- Prof. Dr. Thorsten Fehr
- Prof. Dr. Uwe Engel
Task Area Community Interaction Surveys is concerned with conducting remote surveys to identify white spots of RDM in our commmunities and advise other task areas where to recruit new use cases. In addition, and in collaboration with Task Area Metadata & Ontologies, we will query the structure of an Ontology of Physics via automated patching of large datasets covering domain semantic order. We will combine the set of tools available via Survey Methodology and contextual binary decision-making experiments. A modern Ontology of Physics will be constructed as a probability network of nodes and links. The most probable sub-graph will be identified as the current Ontology of Physics. We will do this in a two step process. First we allow for a free textual response. Probabilities of nodes and links will be determined by Entity Typing [Reference] or another appropriate tools of semantic textual analysis based on machine learning algorithms. Second, in order to ensure a proper ontology, we provide a pre-selected terminology gathered in the first step which is allowed to be arranged according to majority opinion within our domains.
Use Case Standard Physics
The Task Area Community Interactions Use Case Standard Physics develops in close cooperation with all task areas and in close communication with all domains a paradigmatic use case standard for all disciplines of physics.
The idea is to start with a minimal set of tools and descriptions and expand it further and further. A first skeleton would consist of a data model that “modularly pre-thinks” e.g. files, devices and processes but does not specify their parameters.
This is an overall task of all domains and task areas. Each task area must deliver something “minimally structuring” for its core task. All these deliverables must a) fit together and b) make all domains connectable. This is the only way to create synergy between our Use cases.
Domains & Interfaces
- Domain Leaders
- Speakers/Heads of other consortia/institutions
The Task Area Community Interaction Domains & Interfaces establishes contact between domains within the consortium and via our interfaces to other consortia. Our spokesperson and all domain leaders together with interested colleagues from other consortia identify mutual topics of interest for discussion and possible formal agreement. We are fostering our guiding principle of a dual infrastructure consisting of technology and human scientific discourse alike.
Central to our goal, minimal heterogeneous RDM of physical laboratories, is the dissemination of results obtained and services rendered by our task areas into the various domain specific communities. While the Task Area Community Interaction Surveys is concerned with finding and addressing specific needs within our domains and concentrates on knowledge spread out over the communities, Domains & Interfaces distributes the results of our work back into them.
In addition to RDM, we are focusing mainly on the role of information in different disciplines of Transdisciplinar Physics which typically differ in complexity of their field. Key to measuring complexity is the amount and especially the kind of information [Floridi 2011, Jost 2020, Ellis 2020] different disciplines gather about their objects of study. In Statistical Physics, we find that the classical Shannon entropy measures the probability distribution of states. In cell biology, we realize that each protein carries certain functional information. In Computer Science, we are interested about the algorithmic transformation of an input to an output. Cognitive Science asserts how we perceive our environment and control behavior accordingly. Psychology is concerned with the assessment of our perceptions and ensuing actions. Finally, Philosophy forms assessments and principles into knowledge and is concerned with a theory of the mind.
All these statements make sense in one way or another, but can we somehow come up with a more concise way of formulation? Indeed, Luciano Floridi provides a precise and thorough classification of information in his central book on The Philosophy of Information [Floridi 2011]. Especially, he performs a sequential construction to develop the attributes which data need to have in order to count as knowledge. Semantic information is neccessarily well-formed, meaningful and truthful. Well-informed data becomes meaningful by action based-semantics of an autonomous-agent solving the symbol grounding problem by herself interacting with the environment. Knowledge ensues than by being informed by relevant accounted data.
We will engage in semantic mapping of various ontologies as used by neighboring disciplines and provide semantic analysis where appropriate and needed. Semantic work is performed in close collaboration and guidance by the working group on semantics established in the FDO forum.