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  2. Data model - Wikipedia

    en.wikipedia.org/wiki/Data_model

    Overview of a data-modeling context: Data model is based on Data, Data relationship, Data semantic and Data constraint. A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision.

  3. Data modeling - Wikipedia

    en.wikipedia.org/wiki/Data_modeling

    Data modeling in software engineering is the process of creating a data model for an information system by applying certain formal techniques.

  4. Modeling and simulation - Wikipedia

    en.wikipedia.org/wiki/Modeling_and_simulation

    Modeling and simulation (M&S) is the use of models (e.g., physical, mathematical, behavioral, or logical representation of a system, entity, phenomenon, or process) as a basis for simulations to develop data utilized for managerial or technical decision making. [1] [2]

  5. Mathematical model - Wikipedia

    en.wikipedia.org/wiki/Mathematical_model

    If the model was constructed based on a set of data, one must determine for which systems or situations the known data is a "typical" set of data. The question of whether the model describes well the properties of the system between data points is called interpolation , and the same question for events or data points outside the observed data ...

  6. Data model (GIS) - Wikipedia

    en.wikipedia.org/wiki/Data_model_(GIS)

    A hybrid topological data model has the option of storing topological relationship information as a separate layer built on top of a spaghetti data set. An example is the network dataset within the Esri geodatabase. [23] Vector data are commonly used to represent conceptual objects (e.g., trees, buildings, counties), but they can also represent ...

  7. Predictive modelling - Wikipedia

    en.wikipedia.org/wiki/Predictive_modelling

    In all data collection, the collector first defines the set of variables for which data is collected. However, no matter how extensive the collector considers his/her selection of the variables, there is always the possibility of new variables that have not been considered or even defined, yet are critical to the outcome.

  8. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [4] Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5]

  9. Health informatics - Wikipedia

    en.wikipedia.org/wiki/Health_informatics

    An example of an application of informatics in medicine is bioimage informatics.. Dutch former professor of medical informatics Jan van Bemmel has described medical informatics as the theoretical and practical aspects of information processing and communication based on knowledge and experience derived from processes in medicine and health care.