courses/AIProj.md

 ---
 layout: course
 
-title: Projekt zur Künstlichen Intelligenz
-instructor: mkohlhase
-
+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/GenICT1.md

@@ -2,15 +2,15 @@
 layout: course
 
 title: General Information and Communication Technology I 
-instructor:
-- mkohlhase
-- Prof.  Jürgen Schönwälder
-- Prof. Peter Baumann
-- Prof. Herbert Jaeger
-	
+instructors:
+    - mkohlhase
+    - Prof.  Jürgen Schönwälder
+    - Prof. Peter Baumann
+    - Prof. Herbert Jaeger
+    
 organization: Jacobs University
 semesters:
-- Fall14
-- Fall15
+    - Fall14
+    - Fall15
 ---
 An Introduction to Computer Science for students of all subjects. 

courses/GenICT2.md

@@ -2,14 +2,14 @@
 layout: course
 
 title: General Information and Communication Technology II 
-instructor:
-- mkohlhase
-- Prof.  Jürgen Schönwälder
-- Prof. Peter Baumann
-- Prof. Herbert Jaeger
-	
+instructors:
+    - mkohlhase
+    - Prof.  Jürgen Schönwälder
+    - Prof. Peter Baumann
+    - Prof. Herbert Jaeger
+
 organization: Jacobs University
 semesters:
-- Spring15
+    - Spring15
 ---
 An Introduction to Computer Science for students of all subjects. 

courses/KRMT.md

 ---
 layout: course
-
-title: Logik-Basierte Wissensrepräsentation für Mathematisch/Technisches Wissen
-instructor: mkohlhase
-
+title: Logic-Based Representation of Mathematical/Technical Knowledge
+instructors:
+  - 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.
+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. 
+
+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).
 
-Da wir nur wenige Studenten erwarten, wollen wir diesen Kurs sehr interaktiv und
-Projektorientiert aufbauen. 
+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/ai.md

@@ -2,7 +2,8 @@
 layout: course
 
 title: Artificial Intelligence
-instructor: mkohlhase
+instructors:
+    - mkohlhase
 
 organization: Jacobs University
 semesters:

courses/ai1.md

 ---
 layout: course
 
-title: Künstliche Intelligenz I
-instructor: mkohlhase
+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 
 ---
 
-Diese Vorlesung beschäftigt sich mit den Grundlagen der Künstlichen Intelligenz (KI),
+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
+* 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)
+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
-instructor: mkohlhase
+title: Artificial Intelligence II
+instructors:
+    - mkohlhase
 
 semesters:
-    - SS17
+    - SS17 
+    - SS18 
+    - SS19 
+    - SS20 
+    - SS21 
+    - SS22 
+    - SS23 
+    - SS24 
 ---
 
-Dieser Kurs beschäftigt sich mit den Grundlagen der Künstlichen Intelligenz (KI), insbesondere mit Techniken des Schliessens unter Unsicherheit, des maschinellen Lernens und des Sprachverstehens.
-Der Kurs baut auf der Vorlesung Künstliche Intelligenz I vom Wintersemester auf und führt diese weiter.
+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
+[Vorlesung Künstliche Intelligenz I](/courses/ai1/) vom Wintersemester auf und führt diese
+weiter. Wir behandeln insbesondere
+
+* Schliessen unter Unsicherheit
+* Bayessche Netzwerke
+* Theorie der Rationalen Entscheidungen
+* Maschinelles Lernen
+* Sprachverstehen (wenn die Zeit reicht)
+
+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)
+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

@@ -2,11 +2,11 @@
 layout: course
 
 title: Computational Logic
-instructor:
-	- mkohlhase
+instructors:
+    - mkohlhase
     - frabe
     - dmueller
-	
+    
 organization: Jacobs University
 semesters:
     - Fall05
@@ -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

@@ -2,9 +2,9 @@
 layout: course
 
 title: Computational Natural Language Semantics
-instructor:
-	- mkohlhase
-	
+instructors:
+    - mkohlhase
+    
 organization: Jacobs University
 semesters:
     - Fall06
@@ -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/dbwa.md

@@ -2,7 +2,8 @@
 layout: course
 
 title: Data Bases and Web Applications
-instructor: mkohlhase
+instructors:
+    - mkohlhase
 
 organization: Jacobs University
 semesters:

courses/dynamics.md

@@ -2,9 +2,9 @@
 layout: course
 
 title: Representing Dynamics and Dynamic Representation 
-instructor: mkohlhase
-co-instructors:
-    - Herber Jaeger, Jacocbs University
+instructors:
+    - mkohlhase
+    - Herber Jaeger, Jacobs University
 
 organization: Jacobs University
 semesters:

courses/gencs.md

@@ -2,12 +2,13 @@
 layout: course
 
 title: General Computer Science
-instructor: mkohlhase
+instructors:
+    - mkohlhase
 
 organization: Jacobs University
 semesters:
-    - Fall015 
-    - Fall016 
+    - Fall15 
+    - Fall16 
 ---
 
 General Computer Science I is the first semester, introductory course taught at Jacobs University. Starting the Fall Semester 2015 (when GenCS II was dropped). It is really still the same as GenCS I. 

courses/gencs1.md

@@ -2,7 +2,8 @@
 layout: course
 
 title: General Computer Science I
-instructor: mkohlhase
+instructors:
+    - mkohlhase
 
 organization: Jacobs University
 semesters:
@@ -13,11 +14,11 @@ semesters:
     - Fall07
     - Fall08
     - Fall09
-    - Fall010
-    - Fall011
-    - Fall012
-    - Fall013 
-    - Fall014 
----p
+    - Fall10
+    - Fall11
+    - Fall12
+    - Fall13 
+    - Fall14 
+---
 
 General Computer Science I is the first semester, introductory course taught at Jacobs University. It focuses on representation issues for objects, and uses SML as an programming language to equalize over a diverse student body. 

courses/gencs2.md

@@ -2,7 +2,8 @@
 layout: course
 
 title: General Computer Science II
-instructor: mkohlhase
+instructors:
+    - mkohlhase
 
 organization: Jacobs University
 semesters:

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/krsw.md

@@ -2,8 +2,8 @@
 layout: course
 
 title: Research Seminar -  Knowledge Representation and Semantic Web
-instructor:
-	- mkohlhase
+instructors:
+    - mkohlhase
     - frabe
 
 organization: Jacobs University

courses/lbs.md

 ---
 layout: course
-
 title: Logik-Basierte Sprachverarbeitung (LBS)
-instructor: mkohlhase
-
+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 im Grammatical
-Framework (GF)
+Dieser Kurs behandelt Grundlagen der logikbasierten Sprachverarbeitung - Syntax,
+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. 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. 
+