LEADER 04315nam 22006375 450 001 996565862903316 005 20231117163102.0 010 $a3-031-39695-2 024 7 $a10.1007/978-3-031-39695-3 035 $a(CKB)29020630600041 035 $a(DE-He213)978-3-031-39695-3 035 $a(MiAaPQ)EBC31070092 035 $a(Au-PeEL)EBL31070092 035 $a(EXLCZ)9929020630600041 100 $a20231117d2023 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 14$aThe What and How of Modelling Information and Knowledge$b[electronic resource] $eFrom Mind Maps to Ontologies /$fby C. Maria Keet 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (XIV, 177 p. 40 illus., 17 illus. in color.) 311 08$a9783031396946 327 $a1. Introduction: Why Modelling? -- 2. Mind Maps -- 3. Models and Diagrams in Biology -- 4. Conceptual Data Models -- 5. Ontologies and Similar Artefacts -- 6. Ontology?With a Capital O -- 7. Fit For Purpose -- 8. Go Forth and Model. 330 $aThe main aim of this book is to introduce a group of models and modelling of information and knowledge comprehensibly. Such models and the processes for how to create them help to improve the skills to analyse and structure thoughts and ideas, to become more precise, to gain a deeper understanding of the matter being modelled, and to assist with specific tasks where modelling helps, such as reading comprehension and summarisation of text. The book draws ideas and transferrable approaches from the plethora of types of models and the methods, techniques, tools, procedures, and methodologies to create them in computer science. This book covers five principal declarative modelling approaches to model information and knowledge for different, yet related, purposes. It starts with entry-level mind mapping, to proceed to biological models and diagrams, onward to conceptual data models in software development, and from there to ontologies in artificial intelligence and all the way to ontology in philosophy. Each successive chapter about a type of model solves limitations of the preceding one and turns up the analytical skills a notch. These what-and-how for each type of model is followed by an integrative chapter that ties them together, comparing their strengths and key characteristics, ethics in modelling, and how to design a modelling language. In so doing, we?ll address key questions such as: what type of models are there? How do you build one? What can you do with a model? Which type of model is best for what purpose? Why do all that modelling? The intended audience for this book is professionals, students, and academics in disciplines where systematic information modelling and knowledge representation is much less common than in computing, such as in commerce, biology, law, and humanities. And if a computer science student or a software developer needs a quick refresher on conceptual data models or a short solid overview of ontologies, then this book will serve them well. 606 $aKnowledge management 606 $aInformation modeling 606 $aAnalysis (Philosophy) 606 $aApplication software 606 $aSoftware engineering 606 $aKnowledge Management 606 $aInformation Model 606 $aConceptual Analysis 606 $aComputer and Information Systems Applications 606 $aSoftware Engineering 615 0$aKnowledge management. 615 0$aInformation modeling. 615 0$aAnalysis (Philosophy). 615 0$aApplication software. 615 0$aSoftware engineering. 615 14$aKnowledge Management. 615 24$aInformation Model. 615 24$aConceptual Analysis. 615 24$aComputer and Information Systems Applications. 615 24$aSoftware Engineering. 676 $a658.4038 700 $aKeet$b C. Maria$4aut$4http://id.loc.gov/vocabulary/relators/aut$01448636 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996565862903316 996 $aThe What and How of Modelling Information and Knowledge$93644345 997 $aUNISA