Comparative Mind Database


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Comparative Mind Database


Video Sharing and Deep Tagging Portal at: www.cmdbase.or




Comparative Social Cognition is the study of animal and human minds across different species, which involves several deep and undersolved conceptual and methodological questions. An aim of the ESF funded CompCog project is to help understand them better.

Despite the existence of a large body of fragmented knowledge, we currently don’t understand human and animal cognition. What is the animal that we talk about, how can it be conceptualized? What are the terms to be used, and how they are backed up in the various disciplines? How can different species and different experiments be compared, if they measure different things? What are justifyable conceptual and experimental methods that can support reproducibility, scalability, generalizability?


The Comparative Mind Database is a module of the CompCog project that supports the inquiry using innovative, advanced information technologies and methods from philosophy of science, statistics, experimental design and data/text mining.


Components include: data aquisition and description mehods, data and text mining for conceptual analysis, ontologies for animal cognition, integrated tools for the design and analysis of experiments (DoE), work towards the standards of experiments, their communication and evaluation Concepts.


Concepts.Text mining tools might help to map, learn and navigate the conceptual fields that characterize the topics of interest in order to facilitate communication and a better understanding between experts. E.g. topic 1 below.


Database. Many of the above topics point towards the usefulness of a comprehensive, integrated database that uses suggestive tools for the acquisition, handling and analysis of data. The database could be also suggestive for a unified documentation, synthesis and repository of much existing information. E.g. topic 3 below.


Experimental protocols and data description formats including video protocols might be a significant step towards finding a common language. E.g. topic 4 below.


Ontology. The problem of cross-comparisons and different markers points towards the necessity of a formal, flexible representation of animal data currently supported by ICT methods commonly called ontologies. Developing an ontology could also support and standardize many statistical comparisons. E.g. topic 3 below.


Design and Analysis of Experiments (DoE). Effects of sample size, repetitions on the same animals, the use of different statistical methods, or different markers can be handled by modern tools that can be integrated into easy-to-use, automated platforms. Such platforms could also be suggestive in what factors are to be considered, and how new techniques help (re)evaluate new and old results? E.g. topic 2 below.


Example topics and pilot studies in CMD:

  • Text mining and trend analysis for key concepts. Example: „intentionality” and „imitation” (Fig.1, Sandor Soos)
  • Advanced DoE without tears. Example: the MEME system (Fig 2., Laszlo Gulyas)
  • Powerful, suggestive data description formats. Example:  Social cognition markup language (Fig 3, illustration)
  • Unified protocols for experiments. Example: video protocols (Fig 4, illustration)



Fig 1. Topic clusters and conceptual networks in publications using the key word „intentionality” (Sandor Soos, pilot study for the CMD module)




Fig 2. The MEME toolkit for DoE and experimental analysis ((Laszlo Gulyas, pilot study for the CMD module)




Fig 3. Example: The Systems Biology Markup Language (as an analogy)




Fig.4. Example: video communication used in experimental protocols (just to illustrate the idea)

conceptual network


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