Data Management: Communications, Programming and Simulation (250592) – Course 2025/26 PDF
Contents
Data of interest (depth, currents, waves, winds); data vs. metadata (timestamps, geolocation); data acquisition systems (instrumentation, sensors; autonomy, unattended operation); data transmission systems (communication networks); data exploitation (programming, Internet); simulation (modeling, tools).
Dedication
1h Large group + 1h 24m Self StudyDefinition of concepts. Components of a network and basic functions it performs. Information (encoding and data formats). Fundamental parameters to assess its operation: capacity, latency, losses and consumption. Types of networks based on interconnection systems, range and transmission medium (copper, fiber and radio). Switching. Delay (latency) in communication, definition and estimation. Architecture of a computer network. ISO OSI model. Interconnection equipment.
Dedication
4h Large group + 5h 36m Self StudyTCP / IP protocol stack. Bases of operation (addressing and routing). Network layer (IP and ICMP protocols, address types). Transport layer (ports and connections, UDP vs TCP) Application layer (Web and DNS). Internet
Dedication
2h Large group + 1h Laboratory classes + 4h 11m Self StudyGeneral characteristics of the physical and linkage levels (MAC and LLC); field buses (general characteristics, RS-232, RS485); Ethernet (LAN concept, frame format, broadcast, switching). Wired networks: buses and Ethernet
Dedication
1h Large group + 2h Laboratory classes + 4h 11m Self StudyRadio spectrum, regulation; basic concepts (attenuation, coverage) technologies and use cases. GNSS (GPS, GLONASS, Galileo, Beidu); WWANs (2-5G mobile communications networks); WLANs (Wi-Fi); WPANs (Bluetooth, IEEE802.15.4, UWB); LPWANs (Sigfox. LoRaWAN, NB-IoT), GLOVES (satellite) Wireless networks: GNSS and data transmission
Dedication
2h Large group + 3h Laboratory classes + 7h Self StudyFamiliarize with basic programming concepts such as variables and expressions. Variable types and python interpreter errors Variables, expressions and errors
Dedication
1h Large group + 3h Laboratory classes + 5h 36m Self StudyFamiliarize yourself with strings, lists, and python dictionaries. Strings, lists, dictionaries
Dedication
1h Large group + 3h Laboratory classes + 5h 36m Self StudyFamiliarize yourself with the execution flow of a program, conditionals, if / else structures, for, while, and so on. Conditional, execution, iteration
Dedication
1h Large group + 3h Laboratory classes + 5h 36m Self StudyLearn to import basic libraries (math, time, random), learn to generate own functions. Libraries, functions
Dedication
1h Large group + 3h Laboratory classes + 5h 36m Self StudyOpen, read, create files and modify. Different types of files to store data (CSV, JSON, NetCDF). Open and process data in CSV files. Folder generation and automatic organization of files in folders. File operations
Dedication
1h Large group + 3h Laboratory classes + 5h 36m Self StudyLearn that it is a class, that it is an object. Simple class generation. Import classes and use classes from a library. Classes, objects
Dedication
1h Large group + 3h Laboratory classes + 5h 36m Self StudyFamiliarize yourself with the Pandas data processing library and dataframe structures. Simple methods (resample, slice, etc.). Introduction to the Matplotlib library for making graphs with data: lineplot, scatter and correlation. Pandas + Matplotlib
Dedication
1h Large group + 3h Laboratory classes + 5h 36m Self StudyIntroduction to the requests library for working with HTTP. Basic HTTP operations (post, get, patch, delete). Use requests in conjunction with the Telegram API to automate messaging service. HTTP with Requests, Telegram
Dedication
1h Large group + 4h Laboratory classes + 7h Self StudyFinal exercise in which HTTP is used to download data automatically from a data service (eg ERDDAP or CKAN), use Pandas to import data, process it, generate graphs with Matplotlib and send it to via Telegram on mobile phone. Requests + Pandas + Matplotlib + Telegram
Dedication
1h Large group + 4h Laboratory classes + 7h Self StudyAnalyse and review complex networking systems and understand the theoretical underpinning of simulation and gain competency in the use of a simulation package. This module will focus on the transport of multimedia traffic over a variety of communication networks. It will concentrate on the relationships between different types of multimedia traffic, network infrastructures and network protocols in regard to achieving the required Quality-of-Service parameters for multimedia applications. Emphasis will be given to modern high speed communication networks designed to carry high volumes of heterogeneous traffic. LAN/MAN/WAN models with various protocols and different multimedia traffic will be developed and simulated to investigate the behaviour and limitations of such networks. Simulation modelling of communication systems
Dedication
2h Large group + 4h Laboratory classes + 8h 23m Self Study