DS822: Thick Data Analytics

Entry requirements

This course cannot be taken by students enrolled in the Bachelor - or Master program in Computer Science

Academic preconditions

Ingen

Course introduction

The purpose of this seminar is to provide the students with an anthropologically based understanding of technological development, focusing on the relationship between innovation, social change and consumption practices and reflecting on the managerial

consequences of these relationships. The course covers issues that include:

ethnographic practices in innovation, design and corporate culture, ways that people and technologies co-construct everyday conditions and futures, the role of technologies in mediating relationships between citizens, corporations and the state; and the Internet of Things as a new realm of social relationality.

Overall the course equips the student with knowledge and competences in order to manage processes involving

technology and customer – experience interplay and to use market ethnographic knowledge for designing and evaluating

human-technology interaction. These competences are applicable in a large range of service and welfare contexts.

In the face of globalization and its challenge to community-based studies of cultural processes, anthropology has become increasingly interested in innovation and technologies. In order to tackle the notion of cultural complexities and organizational dynamics, students are presented to the use of ethnography and anthropology in the study and design of devices, products, services and infrastructure.

The course will deal with technologies in the following ways;

Technologies used on an individual level social media, algorithm and personal analytics (when people measure, track and monitor themselves), analog versus digital medias & materialities.
Technical systems such as communications networks, energy infrastructure, roads, and water and waste systems, that have become sites for conducting ethnographies of contemporary development, stakeholder networks, projects and relationships.
Robots such as drones and welfare technologies.

This course is an elective for the profile "Economics and Business Administration".

Generel competences:

Knowledge about the needs and opportunities of the specialization when working with and processing data
Competences in selecting, applying, and combining the right programming, statistics, and machine learning tools and methods to work with data relevant for the specialization
Skills in managing complex work and development situations in the areas of data processing and analysis as well as starting up and executing analyses

Expected learning outcome

The learning objective of the course is that the student demonstrates the ability to:

Demonstrate that they possess the required knowledge by being able to:

Explain the contribution of anthropology to the analysis of technology-culture-business relationships
Explain the cultural principles and methods used in the development of a specific technology.

Demonstrate that they have skills to analyze and assess a specific technological content:

Analyse the theoretical relationships and interconnectivity between technologies, culture and human practices
Investigate and analyze the drivers and barriers surrounding technological innovation and development, in particular their cultural dimensions
Be able to detect cultural patterns behind data analytics and apply this insight for strategic decision making
Undertake analysis of the ethical issues at stake
Critically reflect on technological innovation in a societal framework
Based on the analysis of given technology to bring input to the developers to decision.
Reflect on how models and theories of the technologies can be involved to support decisions in a welfare context.

Content

The following main topics are contained in the course:

Theories of organizational culture and technology
Theories and applied cases of innovation and design anthropology Information
Technologies and Social Life
Technological Infrastructure and culture

Literature

See itslearning for syllabus lists and additional literature references.

For example:

Hyysalo, Sampsa Torben Elgaard Jensen and Nelly Oudshoorn (2016) The New Production of Users Changing innovation collectives and Involvement strategies. New York: Routledge.
Verbeek. Paul (2011) Moralising technology, Understanding and Designing the Morality of things. London: University of Chicago press.
Ruckenstein, Minna 2014. Visualized and Interacted Life: Personal Analytics and Engagements with Data Doubles. Societies 4(1):68–84.
Taina Bucher (2017) The algorithmic imaginary: exploring the ordinary affects of Facebook algorithms, Information, Communication & Society, 20:1, 30-44.
Von Schnitzler, Antina. 2013. Travelling Technologies. Infrastructure, Ethical Regimes, and the Materiality of Politics in South Africa. Cultural Anthropology 28 (4): 670-693.
Larkin, Brian. Signal and noise: media, infrastructure, and urban culture in Nigeria. Duke University Press, 2008.
Kristin Asdal, Brita Brenna and Ingunn Moser (eds.) (2007) & Technoscience. The Politics of Interventions. Oslo: Oslo University Press.

Examination regulations

Exam element a)

Timing

Autumn

Tests

Home assignment

EKA

N340077102

Assessment

Second examiner: Internal

Grading

7-point grading scale

Identification

Full name and SDU username

Language

Normally, the same as teaching language

Examination aids

To be announced during the course

ECTS value

Additional information

The student’s achievement of the learning goals will be assessed through a written report that will be prepared based on the student’s independent research and incorporate data collected during the semester. Such materials may be appended to the 10 page body of the report. The report should conform to standard research paper formats.

Supplemental information on reexam: An improved research paper. A short supervision is granted in the form of an explanation of major weaknesses in the original paper.

Indicative number of lessons

32 hours per semester

Teaching Method

The teaching method is based on three phase model.

Intro phase: 4 hours
Skills training phase: 28 hours. The seminar iscarried out as roundtable discussions between students and teacher. If more than 20 students enrolled in the course, the format of the teaching will be changed to lectures. Students are expected to prepare an oral presentation of 1) readings that relate to the themes in the course and their own individual research project 2) their own projects

Teacher responsible

Name	E-mail	Department
Christian Møller Dahl	cmd@sam.sdu.dk	Econometrics and Data Science
Dorthe Brogård Kristensen	dbk@sam.sdu.dk	Consumption, Culture and Commerce (CCC)
Julie Emontspool	juli@sam.sdu.dk	Consumption, Culture and Commerce (CCC)
Oliver Baumann	oliv@sam.sdu.dk	Strategic Organization Design (SOD)

Timetable

Odense

Show full time table

Administrative Unit

Institut for Matematik og Datalogi (datalogi)

Team at Educational Law & Registration

NAT

Offered in

Odense

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