ICM – Computer Science Major – Course unit on Interoperability of Data and Semantics and M1 Cyber Physical and Social Systems – Course unit on System Modeling
Institut Henri Fayol - MINES Saint-Étienne
Syllabus
This lecture aims at ensuring you are familiar with data and information, at the core of every information technology (IT). The course focuses on four main topics:
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Encoding base data types. Numbers, characters, date and time, languages, quantities and units of measures, colors, etc.
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Data formats. Delimiter separated values, XML, JSON, YAML, data formats for configuration files, markup, multimedia, or 3D models.
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Data schemas and semantics. Covering XML and JSON schema, controlled vocabularies and ontologies, the Resource Description Framework, rich structured data.
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The value of data. Everything related to data storage and processing, the data value chain, open data, data interoperability.
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The European strategy for data. The regulatory framework Europe has put in place to boost the data economy, and a focus on data spaces.
You will practice with tutorials, and gain experience through practical work.
Organization
See slides.
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Introduction to the course
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Lecture Part 1
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Tutorial 1
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Lecture Part 1, 2
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Tutorial 2
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Kick-off for practical work 1
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Lecture Part 2, 3
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Exam 1
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Lecture Part 3, 4
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Tutorial 3
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Kick-off for the practical work 2
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Lecture Part 4, 5
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Exam 2
Outline of the lectures
Part 1. Encoding base data types
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Part 1.1. Reminders: binary and hexadecimal strings
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Part 1.2. Endianness
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Example: MCF88 LoRa temperature, humidity and pressure sensor payload
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Part 1.3. Computer number formats
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Part 1.4. Character encoding
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Part 1.5. Base32 and Base64 encoding
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Part 1.6. Date and time
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Part 1.7. XML Schema Datatypes
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Part 1.8. Codes: countries, languages, …
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Part 1.9. Quantities and units of measure
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Part 1.10. Colors
Part 2. Data Formats
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Part 2.1 Generalities
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Part 2.2. Delimiter-separated values
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Part 2.3. Extensible Markup Language (XML)
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Part 2.4. JavaScript Object Notation (JSON)
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Part 2.5. Configuration file formats
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Part 2.6. YAML Ain’t Markup Language (YAML)
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Part 2.7. Lightweight markup languages
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Part 2.8. Compressed formats
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Part 2.9 Multimedia formats
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Part 2.10 3D models
Part 3. Data Schemas and Semantics
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Part 3.1. Data schemas
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Part 3.1.1. XML Schema
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Part 3.1.2. JSON Schema
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Part 3.2. Semantics
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Part 3.2.1. Heterogeneities and data conflicts
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Part 3.2.2. Controlled vocabularies and ontologies
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Part 3.2.3. Resource Description Framework
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Part 3.2.4. RDFa: Rich structured data markup for web documents
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Part 3.2.5. JSON-LD: JSON for Linking Data
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Part 4. The Value of Data
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Part 4.1. Value as one of the V’s of Big Data
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Part 4.2. Data, Information, Knowledge, Metadata, …
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Part 4.3. Interoperability unlocks the value of data
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Part 4.4. Open data generates economic and societal value
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Part 4.5. Machine-actionability of data increases its value
Part 5. The European Data Strategy
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Part 5.1. The European legislation on open data
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Part 5.2. The General Data Protection Regulation (GDPR)
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Part 5.3. The Data Governance Act (DGA)
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Part 5.4. The Data Act
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Part 5.5. Data Spaces
Tutorials
Tutorials contain exercises found in the exams of the past years.
Practical work
You will gain experience through practical work, where you need to demonstrate your know-how based on screenshots, documents, and programs.
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Practical work 1, deadline 14/11
submit your work for Courses 1-2 as LASTNAME.zip to https://ecampus.emse.fr/mod/assign/view.php?id=34360 (expiration date/time: 2025-11-15 01:00 )
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Practical work 2, deadline 14/01
submit your work for Courses 1-2 as LASTNAME.zip to https://ecampus.emse.fr/mod/assign/view.php?id=34361 (expiration date/time: 2026-01-15 01:00 )
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Exams
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Exam 1: 6/11 (2h30) - solutions
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Exam 2: 9/12 (1h30)
The exams test your knowledge with respect to the content of the lectures, and contains exercises similar to those prepared during the tutorials.
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The exam will contain necessary appendices.
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You can bring a A4 sheet of paper, hand-written by you, both sides.
Grading policy
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50 % practical work
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50 % written exams