# orderedItems[].content
Das #FireShonks Video

"Konstruktive digitale Diskussionskultur"
(#KDDK) ist online.

https://media.ccc.de/v/37c3-57963-kons truktive-digitale-diskussionskultur-kddk

Meine Soundkarte hatte einen leicht brummeligen Tag, aber die Inhalte kommen hoffentlich trotzdem rüber.

Vielen Dank ans #shonks23 Team für das möglich Machen!

#37C3 #shonks

# orderedItems[].contentMap.de
Das #FireShonks Video

"Konstruktive digitale Diskussionskultur"
(#KDDK) ist online.

https://media.ccc.de/v/37c3-57963-kons truktive-digitale-diskussionskultur-kddk

Meine Soundkarte hatte einen leicht brummeligen Tag, aber die Inhalte kommen hoffentlich trotzdem rüber.

Vielen Dank ans #shonks23 Team für das möglich Machen!

#37C3 #shonks

# orderedItems[].attachment[].name
Screenshot aus Video.


Zu sehen ist die Titelfolie

Überschrift:
Konstruktive digitale Diskussionskultur

Untertitel:
Warum sind digitale Diskussionen so frustrierend und wie können sie besser werden?

Rechts unten ist das Kamerabild des Sprechers eingeblendet.

# orderedItems[].content
Recently, I submitted the first big paper on our #Python :python: based approach for #FormalKnowledgeRepresentation.

If accepted, it will be #OpenAccess

The preprint is OA anyway:

https://www. preprints.org/manuscript/20240 1.0060/v1

The approach allows to model the content of mathematical theorems (such as Pythagoras) as nodes and edges in a #knowledgegraph

This is done via *qualifiers* – a concept borrowed from #Wikidata

#PyIRK

# orderedItems[].contentMap.en
Recently, I submitted the first big paper on our #Python :python: based approach for #FormalKnowledgeRepresentation.

If accepted, it will be #OpenAccess

The preprint is OA anyway:

https://www. preprints.org/manuscript/20240 1.0060/v1

The approach allows to model the content of mathematical theorems (such as Pythagoras) as nodes and edges in a #knowledgegraph

This is done via *qualifiers* – a concept borrowed from #Wikidata

#PyIRK

# orderedItems[].attachment[].name
Screenshot of a page of the manuscript.

In the main part it shows a depiction of the (automatically) constructed knowledge graph. With ≈850 nodes and 
≈8000 edges.


The caption reads:

Visualization of the whole knowledge graph. While it is impossible to extract meaningful details from this picture it illustrates the high degree of interconnection. Edges of type R3["is subclass of"] are blue, R4["is instance of"] are orange and all other edges types are colored black.

# orderedItems[].content
re-#introduction as a scientist 👨‍🔬

Training: #Mecatronics + #ElectricalEngineering

Specialization: Nonlinear #ControlTheory #MachineLearning and #KnowledgeRepresentation

Long term mission: The knowledge to solve any problem in the world might be hidden in scattered PDF files that are barely read. I want to contribute to the improvement of this unsatisfactory situation, especially in the (partly overlapping) domains of #engineering and #sustainability

Also: Teaching #Python :python:

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# orderedItems[].contentMap.en
re-#introduction as a scientist 👨‍🔬

Training: #Mecatronics + #ElectricalEngineering

Specialization: Nonlinear #ControlTheory #MachineLearning and #KnowledgeRepresentation

Long term mission: The knowledge to solve any problem in the world might be hidden in scattered PDF files that are barely read. I want to contribute to the improvement of this unsatisfactory situation, especially in the (partly overlapping) domains of #engineering and #sustainability

Also: Teaching #Python :python:

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