DSC8015 : Data Acquisition and Cloud Storage in Sport Science
- Offered for Year: 2025/26
- Module Leader(s): Dr Iain Spears
- Lecturer: Dr Daniel Henderson, Dr Silvia Del Din
- Owning School: Biomedical, Nutritional and Sports Scien
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 2 Credit Value: | 20 |
| ECTS Credits: | 10.0 |
| European Credit Transfer System | |
Aims
To provide advanced knowledge and practical experience in collecting, processing, and storing high-resolution sport data using modern hardware and scalable cloud infrastructure. Students will critically evaluate data acquisition systems, build cloud-based pipelines, and consider data governance and ethical considerations in sport science contexts.
Outline Of Syllabus
The syllabus will cover topics from:
• Advanced sensor technology: GPS, IMUs, force plates, heart rate systems, smart wearables
• Data integrity and preprocessing: calibration, drift, signal noise, data fusion
• Data formats used in sports: CSV, JSON, FIT, XML, C3D, CWA proprietary formats
• Historical data integration: Transfermarkt, FBref, Opta datasets for recruitment and performance analysis
• Cloud infrastructure for sport: AWS S3, Firebase, GCP Buckets, serverless functions
• APIs and live data pipelines: REST APIs, WebSockets, real-time uploads
• Edge computing and mobile devices in sport data acquisition
• Security, privacy, and ethical frameworks: GDPR, data consent, secure storage
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 9 | 0:30 | 4:30 | Formative Quizzes |
| Guided Independent Study | Assessment preparation and completion | 1 | 32:00 | 32:00 | Lab portfolio development and preparation and completion |
| Guided Independent Study | Assessment preparation and completion | 1 | 1:00 | 1:00 | Oral presentation (30 mins + 10 mins for questions) |
| Scheduled Learning And Teaching Activities | Lecture | 9 | 2:00 | 18:00 | Lectures |
| Guided Independent Study | Assessment preparation and completion | 1 | 40:00 | 40:00 | Technical report preparation and completion. |
| Scheduled Learning And Teaching Activities | Practical | 8 | 3:00 | 24:00 | Practical sessions Guest/Specialist lectures |
| Guided Independent Study | Directed research and reading | 34 | 1:00 | 34:00 | Background reading |
| Scheduled Learning And Teaching Activities | Drop-in/surgery | 3 | 2:00 | 6:00 | Coursework support |
| Guided Independent Study | Independent study | 1 | 40:30 | 40:30 | Independent study on course content. |
| Total | 200:00 |
Teaching Rationale And Relationship
Lectures explain the underpinning principles for the module and technologies that support data collection in sports environments. Lectures are complemented by supervised practical sessions to guide the application of these principles using suitable technical tools. The practical work builds up experience working with a computational toolset that is used to complete a substantive project working with data from a real-world context.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Oral Presentation | 2 | M | 50 | Design and implement a full data acquisition and cloud storage pipeline for a specific sport use case. The students will present their work via a 30min oral presentation with 10 mins for questions |
| Portfolio | 2 | M | 50 | Lab portfolio-Series of technical tasks involving data acquisition, cleaning and upload This will be presented as one report in in which the solutions to all of the 8 assigned different technical tasks (1 per session) will be presented as a written report |
Zero Weighted Pass/Fail Assessments
| Description | When Set | Comment |
|---|---|---|
| Digital Examination | M | Set of 9 quizzes on lecture content each lasting 30mins |
Assessment Rationale And Relationship
The module includes two summative assessments:
• Technical ReportOral Presentation– This assessment evaluates students’ ability to define a data collection problem, decide on the most effective data collection method, and design an appropriate online repository for such data. It focuses on understanding of the capturing technologies. The students will present their work via a 30 min oral presentation with 10 mins for questions
• Lab portfolio– In this assessment, students will report on the multiple lab sessions using real-world data collected in the lab session. They will present their finding through a written report. It assesses their ability to apply data collection techniques across a range of sensors.
In addition to the summative assessments, the module includes formative assessment in the form of automatically graded quizzes. These can be completed at the students’ own pace and are designed to help them check their understanding of lecture content and key concepts. This provides immediate feedback and supports their learning throughout the module.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- DSC8015's Timetable