Full-text resources of CEJSH and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl


2017 | 23 | 25-41

Article title

Transdziedzinowe aspekty struktur modularnych. O aplikacji modularyzacji w ramach inżynierii wiedzy i kognitywistyki.



Title variants

Trans-Domain Aspects of Modular Structures. Applying Modularization in Knowledge Engineering and Cognitive Science.

Languages of publication



Zastosowanie struktury modularnej w ramach różnych rozwiązań: tak inżynieryjnych, jak i teoretycznych niesie ze sobą pewne ograniczenia. Problemy te są bardzo widoczne w obrębie dyskursu na temat projektowania modularnych ontologii oraz wdrażania technologii Semantic Web. Pomimo szerokiego zakresu problemów związanych z aplikacją modularności w inżynierii wiedzy, istnieje wciąż niewyczerpane źródło innowacji oraz nowoczesnych inspiracji dla przezwyciężania problemów z metamodelowaniem, projektowaniem oraz hybrydyzacją systemów reprezentacji wiedzy. Inspirowanie się naturalnymi przejawami struktur modularnych może stanowić źródło wielu innowacji oraz podłoże do opracowania nowych podejść tak w dziedzinie inżynierii wiedzy, jak kognitywistyki. Z uwagi na nawiązanie do obliczeniowego charakteru struktur modularnych obecnych w rozmaitych dziedzinach o charakterze interdyscyplinarnym, można dotrzeć do konkluzji, że pewne obserwowalne prawidłowości związane z organizacją sieci (np. stopniami i rodzajami centralności) są w istocie transdziedzinowe (tzn. wykraczają poza dziedzinę, w której zostały pierwotnie zastosowane, mając potencjał do wykorzystania w innej dziedzinie badającej struktury relacyjne różnego rodzaju) bądź przynajmniej mają charakter projekcyjny w odniesieniu do metamodelowania ontologii.
The application of modular structure in the context of various solutions, both engineering and theoretical, possesses certain limitations. The problems that arise are very salient amidst the discourse concerning the design of modular ontologies and implementation of Semantic Web technologies. Despite a wide array of obstacles related to aptly used modularity in knowledge engineering, there is still a never-ending source of inspiration for the solutions concerning metamodeling, designing and hybridizing knowledge representation systems. Being inspired by natural occurrences of modular structures can be a potent source of innovation and a foundation for developing new approaches both in the domain of knowledge engineering and cognitive science. Due to reference to the computational character of the modular structures present in various domains that are deemed interdisciplinary, one can arrive at the conclusion that certain observed regularities connected with network organisation (i.e., centrality types and measures) are in fact trans-domain (they go beyond their respective domain and have application in a different domain that concerns itself with studying relational structures of various forms) or they possess at least the projectional character in regard to ontology metamodeling.






Physical description




  • Kogni_LAB Uniwersytet Mikołaja Kopernika w Toruniu


  • Ackoff, R.L., From Data to Wisdom, „Journal of Applied Systems Analysis” 1989, nr 16(1).
  • Azam F., Biologically Inspired Modular Neural Networks, Blacksburg, Virginia 2000.
  • Badia L., Bonner A., Soler A., Who Was Ramon Llull?, Centre de Documentacio Ramon Llull, [online] <http://quisestlullus.narpan.net/eng/713_arbre_eng.html>
  • Bassett D.S., Greenfield D.L., Meyer-Lindenberg A., Weinberger D.R., Moore S.W., Bullmore E.T., Efficient Physical Embedding of Topologically Complex Information Processing Networks in Brains and Computer Circuits, „PloS Computer Biology” 2010, t. 6.
  • Berners-Lee T., Hendler J., Lassila O., The Semantic Web, „Scientific American” 2001, nr 284(5).
  • Bonacich P., Paulette L., Eigenvector-Like Measures of Centrality for Asymmetric Relations, „Social Networks” 2001, t. 23.
  • Brank J., Grobelnik M., Mladenic D., A Survey of Ontology Evaluation Techniques, Proceedings of the conference on data mining and data warehouses, SiKDD 2005.
  • Bullmore E., Sporns O., Complex Brain Nnetworks: Graph Theoretical Analysis of Structural and Functional Systems, „Nature Reviews Neuroscience” 2009, nr 10(3).
  • Carriere S.J., Kazman R., , Web Query: Searching and Visualizing the Web through Connectivity, „Computer Networks and ISDN Systems” 1997, t. 29.
  • Cheng F., Jia P., Wang Q., Zhao Z., Quantitative Network Mapping of the Human Kinome Interactome Reveals New Clues for Rational Kinase Inhibitor Discovery and Individualized Cancer Therapy, „Oncotarget” 2014, t. 15.
  • De Las Rivas J., Prieto C., Protein Interactions: Mapping Interactome Networks to Support Drug Target Discovery and Selection, „Methods in Molecular Biology” 2012.
  • Erétéo G., Buffa M., Gandon F., Grohan P., Leitzelman M., Sander P., A State of the Art on Social Network Analysis and Its Applications on a Semantic Web, SDoW 2008.
  • Guy K. (red.), Lipton P., Hoare T., O’Hara K. i in. Philosophy of Engineering, „The Royal Academy of Engineering” 2010, t. 1–2.
  • Grau B. C., Horrocks I., Kazakov Y., Sattler U., A Logical Framework for Modularity of Ontologies, IJCAI 2007.
  • Hachem S., Teixeira T., Issarny V., Ontologies for the Internet of Things, „Proceedings of the 8th Middleware Doctoral Symposium”, ACM 2011.
  • Honey C.J., Sporns O., Cammoun L., Gigandet X., Thiran J.P., Meuli R., Hagmann P., Predicting Human Resting-State Functional Connectivity from Structural Connectivity, „Proceedings of National Academy of Science” 2009.
  • Jacob F., Evolution and Tinkering, „Science” 1977.
  • Jensen O.N., Modification-Specific Proteomics: Characterization of Post-Translational Modifications by Mass Spectrometry, „Current Opinion in Chemical Biology” 2004, t. 8.
  • Katifori A., Halatsis C., Lepouras G., Vassilakis C., Giannopoulou E., Ontology Visualization Methods – A Survey, ACM Computing Surveys (CSUR), (2007), nr 39(4).
  • Keerthana M., Ashika Parveen S., Internet of Things, „International Journal of Advanced Research Methodology in Engineering and Technology” 2017, nr 1(2).
  • Kollia I., Simou G., Stamou G., Stafylopatis A., Interweaving Knowledge Representation and Adaptive Neural Networks, National Technical University of Athens, Workshop on Inductive Reasoning and Machine Learning on the Semantic Web 2009.
  • Newman M.E.J., Networks: An Introduction, Oxford University Press 2010.
  • Oberlaender A. M., Roeglinger M., Rosemann M., Kees A., Conceptualising Business--to-Thing Interactions – A Sociomaterial Perspective on the Internet of Things, „European Journal of Information Systems” 2017.`
  • Peng Y., Ontology Mapping Neural Network: An Approach to Learning and Inferring Correspondences Among Ontologies, University of Pittsburgh 2010.
  • Roche C., Network Analysis of Semantic Web Ontologies, Stanford CS224W Social and Information Network Analysis 2011.
  • Sporns O., The Human Connectome: A Complex Nnetwork, “Annals of the New York Academy of Sciences” 2011, nr 1224(1).
  • Tan H., Muhammad I., Tarasov V., Adlemo A., Johansson M., Development and Evaluation of a Software Requirements Ontology, (w:) 7th International Workshop on Software Knowledge-SKY 2016, 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management-IC3K 2016.
  • Tergan S.O., Kelle T. (red.), Knowledge and Information Visualization: Searching for Synergies, Springer 2005, t. 3426.
  • Xiao Ch., Tao X., Yun L., Kai W., Dynamic Modular Architecture of Protein-Protein Interaction Networks Beyond the Dichotomy of „Date” and „Party” Hubs, „Scientific Reports” 2013, t. 3.
  • Zhang Q., Cheng L., Boutaba R., Cloud Computing: State-of-the-Art and Research Challenges, „Journal of Internet Services and Applications” 2010, nr 1(1).
  • Zuo X.N., Ehmke R., Mennes M., Imperati O., Castellanos F.X., Sporns O., Milham M.P., Network Centrality in the Human Functional Connectome, “Cerebral Cortex” 2012, t. 22.

Document Type

Publication order reference



YADDA identifier

JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.