Jove
Visualize
Contact Us

Related Concept Videos

Archival Research01:40

Archival Research

16.6K
Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
16.6K
Metacognition01:26

Metacognition

349
Metacognition is a conscious process where individuals are aware of their cognitive and executive processes, such as planning before solving a problem or self-monitoring during reading. For instance, a writer may need help with composing a piece. The situation involves a writer who is working on a piece of writing, but while doing so, they realize that something is missing. They notice that their characters lack depth or details. This realization occurs because the writer is reflecting on their...
349
Impact of Schemas01:30

Impact of Schemas

55
Schemas are cognitive structures that provide a framework for interpreting and organizing social information. They help individuals navigate complex environments by offering expectations about people, events, and behaviors. Schemas influence attention, encoding, and retrieval processes, thereby shaping the entire trajectory of information processing in social contexts.Attention and Cognitive LoadDuring initial attention, schemas function as filters that prioritize schema-consistent information,...
55
Schemata01:17

Schemata

182
A schema is a mental construct that organizes related concepts, allowing the brain to process information efficiently. Upon activation, schemata facilitate assumptions about people or objects.
Two types of schemata are:
182
Concepts and Prototypes01:24

Concepts and Prototypes

278
The human nervous system handles vast amounts of information by translating sensory stimuli into neural impulses, which the brain processes, creating thoughts expressed through language or stored as memories. The brain also synthesizes information from emotions and memories, which significantly influence thoughts and behaviors. This intricate process creates a comprehensive mental picture.
The brain organizes this information using concepts, which are mental categories grouping linguistic data,...
278
Schemas01:42

Schemas

12.1K
A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
12.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Performance of PRISM III and pediatric early warning score for predicting patients needing increased level of care in a pediatric intermediate care unit.

European journal of pediatrics·2026
Same author

Advanced Management of Severe Adenomyosis in IVF: A Personalized Approach With Extended GnRH Agonist and Letrozole Therapy.

Case reports in obstetrics and gynecology·2026
Same author

Optimizing mature oocyte yield in IVF: clinical comparison of r-hFSH+r-hLH and HMG in women with a stimulation dosage of at least 300 IU of gonadotropins.

Frontiers in endocrinology·2026
Same author

Multi-ignition fire complexes drive extreme fire years and impacts.

Science advances·2026
Same author

Beyond emotions: Social cognitive predictors of COVID-19 vaccination intentions before and after vaccine roll-out.

PLOS global public health·2026
Same author

Tracking mangrove restoration using a biogeochemical soil health index and ecosystem service indicators.

Scientific reports·2025
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Oct 25, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

783

A method for transforming knowledge discovery metamodel to ArchiMate models.

Ricardo Pérez-Castillo1, Andrea Delgado2, Francisco Ruiz3

  • 1Faculty of Social Sciences and IT, University of Castilla-La Mancha, Av. Real Fábrica de Sedas s/n, 45600 Talavera de La Reina, Spain.

Software and Systems Modeling
|August 9, 2021
PubMed
Summary

Enterprise architecture modelling is crucial for digital transformation. This study introduces automated ArchiMate model generation using the Knowledge Discovery Metamodel (KDM) for more accurate enterprise representations.

Keywords:
ATLArchiMateEnterprise architectureKnowledge discovery metamodelMDEModel transformation

More Related Videos

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

24.7K
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

1.2K

Related Experiment Videos

Last Updated: Oct 25, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

783
From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

24.7K
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

1.2K

Area of Science:

  • Information Systems Engineering
  • Software Architecture
  • Digital Transformation

Background:

  • Enterprise architecture (EA) is vital for managing IT and business integration during digital transformation.
  • Current EA modeling is manual, time-consuming, and error-prone, hindering continuous realignment.
  • Existing automated methods analyze artifacts in isolation, limiting comprehensive EA representation.

Purpose of the Study:

  • To propose an automated method for generating ArchiMate models from enterprise system artifacts.
  • To introduce the Knowledge Discovery Metamodel (KDM) as an intermediate representation for diverse artifacts.
  • To enable the exploitation of relationships between different artifact types for improved EA accuracy.

Main Methods:

  • Utilizing the Knowledge Discovery Metamodel (KDM) to consolidate information from various system artifacts (source code, databases, services).
  • Developing a model transformation process from the KDM metamodel to the ArchiMate metamodel.
  • Automating the analysis and integration of disparate information system artifacts.

Main Results:

  • Successful transformation of KDM representations into ArchiMate models.
  • Automatic generation of ArchiMate models from a unified knowledge repository.
  • Demonstrated ability to leverage relationships between diverse artifacts for richer EA models.

Conclusions:

  • The proposed KDM-to-ArchiMate transformation facilitates automated EA modeling.
  • This approach enhances the completeness and accuracy of enterprise architecture representations.
  • Automated EA modeling supports more effective digital transformation initiatives.