This document discusses the iterative process of co-creating an ontology with stakeholders. Researchers conducted contextual inquiries through documentation analysis, observations, and interviews across multiple healthcare sites. Scenarios were developed and used in workshops with various stakeholders including medical professionals, engineers, and social scientists. The workshops introduced ontologies and involved role playing, decision making, and concept evaluation. A proof of concept was developed using a personal electronic device to demonstrate the ontology. The document reflects on further refining the process and developing the research.
Tijdens het tweede Cultuurdebat in Arnhem geeft Erik Vos een presentatie over zijn ontwerppraktijk. Het Lab heeft deelgenomen aan Power to Arnhem en daar zijn verschillende lessen uit te trekken. Corss-overs en kruisbestuivingen leveren innovatieve ideeën op.
Tijdens het tweede Cultuurdebat in Arnhem geeft Erik Vos een presentatie over zijn ontwerppraktijk. Het Lab heeft deelgenomen aan Power to Arnhem en daar zijn verschillende lessen uit te trekken. Corss-overs en kruisbestuivingen leveren innovatieve ideeën op.
Describing latest research in visual reasoning, in particular visual question answering. Covering both images and videos. Dual-process theories approach. Relational memory.
Deep Learning has taken the digital world by storm. As a general purpose technology, it is now present in all walks of life. Although the fundamental developments in methodology have been slowing down in the past few years, applications are flourishing with major breakthroughs in Computer Vision, NLP and Biomedical Sciences. The primary successes can be attributed to the availability of large labelled data, powerful GPU servers and programming frameworks, and advances in neural architecture engineering. This combination enables rapid construction of large, efficient neural networks that scale to the real world. But the fundamental questions of unsupervised learning, deep reasoning, and rapid contextual adaptation remain unsolved. We shall call what we currently have Deep Learning 1.0, and the next possible breakthroughs as Deep Learning 2.0.
This is part 2 of the Tutorial delivered at IEEE SSCI 2020, Canberra, December 1st (Virtual).
Describing latest research in visual reasoning, in particular visual question answering. Covering both images and videos. Dual-process theories approach. Relational memory.
Deep Learning has taken the digital world by storm. As a general purpose technology, it is now present in all walks of life. Although the fundamental developments in methodology have been slowing down in the past few years, applications are flourishing with major breakthroughs in Computer Vision, NLP and Biomedical Sciences. The primary successes can be attributed to the availability of large labelled data, powerful GPU servers and programming frameworks, and advances in neural architecture engineering. This combination enables rapid construction of large, efficient neural networks that scale to the real world. But the fundamental questions of unsupervised learning, deep reasoning, and rapid contextual adaptation remain unsolved. We shall call what we currently have Deep Learning 1.0, and the next possible breakthroughs as Deep Learning 2.0.
This is part 2 of the Tutorial delivered at IEEE SSCI 2020, Canberra, December 1st (Virtual).
BigML's take on Big Data. University of Geneva, October 12, 2012.
In the "Big Data" era, rapidly and easily getting insights from your data or creating data-driven applications does not have to be painful. BigML shows how business managers, application developers, and data scientists can start building their own predictive models in a matter of minutes.
Computational Rationality I - a Lecture at Aalto University by Antti OulasvirtaAalto University
This 2-hour lecture looks at the emerging field of Computational Rationality. Lecture given March 12, 2018, for the Aalto University Master's level course on "Probabilistic Programming and Reinforcement Learning for Cognition and Interaction." Based on: Gershman et al 2015 Science, Lewis et al 2014 Topics in Cog Sci, and Gershman & Daw 2017 Annu Rev Psych
4. And it sounded like….
“An ontology is a specification of a conceptualization in
= specification of a conceptualization
the context of knowledge description.”
in the context of knowledge description.
has_symptom Symptom
* Is a
Disease
Fever
has_treatment Temp
Treatment
Curable Disease
Disease
*
has_treatment.Treatment Antibiotics
= capture what domain expert commonly understand about a domain
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6. User-centered ontology co-creation
+ +
Initial Other
Analysis of current system
scenario ontologies
& workspractices in domain
Ontology engineer(s)
User researcher(s) Scenarios
& probing exercises
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8. Observations
Contextual Inquiry:
Document analysis
Observation
Interdisciplinary
2 intramural sites:
Care centre for people with
severe dependencies
Hospital
Emergency unit
Neurology ward
8
10. Co-creation workshops
Mix of stakeholders:
Ontology engineers
Potential end users: nurses, doctors, …
Professional working for healthcare industry
Social scientists
Different types of workshops
type 1: introducing ontologies
type 2: role play
type 3: decision making
type 4: concept evaluation workshop
type 5: embodied system use workshop
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15. Where do we go from here?
Back to the drawing board….
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16. Time for interaction
Interactive demo set up on Proof of Concept
Snap shot workshop on ontology co-creation
Short testimonials
Reflect on future research topics
Reflect on reseach methodology
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