, SAT solving, semantic web, planning, ...)
+and the AI-2 Systems Project focuses on the subsymbolic methods covered by the [AI-2 lecture](https://kwarc.info/courses/ai2/) (Bayesian networks, (hidden) markov problems, machine learning, ...).
+Each AI systems project is worth 10 ECTS.
+Generally, you can pick whichever project sounds more interesting to you/is more relevant for your studies.
+If you need two projects, you can also take both, but you cannot start both at the same time.
+
+**Requirements:** There are no formal requirements, but we strongly recommend
+that you either have taken the AI lecture or will take it in parallel.
+Furthermore, you should have substantial programming experience (the programming language is not important) because you will have to program a lot.
+In particular, the AI systems project is not a programming course, i.e. we expect that you are already proficient.
+
+##### What happens in the project?
+The project will consist of several large problems (≈6), which you will work on individually or in small teams.
+Each problem will require a substantial amount of programming work - after all the project is worth 10 ECTS.
+You can take a look at the [problems from the previous iterations](https://kwarc.info/teaching/AISysProj/) to get a first impression.
+The first problem is a warm-up problem, which you have to solve alone, so that you can judge whether the project works for you.
+The remaining problems are intended to be solved in teams of size 2.
+Furthermore, you will have to write a report on one of the problems and have a small presentation (or rather, a section of a presentation together with other people).
+The details will be discussed in the admin meeting.
+
+
+##### Sign-up
+You can sign up for the AI systems project via [StudOn](https://www.studon.fau.de/crs6243066.html)
+(sign-up is independent of whether you are interested in the AI-1 or AI-2 systems project).
+You will probably be placed on a waiting list (this is normal; demand is high). We first accept people from the waiting list of the previous semester, so the course may already be fuller than indicated.
+However, we will regularly accept new people throughtout the semester,
+whenever students have finished or dropped out.
+The project is designed in a way that you can join at any point, including in the middle of the semester.
+In that case your project would simply continue for a while after the semester ends.
+
+**Important: Make sure to regularly check if you have been admitted (you should also get an email notification).
+If you miss some of the early deadlines, we assume that you are not interested in the project and will remove you to give other students a chance.**
+
+
+##### Timeline
+The project timeline is quite flexible:
+
+* You can request to join the project at any time, and at regular intervals we will admit new people (the capacity is limited, so you might have to wait).
+* Once we have admitted you, we will have an admin meeting, in which we will discuss more details about the project.
+    Check the StudOn forum for information on the time of the next admin meeting.
+    Afterwards, you should follow the onboarding guide (posted on StudOn).
+    You can still drop the project later on.
+* Then you can get started with the warm-up problem.
+    The warm-up problem has to be solved individually and is a requirement to take the project.
+    It is also an opportunity for you to see if the project works for you. You can still decide to drop the project after starting the warm-up problem.
+* Once you have solved the warm-up problem, you can sign up to solve the other ≈5 problems. These are intended to be solved in teams of size two,
+    but currently we also allow teams of size one (that might change at any point though).
+    Each problem is offered once a semester. It's up to you if you want to do all of them in one semester or e.g. spread it over two semesters.
+* You will have to give a presentation on one of the problems. We will use some sort of sign-up process for that as well.
+* You will have to write a report on one of the problems (can be the one you present). Furthermore, we will simulate double-blind peer review,
+    which means that you will have to write 3 anonymous reviews for other students' reports.
+
+**Important:**
+You will have to take initiative to finish the project.
+That means actively following the announcements (e.g. about new problems or available presentation slots), making sure that you sign up for problems and reach out if you need anything.
+Simply joining the StudOn course is not enough.
+**As the number of spaces in the project is limited, we will remove students from the project who do not finish the on-boarding procedure in time or who do not submit a preliminary solution to the warm-up problem on time.**
+If you have been removed, you can join the waiting list again.
+
+
+##### It's different from "Projekt zur Künstlichen Intelligenz"
+You might also find references to "Projekt zur Künstlichen Intelligenz (P KI)".
+Despite the similar names, they are very different:
+The systems project (as described on this page) is organized more like a course, parallel to the AI lecture,
+and every student will work on the same set of problems.
+"P KI", on the other hand, is an individual research project with the kwarc group.
+In the AI Master you need two projects, so you could even take both (then taking the systems project first is probably a good idea).
+
+
+##### Contact
+If you have any questions, feel free to send an email to `"jan frederik schaefer".replace(' ', '.') + "@fau.de"`.
+Note that sending an email will not get you accepted into the project faster.
+You can also join [our public AISysProj matrix room](https://matrix.to/#/#aisysproj-non-members:fau.de).
+Matrix is a communications platform that is supported by FAU. We will use it to communicate during the AI systems project.
+You can find instructions for joining Matrix at FAU [here](https://www.anleitungen.rrze.fau.de/serverdienste/matrix-an-der-fau/erste-schritte/) (only in German, unfortunately).
+

courses/complog.md

@@ -18,3 +18,5 @@ semesters:
 ---
 Theory and machine-oriented inference for propositional, first-order, higher-order, modal,
 and description logics. 
+
+The course resources (course notes, literature, assignments) can be found [here](http://kwarc.info/teaching/CompLog).

courses/comsem.md

@@ -14,4 +14,16 @@ semesters:
     - Spring14
     - Spring15
 ---
-Logic-based theories for the semantics of natural language. 
+
+This course introduces logic-based methods for computing and representing for the semantics of natural language. We use Montague's "method of fragments" to create a series of language models of increasing coverage (of English).
+
+A **language model** is a triple of
+
+* a grammar *G* that defines a language fragment that can be translated,
+* a logical system *L* that acts as the meaning representation, and 
+* a translation from syntax trees induced by *G* to formulae in *L*.
+
+The course resources (course notes, literature, assignments) can be found [here](http://kwarc.info/teaching/ComSem).
+
+Having heard the course ["Computational Logic](http://kwarc.info/teaching/CompLog)" is very helpful, but not a prerequisite.
+ 

courses/iwgs1.md

+---
+layout: course
+
+title: Informatische Werkzeuge in den Geistes- und Sozialwissenschaften IWGS-I
+instructors:
+    - mkohlhase
+
+semesters:
+    - WS18/19
+    - WS19/20
+    - WS20/21
+    - WS21/22
+    - WS22/23 
+    - WS23/24 
+    - WS24/25 
+    - WS25/26 
+---
+
+Diese Vorlesung ist der erste Teil einer zwei-semestrigen Einführung. 
+Das Ziel dieser Vorlesung ist es, Studenten einen Überberblick über die informatischen
+Werkzeuge für die Geistes- und Sozialwissenschaften zu geben, sowie intuitiv ihre
+Arbeitsweisen und Prinzipien zu erklären. Studenten sollen für die aufkommenden „Digitalen
+Geistesund Sozialwissenschaften“ ermächtigt werden. Im Gegensatz zu normalen
+Informatikvorlesungen, die primär die mathematischen Grundlagen und Berechnungskonzepte
+einführen, die langfristig notwendig sind, die Informatik voll zu verstehen, wollen wir in
+dieser Vorlesung Methoden und Werkzeuge einführen, die kurzfristig – am besten unmittelbar
+– nützlich werden und so zu motivierenden Erfolgserlebnissen führen. Damit wollen wir den
+„Programmierschock“ (das Gehirn hört auf zu arbeiten sobald von Programmen die Rede ist)
+verhindern, der so häufig bei Geistes- und Sozialwissenschaftlern auftritt.
+
+Themen in in IWGS-1
+
+* programming in python (main tool in IWGS)
+   * systematics and culture of programming
+   * program and control structures
+   * basic data strutures like numbers and strings, character encodings, unicode, and
+   regular expressions
+* digital documents and document processing
+   * text files 
+   * markup systems, HTML, and CSS
+* Data bases and Data Storage
+  * Entity Relationship diagrams,
+  * CRUD operations, and DB querying
+  * XML and JSON for file-based data storage
+* Web technologies for interactive documents and applications
+  * Internet infrastructure: web browsers and servers
+  * PHP, dynamic HTML, Javascript, HTML forms
+* Web Application Project (design your own!)
+
+Die Kursmaterialien (z.B. [Course Notes](http://kwarc.info/teaching/IWGS/notes.pdf) oder
+[Aufgaben](http://kwarc.info/teaching/IWGS/assignments.pdf), aber auch alte Klausuren)
+finden sich in [hier](http://kwarc.info/teaching/IWGS/). 
+
+Diskussionen finden auf dem
+[Studon Forum IWGS](https://www.studon.fau.de/frm2319978.html) statt. Dies ist
+eine wichtige Quelle von Rat und Tat. Wir bemühen uns, auf dem Forum präsent zu sein, und
+schnell auf Fragen zu antworten. Also das Forum abonnieren! 

courses/iwgs2.md

+---
+layout: course
+
+title: Informatische Werkzeuge in den Geistes- und Sozialwissenschaften IWGS-II
+instructors:
+    - mkohlhase
+
+semesters:
+    - SS19
+    - SS20
+    - SS21
+    - SS22 
+    - SS23 
+    - SS24 
+    - SS25 
+---
+
+Diese Vorlesung ist der zweite Teil einer zwei-semestrigen Einführung
+([IWGS-1](/courses/iwgs1/)
+
+Das Ziel dieser Vorlesung ist es, Studenten einen Überberblick über die informatischen
+Werkzeuge für die Geistes- und Sozialwissenschaften zu geben, sowie intuitiv ihre
+Arbeitsweisen und Prinzipien zu erklären. Studenten sollen für die aufkommenden „Digitalen
+Geistesund Sozialwissenschaften“ ermächtigt werden. Im Gegensatz zu normalen
+Informatikvorlesungen, die primär die mathematischen Grundlagen und Berechnungskonzepte
+einführen, die langfristig notwendig sind, die Informatik voll zu verstehen, wollen wir in
+dieser Vorlesung Methoden und Werkzeuge einführen, die kurzfristig – am besten unmittelbar
+– nützlich werden und so zu motivierenden Erfolgserlebnissen führen. Damit wollen wir den
+„Programmierschock“ (das Gehirn hört auf zu arbeiten sobald von Programmen die Rede ist)
+verhindern, der so häufig bei Geistes- und Sozialwissenschaftlern auftritt.
+
+Themen in in IWGS-1
+
+tba
+
+Die Kursmaterialien (z.B. [Course Notes](http://kwarc.info/teaching/IWGS/notes.pdf) oder
+[Aufgaben](http://kwarc.info/teaching/IWGS/assignments.pdf), aber auch alte Klausuren)
+finden sich in [hier](http://kwarc.info/teaching/IWGS/). 
+
+Diskussionen finden auf dem
+[Studon Forum IWGS](https://www.studon.fau.de/frm2319978.html) statt. Dies ist
+eine wichtige Quelle von Rat und Tat. Wir bemühen uns, auf dem Forum präsent zu sein, und
+schnell auf Fragen zu antworten. Also das Forum abonnieren! 

courses/lbs.md

 ---
 layout: course
-
 title: Logik-Basierte Sprachverarbeitung (LBS)
 instructors:
     - mkohlhase
-
+    - jfschaefer
 semesters:
     - WS17/18
+    - WS18/19 
+    - WS19/20 
+    - WS20/21 
+    - WS21/22
+    - WS22/23
+    - WS23/24
+    - WS24/25
 ---
 
 Dieser Kurs behandelt Grundlagen der logikbasierten Sprachverarbeitung - Syntax,
-Semantik-Konstruktion, und Semantische Verarbeitung natürlicher Sprache. Wir werden
+Semantik-Konstruktion, und semantische Verarbeitung natürlicher Sprache. Wir werden
 einerseits die Grundlagen theoretisch erarbeiten (Montague's "method of fragments"), und
 andererseits praktisch im
 [Grammatical Framework (GF)](http://www.grammaticalframework.org/) implementieren und
-damit experimentieren. 
+damit experimentieren. Der theoretische Teil des Kurses wird auf
+[dem Kurs "Computational Semantics"](http://kwarc.info/teaching/ComSem) aufbauen. 
 
 Da wir nur wenige Studenten erwarten, wollen wir diesen Kurs sehr interaktiv und
-Projektorientiert aufbauen. 
+projektorientiert aufbauen.
+
+Die Vorlesung
+["Logik-Basierte Wissensrepräsentation für Mathematisch/Technisches Wissen"](/courses/KRMT/)
+aus dem vorhergehenden Sommer-Semester ist sehr hilfreich für den praktischen Teil, aber
+keine notwendige Voraussetzung.
+
+Die Kursmaterialien (wichtig vor allem die
+[course notes](https://kwarc.info/teaching/LBS/notes.pdf), aber auch Hausaufgaben)
+finden sich [hier](https://kwarc.info/teaching/LBS/). Die Resourcen des LBS Labs sind
+im [LBS Lab Repository](https://gl.mathhub.info/Teaching/LBS) auf [MathHub](http://mathhub.info).
 
+Diskussionen finden auf dem
+StudOn-Forum statt. Dies ist
+eine wichtige Quelle von Rat und Tat. Wir bemühen uns, auf dem Forum präsent zu sein, und
+schnell auf Fragen zu antworten. Also das Forum abonnieren! 

courses/mathdata.md

+---
+layout: course
+
+title: Seminar for mathematical data
+instructors:
+semesters:
+    - SS20
+---
+
+This seminar grew out of the planned April 2020 [bilateral](https://kwarc.info/projects/mdh/)
+workshop on mathematical data from Ljubljana to an online setting.
+
+The main goal is to build and interconnect the community of people
+interested in data generated within mathematical research as well as data related 
+to mathematics in other ways.
+
+The seminar will aim for a relaxed atmosphere and shorter talks, with plenty of 
+time for discussion.
+
+- Time: Fridays, 14:00-15:30 (12:00-13:30 UTC)
+- Zoom ID of the seminar will be posted with each announcement.
+
+Announcements will be posted on the [KWARC mathematical data mailing list](http://lists.informatik.uni-erlangen.de/mailman/listinfo/math-data).
+
+### Upcoming seminars:
+
+#### ICMS discussion
+
+- *Time*: Friday, July 24, 2020 from 14:00 to 15:30 (Central European Summer Time, UTC+2)
+- *Location*: online at Zoom, ID 933 8933 3092
+- *Speaker*: roundtable
+
+**Abstract.** We will discuss talks and discussions from the International Congress on Mathematical Software,
+especially the two sessions related to data in mathematics.
+
+
+### Past seminars:
+
+##### The Knowledge of Mathematics
+
+- *Time*: Friday, July 3, 2020 from 14:00 to 15:30 (Central European Summer Time, UTC+2)
+- *Location*: online at Zoom ID: 960 8031 7108
+- *Speaker*: Patrick Ion (Mathematical Reviews (retd.), University of Michigan, Ann Arbor, MI)
+
+**Abstract.** Mathematics is a body of knowledge, and it has many representations.  A
+library is traditionally a repository of materials that provide access to knowledge.
+The idea of a universal library, or of one just for mathematics, has long been an
+obvious one.  In the modern day (last century or so) it has come up again from
+time to time with each new technological change and notion of representing
+mathematics.  Working forward from a resolution of the International Mathematical
+Union in 2006 efforts have been under taken to realize a Global Digital Mathematics Library. As part of this an International Mathematical Knowledge Trust has been
+founded. I will speak of grand plans, small successes and enormous challenges
+that remain in describing some of recent GDML/IMKT activity. This will be from
+the point of view I've acquired as a result of watching the field from
+Math Reviews (MR) for 30 years or so, being involved with TeX and databases
+at MR and with creation of MathML, as well as trying to understand a little bit
+of specific subjects (quantum field theory and statistical mechanics, hyperfunctions,
+non-commutative geometry, quantum stochastic processes---i.e., anti-Gauss: "multa sed immatura")
+
+##### The Role of Data in Discrete Mathematics
+
+- *Time*: Friday, June 19, 2020 from 14:00 to 15:30 (Central European Summer Time, UTC+2)
+- *Location*: online at Zoom ID: 973 9039 7028
+- *Speaker*: Gabe Cunningham (University of Massachusetts Boston)
+
+**Abstract.** In mathematics, a well-chosen example can help guide our intuition or 
+illustrate the edge-cases of our definitions. 
+When studying discrete objects, we can go for quantity over quality and generate 
+all examples of objects satisfying certain properties and up to a certain size. 
+How can we actually use this data for doing mathematics? 
+What are the barriers that prevent us from making better use of data? 
+In this talk, I will describe the role that data has played in my own research. 
+I will highlight the data repositories that currently exist in my community, 
+and I will discuss why I think better tools are needed and why they wouldn't ever be made without MathDataHub. 
+Finally, I will talk briefly about some work in progress with Katja Berčič and Jukka Kohonen 
+toward developing some new data sets and a Sage package to help my research community.
+
+##### Big Math and the One-Brain Barrier -- The Tetrapod Model of Mathematical Knowledge
+
+- *Time*: Friday, June 5, 2020 from 14:00 to 15:30 (Central European Summer Time, UTC+2)
+- *Location*: online at Zoom ID: 939 0067 6059
+- *Speaker*: Michael Kohlhase (FAU)
+
+**Abstract.** In this talk I will  present an information model for doing mathematics, 
+which posits that humans very efficiently integrate five aspects of mathematics: 
+inference, computation, concretization, narration, and organization. 
+The challenge for mathematical software systems is to integrate these five aspects in the same way humans do.
+
+The Tetrapod model has cristallized out of almost two decades of work on 
+mathematical knowledge representation and permeates the work of the KWARC group. 
+The model is relevant to the MathDataHub effort as it will guide the further development 
+of the MathHub system (MathDataHub is seen as the concretization facet of MathHub).
+
+##### MathDataHub - your dataset, but FAIR
+
+- *Time*: Friday, May 22, 2020 from 14:00 to 15:30 (Central European Summer Time, UTC+2)
+- *Location*: online at Zoom ID: 998 0468 1137
+- *Speaker*: Tom Wiesing (FAU)
+- [Slides](https://kwarc.info/people/twiesing/pubs/slides/2020_05_22_mdh.pdf)
+
+**Abstract.** MathDataHub provides dataset hosting and a searchable interface for the hosted dataset. 
+It was developed by Katja Berčič, Michael Kohlhase, Florian Rabe, and Tom Wiesing. 
+In this talk I will give a basic introduction and overview of the system.
+
+##### An overview of mathematical data (Welcome to the seminar)
+
+- *Time*: Friday, May 8, 2020 from 14:00 to 15:30 (Central European Summer Time, UTC+2)
+- *Location*: online at Zoom ID: 995-5145-1656
+- *Speaker*: Katja Berčič (FAU)
+
+**Abstract.** I will present some of the topics that are relevant for data in 
+mathematics: the state of the art, technical and theoretical issues that arise,
+as well as broader trends in scientific research data. 
+

courses/meta/former.html

@@ -3,20 +3,21 @@ layout: default
 title: Former Courses
 permalink: /courses/former/
 ---
+The courses given by the KWARC group in the last semesters: 
 
 {% assign courses = site.pages | where: "layout", "course" | sort: "title" %}
 {% assign semesters = site.semesters.former | reverse %}
 {% for semester in semesters %}
-    {% assign offers = (courses | where_exp: "c", "c.semesters contains semester") %}
+    {% assign offers = courses | where_exp: "c", "c.semesters contains semester" %}
     
     {% if offers.size > 0%}
         
         <ul class="collection with-header">
-            <li class="collection-header"><h5>{% include semester.html %}</h5></li>
+            <li class="collection-header"><h5>{% include semester.html semester=semester %}</h5></li>
             
             {% for item in offers %}
-                {% include course.html %}
+                {% include course.html item=item %}
             {% endfor %}
         </ul>
     {% endif %}
-{% endfor %}
\ No newline at end of file
+{% endfor %}

courses/meta/index.html

 ---
 layout: default
-title: Courses
+title: KWARC - Current Courses 
 permalink: /courses/
 ---
 
 {% assign courses = site.pages | where: "layout", "course" | sort: "title" %}
+The courses given by the KWARC group in the current semester: {{site.semesters.current}}
+
 
 <ul class="collection">
     {% for item in courses %}
         {% if item.semesters contains site.semesters.current %}
-            {% include course.html %}
+            {% include course.html item=item %}
         {% endif %}
     {% endfor %}
 </ul>

courses/meta/upcoming.html

 ---
 layout: default
-title: Upcoming Courses
+title: Upcoming Courses 
 permalink: /courses/upcoming/
 ---
+The courses in the upcoming semester: {{site.upcoming}} 
 
 {% assign courses = site.pages | where: "layout", "course" | sort: "title" %}
 
 <ul class="collection">
     {% for item in courses %}
         {% if item.semesters contains site.semesters.upcoming %}
-            {% include course.html %}
+            {% include course.html item=item %}
         {% endif %}
     {% endfor %}
-</ul>
\ No newline at end of file
+</ul>

courses/overview.md

 ---
 layout: default
-title: Vertiefungsgebiet Künstliche Intelligenz
+title: Vertiefungsgebiet KI 
 ---
 <table>
   <tr>
     <th>Studiengang</th>
+    <th>Sem</th>
     <td colspan="2">Bachelor</td>
     <td colspan="4">Master</td>
   </tr>
   <tr>
     <th>Empfohlenes Semester</th>
+    <td/>
     <td>5</td><td>6</td><td>1</td><td>2</td><td>3</td><td>4</td>
   </tr>
   <tr>
     <th>Grundlagen-Vorlesung</th>
+    <th>(WS)</th>
     <td colspan="3" style="border-style:solid">
       <a href="/courses/ai1/">Künstliche Intelligenz 1</a>
     </td>
@@ -21,13 +24,23 @@ title: Vertiefungsgebiet Künstliche Intelligenz
   </tr>
   <tr>
     <th>Grundlagen-Vorlesung</th>
+    <th>(SS)</th>
     <td/>
     <td colspan="3" style="border-style:solid">
       <a href="/courses/ai2/">Künstliche Intelligenz 2</a>
     </td>
   </tr>
+  <tr>
+    <th>Vertiefungs-Vorlesung</th>
+    <th>(SS)</th>
+    <td/>
+    <td colspan="5" style="border-style:solid">
+      <a href="/courses/wuv/">Wissensrepräsentation und -Verarbeitung</a>
+    </td>
+  </tr>
   <tr>
     <th>Spezial-Vorlesung</th>
+    <th>(WS)</th>
     <td colspan="5" style="border-style:solid">
       <a href="/courses/lbs/">Logikbasierte Sprachverarbeitung</a>
     </td>
@@ -35,6 +48,7 @@ title: Vertiefungsgebiet Künstliche Intelligenz
   </tr>
   <tr>
     <th>Spezial-Vorlesung</th>
+    <th>(SS)</th>
     <td/>
     <td colspan="5" style="border-style:solid">
       <a href="/courses/KRMT/">Wissensrepräsentation &amp; -Verarbeitung für die Mathematik</a>
@@ -42,17 +56,19 @@ title: Vertiefungsgebiet Künstliche Intelligenz
   </tr>
   <tr>
     <th>Seminar</th>
+    <th>(SS/WS)</th>
     <td colspan="6" style="border-style:solid">
-      <a href="/courses/wuv/">Wissensrepräsentation &amp; -Verarbeitung</a>
+      <a href="/courses/swuv/">Wissensrepräsentation &amp; -Verarbeitung</a>
     </td>
   </tr>
   <tr>
     <th>Projekt</th>
+    <th>(SS/WS)</th>
     <td colspan="2" style="border-style:solid">
       <a href="/courses/AIProj/">KI-Projekt</a>
     </td>
     <td colspan="4" style="border-style:solid">
-      <a href="/courses/AIProj/">Master-Projekt zur KI</a>
+      <a href="/courses/AIProj/">Master-Projekt KI</a>
     </td>
   </tr>
 </table>
@@ -62,11 +78,13 @@ zwei-semestrige Einführungsvorlesung. Diese gibt eine Einführung und exemplari
 
 Die anderen Veranstaltungen gruppieren sich um die
 [Forschungsthemen der KWARC Gruppe](/research/):
-
- * In den beiden Spezialvorlesungen behandeln wir im Wechsel
+ * In der [Vertiefungsvorlesung "Wissensrepräsentation und -Verarbeitung"](/courses/wuv)
+   wird grundlagenorientiert die formale Repräsentation von verschiedenen Arten von Wissen
+   vorgestellt.
+* In den beiden Spezialvorlesungen behandeln wir im Wechsel
 [Wissensrepräsentation für mathematisches Wissen](/courses/KRMT) und
 [Logikbasierte Sprachverarbeitung](/courses/lbs/).
-* Im [WuV-Seminar](/courses/wuv) vertiefen wir diese durch Diskussion aktueller Forschungsartikel
+* Im [Seminar "Wissensrepräsentation und -Verarbeitung"](/courses/swuv) vertiefen wir diese durch Diskussion aktueller Forschungsartikel
 * In den [KI-Projekten](/courses/AIProj/) (Master/Bachelor) können Studenten sich
   selbst an Forschungsarbeiten zu diesen Themen versuchen. Themen werden individuell
   abgesprochen; eine initiale Liste von Projektthemen [findet sich hier](https://gl.kwarc.info/kwarc/thesis-projects).

courses/symnlproj.md

+---
+layout: course
+
+title: Symbolic NLP Project
+instructors:
+    - mkohlhase
+    - jfschaefer
+semesters:
+    - WS24/25 
+---
+
+##### Symbolic NLP Project
+
+This 5 ECTS project is a companion to the [LBS course](https://kwarc.info/courses/lbs/)
+which introduces logical models for natural language semantics and inferential processes
+for natural language understanding. 
+
+The project will be to implement these in state of the art
+meta-linguistic/logical/computational frameworks developed at the [KWARC
+group]{https://kwarc.info). 
+
+##### Organization
+
+The project will start in the third week of classes (so that the LBS course can cover some of the material this project wants to implement) with an admin meeting. Details will be announced.
+
+**Requirements:** There are no formal requirements, but we strongly recommend
+that you either have taken the LBS course or will take it in parallel. Furthermore, we
+assume that you have a high tolerance for logic and declarative programming.  
+
+##### What happens in the project?
+We will start with an individual warm-up problem, in which you will implement some of the
+components of the NLU waterfall in Prolog as a baseline. 
+
+All students have to "pass" the
+warm-up problem to alone, so that you can judge whether the project works for you.  
+The
+remaining problems are intended to be solved in teams of size 2.  
+
+Furthermore, you will
+have to write a report on one of the problems and have a small presentation (or rather, a
+section of a presentation together with other people).  The details will be discussed in
+the admin meeting.
+
+##### Sign-up
+You can sign up for the AI systems project via
+[StudOn](https://www.studon.fau.de/crs5912728.html).
+
+If you miss some of the early deadlines, we assume that you are not interested in the
+project and will remove you to give other students a chance.**
+
+**Important:**
+You will have to take initiative to finish the project.
+That means actively following the announcements (e.g. about new problems or available presentation slots), making sure that you sign up for problems and reach out if you need anything.
+Simply joining the StudOn course is not enough.
+**As the number of spaces in the project is limited, we will remove students from the project who do not finish the on-boarding procedure in time or who do not submit a preliminary solution to the warm-up problem on time.**
+If you have been removed, you can join the waiting list again.
+
+##### Communication
+We will use  [our public AISysProj matrix room](https://matrix.to/#/#SymNLProj:fau.de) for
+most of the data-to-day communication.
+Matrix is a communications platform that is supported by FAU. 
+You can find instructions for joining Matrix at FAU [here](https://www.anleitungen.rrze.fau.de/serverdienste/matrix-an-der-fau/erste-schritte/) (only in German, unfortunately).
+
+
+<!--  LocalWords:  jfschaefer AISysProj
+ -->

courses/theses.md

 ---
 layout: page
-title: For Students
-menu_title: KWARC For Students
+title: KWARC Theses
+menu_title: Completed Theses
 menu_order: 101
 ---
-The KWARC Group welcomes student involvement in research. If you are interested, please send an e-mail to <michael.kohlhase@fau.de>, or come to our seminars and courses
-
-We have an initial list topics for [theses, or guided research](https://gl.kwarc.info/kwarc/thesis-projects)
-
+* [Ph.D. Theses](https://kwarc.github.io/bibs/phdthesis/)
+* [M.Sc Theses](https://kwarc.github.io/bibs/mscthesis/)
+* [B.Sc Theses](https://gl.kwarc.info/supervision/BSc-archive) (list incomplete) 

courses/topics.md

+---
+layout: page
+title: Thesis Topics & Projects
+menu_title: Thesis Topics & Projects 
+menu_order: 101
+---
+The KWARC Group welcomes student involvement in research. If you are interested, please
+send an e-mail to [<michael.kohlhase@fau.de>](maito:michael.kohlhase@fau.de), or come to
+our seminars and courses. 
+
+We have an initial list of topics for
+[theses, or guided research](https://gl.kwarc.info/kwarc/thesis-projects) which may suit
+you, but you can always [help with our systems](/systems/) or [adopt one of our currently orphaned systems](/systems/orphans/) .
+

courses/wuv.md

 ---
 layout: course
 
-title: Seminar Wissensrepräsentation und -verarbeitung
+title: Course Knowledge Representation and Processing (Wissensrepräsentation und -verarbeitung, WuV)
 instructors:
     - mkohlhase
-
+    - frabe
 semesters:
-    - SS17
-    - WS17/18
+    - SS20
+    - SS21
+    - WS22/23
 ---
 
-This seminar covers topics from knowledge representation and knowledge processing, mostly
-with a focus on mathematical knowledge. Topics are agreed up with the instructor.
+This is the homepage of the WuV *lecture*, the *seminar* of the same name is a [separate course](/courses/swuv/).
+
+This module provides a general and foundational introduction into knowledge representation and processing.
+Human knowledge pervades all areas not only of computer science, but also of all sciences, and this representing and processing this knowledge 
+in computer systems is in some sense **the** big challenge and potential of using computers.
+
+Computer science has recognized multiple aspects of knowledge and has developed dedicated representation languages for them.
+Over time these have been specialized massively, and the languages, systems, and communities have drifted apart.
+Today they include in particular ontology languages and linked data, programming languages and algorithms, data description languages and databases, logics and proofs, as well as formal natural languages and narrative documents.
+
+While many of these aspects and languages are studied in depth in individual courses, students often miss an overall perspective that describes  these approaches as a whole.
+The WuV course uses the general goal of knowledge representation as the big picture motivation to survey, analyze, and compare the different languages and systems.
+It introduces all the fundamental concepts both of knowledge representation languages in general and of paradigmatic examples of specialized languages in particular (e.g., OWL, Java, first-order logic, SQL, sTeX).
+It places special emphasis on the commonalities, differences, and integration of the approaches and the interoperability of the various systems.
+
+The exercises teach practical aspects including both the implementation of knowledge representation languages from scratch as well as the use of state-of-the-art languages and software systems.
+
+We recommend WuV to Master or 3rd year Bachelor students both as an introductory module before taking other modules in the area Artificial Intelligence as well as a one-off overview of the area.