thesis-projects issueshttps://gl.kwarc.info/kwarc/thesis-projects/-/issues2020-05-01T23:34:36Zhttps://gl.kwarc.info/kwarc/thesis-projects/-/issues/363D Theory Graph Visualization2020-05-01T23:34:36ZRichard Marcus3D Theory Graph VisualizationAs a follow up to #8, we have developed an interactive [3D graph viewer](https://github.com/UniFormal/tgview3d).
Based on this, there are several possibilities for further research:
- extending the virtual reality prototype with state-of...As a follow up to #8, we have developed an interactive [3D graph viewer](https://github.com/UniFormal/tgview3d).
Based on this, there are several possibilities for further research:
- extending the virtual reality prototype with state-of-the-art interaction concepts
- developing library-specific, specialized builds
- comparing different layout algorithms
- optimizing layout computationMichael Kohlhasemichael.kohlhase@fau.deMichael Kohlhasemichael.kohlhase@fau.dehttps://gl.kwarc.info/kwarc/thesis-projects/-/issues/35FrameIT State Interface2020-12-03T17:45:48ZRichard MarcusFrameIT State InterfaceIn the FrameIT project (#1), we use the Unity game engine in combination with MMT to have access to mathematical knowledge management techniques and interact with the knowledge in the game world.
Since (formalized) knowledge is generate...In the FrameIT project (#1), we use the Unity game engine in combination with MMT to have access to mathematical knowledge management techniques and interact with the knowledge in the game world.
Since (formalized) knowledge is generated interactively during runtime, it is difficult to debug with existing MMT utilities.
Accordingly, we need adaptions to make use of these and new concepts to interact with the generated content on the programming language level.
Based on this, we would like to have an interface that helps developers to monitor the state of the underlying knowledge during gameplay.Michael Kohlhasemichael.kohlhase@fau.deMichael Kohlhasemichael.kohlhase@fau.dehttps://gl.kwarc.info/kwarc/thesis-projects/-/issues/34Machine Learning Applications for FrameIT2023-02-03T10:26:41ZRichard MarcusMachine Learning Applications for FrameITIn the FrameIT project (#1), we use the Unity game engine in combination with MMT to have access to mathematical knowledge management techniques and interact with the knowledge in the game world.
Building on the [Unity machine learning ...In the FrameIT project (#1), we use the Unity game engine in combination with MMT to have access to mathematical knowledge management techniques and interact with the knowledge in the game world.
Building on the [Unity machine learning integration](https://unity.com/products/machine-learning-agents), we would like to teach an agent to play the games developed with the FrameIT method.
Possible approaches may be:
- reinforcement learning via reward function
- imitation learning
- modularizing tasks based on the MMT knowledge formalization
Note that there is no groundwork for this topic, so a strong background in machine learning is required.Michael Kohlhasemichael.kohlhase@fau.deMichael Kohlhasemichael.kohlhase@fau.dehttps://gl.kwarc.info/kwarc/thesis-projects/-/issues/33FrameIT Virtual Reality Port2023-01-20T22:14:44ZRichard MarcusFrameIT Virtual Reality PortIn the FrameIT project (#1), we use the Unity game engine in combination with MMT to have access to mathematical knowledge management techniques and interact with the knowledge in the game world.
Our current frameworks aims at supportin...In the FrameIT project (#1), we use the Unity game engine in combination with MMT to have access to mathematical knowledge management techniques and interact with the knowledge in the game world.
Our current frameworks aims at supporting the development of serious games.
These profit from virtual reality by having intuitive forms of interaction and a more immersive learning experience.
For interaction, we use different *gadgets* and user interfaces, which need to be adapted for use in VR.Michael Kohlhasemichael.kohlhase@fau.deMichael Kohlhasemichael.kohlhase@fau.dehttps://gl.kwarc.info/kwarc/thesis-projects/-/issues/31Lexicon Management in GLIF2020-04-20T14:32:19ZFrederik SchaeferLexicon Management in GLIF[**GLIF**](https://github.com/kwarc/GLIF) is a framework for describing the translation of natural language into logical expressions.
This requires the specification of a grammar, a target logic, a domain theory in that logic, and a sema...[**GLIF**](https://github.com/kwarc/GLIF) is a framework for describing the translation of natural language into logical expressions.
This requires the specification of a grammar, a target logic, a domain theory in that logic, and a semantics construction (mapping of parse trees into the domain theory).
If you participated in the LBS lecture, you should be familiar with the setup.
Adding a new word (like "woman") to a GLIF pipeline requires the following additions:
* abstract syntax: `woman_N : N;`
* concrete syntax: `woman_N = mkN "woman" "women";` (if e.g. German is also supported: `woman_N = mkN "Frau" feminine;`)
* domain theory: `woman : i -> o`
* semantics construction: `woman_N = woman`
There clearly is a lot of repetition here.
Your task would be to improve this by designing a lexicon format from which the necessary files can be generated automatically.
A naive attempt to write a lexicon entry could look like this:
```
woman
noun
eng: "woman" "women"
ger: "Frau" feminine
```
We probably want customization in different places. For example, the semantics construction for the name John might be `john_PN = john` or `john_PN = [P] P john` depending on the context. Also, not every project uses the resource grammar library, so the operations used in the concrete syntax might vary.
The lexicon management should also be supported in GLIF's Jupyter front-end.
It would also be interesting to take existing lexica and generate a generic lexicon from that, which can be imported into any projects (with the required customization to make it fit in).https://gl.kwarc.info/kwarc/thesis-projects/-/issues/30SUMO to OMDoc/MMT exporter.2020-12-08T09:04:14ZMichael Kohlhasemichael.kohlhase@fau.deSUMO to OMDoc/MMT exporter.The Suggested Upper Merged Ontology [SUMO](http://www.adampease.org/OP/) is an upper ontology that lightly formalizes common sense situations. It woucd be very nice to have a translator of SUMO into MMT Theories. For that we need
* A me...The Suggested Upper Merged Ontology [SUMO](http://www.adampease.org/OP/) is an upper ontology that lightly formalizes common sense situations. It woucd be very nice to have a translator of SUMO into MMT Theories. For that we need
* A meta-theory for the KIF (Knowledge Interface Format)
* a translator for the [SUMO data](https://github.com/ontologyportal/sumo) to OMDoc/MMT.
SUMO seems licenced mostly under GPL, so we are allowed to do this and even republish it on MathHub (as long as we keep the GPL).
This would be a good basis for JLogic.Max RappMax Rapphttps://gl.kwarc.info/kwarc/thesis-projects/-/issues/29FrameNet to OMDoc/MMT exporter.2022-04-22T12:14:49ZMichael Kohlhasemichael.kohlhase@fau.deFrameNet to OMDoc/MMT exporter.[FrameNet](https://framenet.icsi.berkeley.edu) is a semantic linguistic resource that collects a set of common frames that can be used for understanding common sense situations. It woucd be very nice to have a translator of FrameNet into...[FrameNet](https://framenet.icsi.berkeley.edu) is a semantic linguistic resource that collects a set of common frames that can be used for understanding common sense situations. It woucd be very nice to have a translator of FrameNet into MMT Theories. For that we need
* A metatheory (FrameNetLogic)
* a translator for the FrameNet data, which comes as an XML file.
I have already requested the data.
FrameNet is licensed under Creative Commons Attribution, so we are allowed to do this and even republish it on MathHub (as long as we attribute).
This would be a good basis for JLogic.Frederik SchaeferFrederik Schaeferhttps://gl.kwarc.info/kwarc/thesis-projects/-/issues/28Build an integrated SPARQL index/endpoint for MathHub2020-07-30T11:25:15ZMichael Kohlhasemichael.kohlhase@fau.deBuild an integrated SPARQL index/endpoint for MathHubWe are slowly building up capacities for [tetrapodal search](https://kwarc.info/people/mkohlhase/papers/cicm20-search.pdf) in [MathHub](https://mathhub.info), i.e. search capacities across mathematical aspects.
For that we need an inde...We are slowly building up capacities for [tetrapodal search](https://kwarc.info/people/mkohlhase/papers/cicm20-search.pdf) in [MathHub](https://mathhub.info), i.e. search capacities across mathematical aspects.
For that we need an index for the *organizational aspect* which can mostly be expressed in terms of RDF graphs and queried via SPARQL. We already have quite a lot of data from our theory graphs and theorem prover libraries; see [the ULO paper](https://kwarc.info/kohlhase/papers/cicm19-ulo.pdf).
Now we need a dedicated index and query engine for them integrated into [MathHub](https://mathhub.info). I am thinking of [GraphDB](https://www.ontotext.com/products/graphdb/) a powerful system that is free in the basic tier. And give it a good test-drive with our data.Tom WiesingTom Wiesinghttps://gl.kwarc.info/kwarc/thesis-projects/-/issues/27OEIS importer and extension for MathDataHub2020-12-08T09:05:50ZMichael Kohlhasemichael.kohlhase@fau.deOEIS importer and extension for MathDataHub[MathDataHub](http://data.mathhub.info) (MDH) is a deep FAIR system for mathematical data sets. Currently, it has mostly been used for systematic data sets like the [Small Groups Library](https://data.mathhub.info/collection/smallgp/).
...[MathDataHub](http://data.mathhub.info) (MDH) is a deep FAIR system for mathematical data sets. Currently, it has mostly been used for systematic data sets like the [Small Groups Library](https://data.mathhub.info/collection/smallgp/).
Having the [OEIS](http://oeis.org) (Encyclopedia of Integer Sequences) in [MathDataHub](http://data.mathhub.info) would be a major undertaking and a major success. Some of this we have already done, see [E. Luzhnica and M. Kohlhase (2016) Formula semantification and automated relation finding in the OEIS. ICMS 2016](http://kwarc.info/kohlhase/papers/icms16-oeis.pdf). This needs to be made sustainable and much more complete. [MathDataHub](http://data.mathhub.info) and [MathHub](http://mathhub.info) are the right tools/targets for this. We have to
* get our hands on the OEIS dumps - KWARC has the necessary contacts - and build an infrastructure to keep the content synced.
* build a parser for the OEIS that is as lossless as possible
* formalize the meta-theory of OEIS in MMT.
* Build the MDDL Schema theories for the OEIS
* (optionally) Build specialized User Interfaces on top of MDH.
* (optionally) build a programmatic API for the OEIS.
Clearly this is a project for a whole group, and the later points are optional.
One of the high proints of this project is that there is a good chance that there will be funding (and possibly future employment options via the [NFDI](https://de.wikipedia.org/wiki/Nationale_Forschungsdateninfrastruktur) KWARC is part of the [MaRDI Consortium](http://wias-berlin.de/mardi/).Michael Kohlhasemichael.kohlhase@fau.deMichael Kohlhasemichael.kohlhase@fau.dehttps://gl.kwarc.info/kwarc/thesis-projects/-/issues/26More MathWebSearch Instances2020-03-20T07:45:59ZMichael Kohlhasemichael.kohlhase@fau.deMore MathWebSearch InstancesThere are numerous mathematical resources that need [formula search engines](https://search.mathweb.org). Given Christoph Alt's thesis and MWS front-end this is mostly a matter of writing a good harvester. Some examples that come to mind...There are numerous mathematical resources that need [formula search engines](https://search.mathweb.org). Given Christoph Alt's thesis and MWS front-end this is mostly a matter of writing a good harvester. Some examples that come to mind
* The [Stacks Project](https://stacks.math.columbia.edu/) 7000 pages of algebra in LaTeX; see https://github.com/MathWebSearch/frontend/issues/18
* the [OEIS](https://oeis.org), We had a search engine for the formulae at one point, we just need to resurrect and modernize it (see #27)
* ...
And the best would be to create a joint index where MWS searches all of these together. https://gl.kwarc.info/kwarc/thesis-projects/-/issues/25Intellij support for MMT-jupyter-notebooks2020-01-03T09:11:22ZDennis MüllerIntellij support for MMT-jupyter-notebooksSee https://github.com/UniFormal/IntelliJ-MMT/issues/28See https://github.com/UniFormal/IntelliJ-MMT/issues/28https://gl.kwarc.info/kwarc/thesis-projects/-/issues/24Identifying Mathematical Objects up to Canonical Isomorphpism2019-06-04T22:57:39ZFlorian RabeIdentifying Mathematical Objects up to Canonical Isomorphpism@mkohlhase @dmueller
# Motivation
Mathematics pervasively identifies objects if they are canonically isomorphic.
Examples:
* define the rationals as fractions (pairs of integers, quotiented by cancelling), then identify the integer z...@mkohlhase @dmueller
# Motivation
Mathematics pervasively identifies objects if they are canonically isomorphic.
Examples:
* define the rationals as fractions (pairs of integers, quotiented by cancelling), then identify the integer z with the fraction z/1
* the entire number hierarchy N <: Z <: Q etc. is built like above
* elements of ring R are identified with constant polynomials over R
* elements of ring R are identified with elements in localizations over R
* polynomials are identified with the respective elements in the field of fractions
* generators of a group are identified with elements of the generated group (which are technically equivalence classes)
It is very common that
* the isomorphism is from a smaller to a subset of a bigger structure
* the bigger structure is built from the smaller one (i.e., we cannot simply *define* the smaller one as a subset of the bigger one because we need it to build the bigger one)
* the embedding of the smaller into the bigger structure preserves some operations (e.g., the embedding N -> Z is a semiring morphism, the embedding of R into R[X] is a ring moprhism) and can therefore not simply be represented as just a function
* the set preserved properties is extended later on as additional properties are considered (e.g., the embedding N -> Z is also an order morphism)
Virtually all tools for formalized mathematics cannot handle this at all, let alone elegantly.
It requires fundamentally different formal systems that we have not designed yet.
# Idea
For a certain special case, theory morphisms may be a solution:
* We can define the structures as theories and the embedding as a theory morphism, e.g.,
* N={n: type, z: n, s: n->n}
* Z={i: type, z:i, s:i->i, p:i->i, s(p(x)=x, p(s(x)=x, leq:i->i->prop}
* emb: N->Z = {n={x:i|z leq x}, z=z, s=s}
In particular, the theory morphism would capture which operations are preserved.
In this topic, you build a case study formalizing canonical isomorphisms in this way.
You will identify and possibly solve any theoretical or practical problems that come up along the way.
# Technical Problems
## Weak Embeddings
Often the embedding function is not a theory morphism because it does not preserve all properties of a structure s.
Such embeddings can only be expressed as theory morphism out of S if S is an inadequately weak formalization of s.
Often the theory S amounts to specifying a category in which s is the initial object.
More generally, we can think of s as the structure that is freely generated by the syntax of S.
An important special case are non-injective embeddings.
For example, the embedding of the natural numbers into the theory of rings is not necessarily injective.
This can only be expressed as a theory morphism if the natural numbers are formulated without the injectivity of successor.
Similarly, we may have to allow for non-surjective embeddings if we cannot capture the image of the embedding as a predicate subtype (e.g., when embedding natural numbers into real numbers, where the logic cannot express the needed predicate).
In the case of natural numbers, this means the induction axiom should be optional as well.
## Models as Theories
There are multiple ways to represent mathematical structures (here called models) in a formal system.
*Concrete* models of theory T are given as tuples of their universes and operations, e.g., (N,0,1+,*) for the semiring of natural numbers.
(Technically, this tuple also includes proofs of all axioms.)
Concrete models can be represented in two different way:
* internal models: models are represented as record values of a record type corresponding to T
* external models: models are represented as theory morphisms out of T
*Abstract* models of theory T are represented as theories.
These theories contain undefined constants and axioms. Examples are the models for N and Z above.
Typically, these theories M extend T or admit very simpl morphisms, usually injective renamings, T -> M.
The critical idea of this case study is to use abstract models.
This is the only way that allow using theory morphisms for the embeddings.
It remains open how this relates to other, concrete, representations of models.https://gl.kwarc.info/kwarc/thesis-projects/-/issues/23Formalization of legal content2019-05-02T10:12:22ZMax RappFormalization of legal contentAs part of the ALMANAC-project, we are currently developing new MMT-modules to deal with conflict-laden content. These include context graphs (theory graphs with attack relations), formalizations of nonmonotonic logics and argumentation ...As part of the ALMANAC-project, we are currently developing new MMT-modules to deal with conflict-laden content. These include context graphs (theory graphs with attack relations), formalizations of nonmonotonic logics and argumentation theories (as context graphs or in classical MMT) and computation and visualization components (Embedding of argumentation semantic solvers, TGView graph viewer).
The goal of this project is a first application of these developments in an effort to formalize paradigmatic documents (rulings, example cases) in law. Legal content involves a plethora of interesting formalization challenges such as defeasible reasoning, ambibuity, precedence and argumentation. There for it provides an ideal arena to gain a sense of the current capabilities of our systems as well as the open requirements.
The project would entail choosing a suitable document (or collection of documents) and flexiformalizing it. The final document will include content of various formalization levels which can be visualized and processed by ALMANAC's graphical and computational tools. The undertaking would be closely supervised jointly by members of the ALMANAC-project and our Legal-Tech cooperation partner [Prof. Dr. Axel Adrian](https://www.str2.rw.fau.de/lehrstuhl/honorarprofessor/).https://gl.kwarc.info/kwarc/thesis-projects/-/issues/22Formalize Haskell Type Classes as a Theory Graph2021-10-21T16:06:03ZFlorian RabeFormalize Haskell Type Classes as a Theory GraphChoose a logical framework, e.g., LF, and formalize (a simple fragment of) Haskell in it.
Then use that theory as a meta-theory for a theory graph containing the standard type classes.
This includes in particular the various kinds of Mo...Choose a logical framework, e.g., LF, and formalize (a simple fragment of) Haskell in it.
Then use that theory as a meta-theory for a theory graph containing the standard type classes.
This includes in particular the various kinds of Monad classes and their implementations
There are multiple variants of Monad, some related by include, some by view.
Interestingly, because Haskell is a programming language, the Monad *laws* are often spelt out in a formal system.
That can lead to confusion, and a clean theory would be very helpful.https://gl.kwarc.info/kwarc/thesis-projects/-/issues/21Data Dimension for MathHub.info2018-07-25T00:03:43ZMichael Kohlhasemichael.kohlhase@fau.deData Dimension for MathHub.infoThe [MathHub.info](http://mathhub.info) system currently only has active/semantic documents and theory graphs. But we would like to integrate and host mathematical data bases like the [OEIS](http://oeis.org) or [LMFDB](http://lmfdb.org) ...The [MathHub.info](http://mathhub.info) system currently only has active/semantic documents and theory graphs. But we would like to integrate and host mathematical data bases like the [OEIS](http://oeis.org) or [LMFDB](http://lmfdb.org) with mathematical interfaces.
The theory and part of the implementation has already been done in [virtual theories](https://github.com/OpenDreamKit/OpenDreamKit/blob/master/WP6/MACIS17-vt/crc.pdf) and is proposed as part of #20. Now we need to build the infrastruture in [MathHub.info](http://mathhub.info). Concretely, this involves
* installing and exposing a data base server as <http://data.mathhub.info> (probably Postgres or so)
* extending the MMT `lmh` extension to create data bases for any archive with virtual theories (i.e. theories for which the necessary codecs and schema theories exist)
* developing a process for syncing the access permissions in the data base with those for the archive at http://gl.mathhub.info
* develop a MMT `data` extension with a structure component that creates/updates tables for MMT theories and whose object component uses queries for MMT expressions.https://gl.kwarc.info/kwarc/thesis-projects/-/issues/20Representing Relational Databases in a Logical Framework2019-10-08T11:08:32ZFlorian RabeRepresenting Relational Databases in a Logical Framework@kohlhase @twiesing
There is a very elegant embedding of relational databases into MMT.
* We write a theory D that declares all the basic datatypes (integers, string, products, etc.) of the database language.
* A table schema is repres...@kohlhase @twiesing
There is a very elegant embedding of relational databases into MMT.
* We write a theory D that declares all the basic datatypes (integers, string, products, etc.) of the database language.
* A table schema is represented as a theory S with meta-theory D. The constants of S correspond to the columns of the table.
* Local consistency conditions (which are often omitted in relational databases) are represented as axioms in S.
* A table entry in S is represented as a morphism S -> D, i.e., entries are records whose fields are given by S.
* A join is represented as a pushout.
For example, the join of S with S' where the field f of S should be equal to the field f' of S', is the pushout of {f} -include-> S and {f} -{f=f'}-> S'.
The entries of the join are the set of universal morphisms out of the pushout for every pair (e,e') of entries for which the respective diagram commutes.
* A database view providing a table S backed by a table T are MMT morphisms m is represented as a morphism S -> T.
As a special case, include morphisms represent the selection of some columns from a table.
The entries of the view are the morphisms m;e for all entries e of T.
* A writable view providing S backed by T allows modifying an entry of T if the change can be propagated back to the corresponding entry of T.
If T is a declared theory, this is possible if m is a renaming/inclusion.
If m is a view or join, this is more complicated.
The goal of this topic is to
* work out the details of the above
* investigate the propagation of changes along writable views in general
* determine how these representations can be used to provide added value to database applications
In particular, we could represent the schema of a database in MMT (as sets of theories and views).
The entries would be stored in an actual database.
The theory D can use high-level datatypes, which MMT's codecs translate to the concrete types of the database.
Queries (like joins, selections, and views) can be formulated in MMT and translated to relational queries; conversely, entries can be translated back to MMT views.https://gl.kwarc.info/kwarc/thesis-projects/-/issues/19MMT as a parser framework for Scala APIs2018-07-02T20:21:23ZFlorian RabeMMT as a parser framework for Scala APIsSee https://github.com/UniFormal/MMT/issues/368See https://github.com/UniFormal/MMT/issues/368https://gl.kwarc.info/kwarc/thesis-projects/-/issues/18Integrate Kwarc tools with GitLab2018-05-17T13:20:01ZFlorian RabeIntegrate Kwarc tools with GitLabGitLab is a major open-source locally-installable GitHub-style git repository manager.
The Kwarc uses it as the backend of our MathHub system. See [https://gl.mathhub.info/users/sign_in](https://gl.mathhub.info/users/sign_in).
GitLab is...GitLab is a major open-source locally-installable GitHub-style git repository manager.
The Kwarc uses it as the backend of our MathHub system. See [https://gl.mathhub.info/users/sign_in](https://gl.mathhub.info/users/sign_in).
GitLab is mostly monolithic, but like any open-source toll it must offer some interface to customize it.
In this project, a student
* peruses GitLab for such options
* identifies potential for integrating Kwarc knowledge management solutions with it
* designs and implements these integrations
Examples and starting points:
* GitLab uses some general purpose syntax highlighting framework.
But currently our .mmt files are rendered as plain text.
Find out which framework GitLab uses, write a syntax highlighter for .mmt files in it, and configure GitLab to use it.
* GitLab provides a very simple plugin interface for event handling.
Write an even handler that scans every new issue for special annotations that tie individual issues to MMT URIs.
Then customize MMT-based tools to display links to these issues, e.g., jEdit can display button whenever an issue for a declaration exists.https://gl.kwarc.info/kwarc/thesis-projects/-/issues/17applications of viewfinding2018-05-15T06:02:08ZMichael Kohlhasemichael.kohlhase@fau.deapplications of viewfinding@dmueller has recently implemented a viewfinder, i.e. a function that finds MMT views (and partial ones as well) in an OMDoc/MMT library or between more than one. This [paper](http://kwarc.info/kohlhase/submit/cicm18-viewfinder.pdf) des...@dmueller has recently implemented a viewfinder, i.e. a function that finds MMT views (and partial ones as well) in an OMDoc/MMT library or between more than one. This [paper](http://kwarc.info/kohlhase/submit/cicm18-viewfinder.pdf) describes the specifics and lists a bunch of applications in the back. The project is to implement one or more of these applications in [MathHub](https://mathhub.info).
The necessary steps are
* fully understand viewfinding and the intended application
* build an extended example and produce the mathematical resources
* specify the context of use and the user interactdions
* build a front-end that supports these.https://gl.kwarc.info/kwarc/thesis-projects/-/issues/16implementing Realms as an MMT structural feature2018-02-07T14:41:37ZMichael Kohlhasemichael.kohlhase@fau.deimplementing Realms as an MMT structural featureWe have this global language feature of realms, see http://kwarc.info/kohlhase/papers/cicm14-realms.pdf and http://kwarc.info/kohlhase/papers/cicm15-induced.pdf and http://kwarc.info/kohlhase/papers/cicm15-recaps.pdf This is a very well-...We have this global language feature of realms, see http://kwarc.info/kohlhase/papers/cicm14-realms.pdf and http://kwarc.info/kohlhase/papers/cicm15-induced.pdf and http://kwarc.info/kohlhase/papers/cicm15-recaps.pdf This is a very well-understood practical device that makes theory graphs much closer to mathematical practice.
This needs to be implemented in MMT (following and building on Mihnea Iancu's thesis), and a management interface needs to be designed. And of course tested on the examples Mihnea and I have designed. Michael Kohlhasemichael.kohlhase@fau.deMichael Kohlhasemichael.kohlhase@fau.de