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008			231117s2023 sz | fo |||| 0|eng d
020			_a9783031396953
024	7		_a10.1007/978-3-031-39695-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9 .S88 _b2023 EB
100	1		_aKeet, C. Maria _eautor _0(orcid)0000-0002-8281-0853 _1https://orcid.org/0000-0002-8281-0853 _4http://id.loc.gov/vocabulary/relators/aut _9690149
245	1	4	_aThe What and How of Modelling Information and Knowledge : _bFrom Mind Maps to Ontologies _cby C. Maria Keet
250			_a1st ed 2023
264		1	_aCham _bSpringer Nature Switzerland _c2023
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_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.
520			_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.
988			_aSpringer_Computer_2023
650		7	_2embne _9158356 _aDiseño de sistemas
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-39695-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2024 _dz _ean _zSI