In data project 2, students will be introduced to digital data and guided through the process of sourcing data that critically engages with standards of sampling and representation to produce new and useful datasets. Drawing from 'Understanding Data', students will be encouraged to work with theory to determine the value of different data for capturing reality as they engage with data management and analysis.

Week 7-11 (following Working with Secondary Data: Data Project 1 in the timetable).

2x 1-hour lab-based lectures

1x1-hour tutorial

Should avoid Mondays 12:00-14:00 and Thursdays 10:00-12:00

None

In parallel to this course, students must take:

SPS5071 Understanding Data.

Portfolio submission: 2400 words consisting of three equally weighted components.

The aim of the course is to provide students on the MSc Social Science Research Methods with a second opportunity to work through a 'whole project' while introducing students to messy data that will require advanced data management skills. The focus on digital data allows us to critically explore how sampling must be managed in order to make robust claims around representation. Digital data includes information available in digital spaces (such as industry websites, social media) as well as data produced in a digital space (such as remote interviews). This course will explore concepts such as truth and how authenticity can be determined when using data that exists in digital spaces.

Students will continue to be guided through this second project but will have more autonomy as they choose what data to work with, and what themes the data might illuminate. All students will work with numbers and words/narrative and will be encouraged to use digital ethnography strategies and/or use imagery to draw conclusions about the culture/society constructed, including how well it reflects broader cultures/society. Assessments will again, allow students to build data literacy while focusing on skills they are most keen to develop, supported by an interactive moodle and weekly formative 'quizzes'.

By the end of this course students will be able to:

■ Recognise the role played by theory for social constructions of reality in the context of digital data.

■ Demonstrate data management skills for collecting, storing and preparing digital data for data for analysis.

■ Complete an analysis of collected digital data.

■ Assess the value of data management, analysis approaches within their disciplinary context.

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.