Checking date: 05/05/2023


Course: 2024/2025

Data Design for sensemaking
(16804)
Bachelor in Data Science and Engineering (Plan: 392 - Estudio: 350)


Coordinating teacher: DIAZ PEREZ, MARIA PALOMA

Department assigned to the subject: Computer Science and Engineering Department

Type: Electives
ECTS Credits: 6.0 ECTS

Course:
Semester:




Requirements (Subjects that are assumed to be known)
Programming Data structures and algorithms Files and Databases
Objectives
1. Data integration models: data store based models and virtual models 2. Data acquisition: Crawlers. Web data integration 3. NoSQL databases in data integration 4. Situation awareness and interpretation in the Big Data era 5. Visual analytics: history, definition and development process. 6. Principles of Human-Machine Interaction: Perception, cognitive aspects, semiotics and creativity 7. Interaction with visual interfaces 8. Temporal and geo-spatial data processing 9. Applications of visual analytics
Skills and learning outcomes
Description of contents: programme
1. Context of Data Governance 2. Data integration models (datawarehouse and virtual models) 3. Heterogeneous Data. Mediated Schema. Schema Matching and Mapping. 4. Obtaining Data. Crawlers. Wrappers. Data Integration on the web. 5. Sensemaking and Situational Awareness in the Big Data Era 6. Visual Analytics: History, Definition and Building Process 7. Principles of Human Computer Interaction: Perception, Cognitive Aspects, Semiotics and Creativity 8. Interaction with Visual Interfaces 9. Geo-spatial and Temporal Data Processing 10. Deep Learning Models 11. Applications of Visual Analytics
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40

Extraordinary call: regulations

The course syllabus may change due academic events or other reasons.