Universität Wien

230211 SE Energy and Big Data (2018S)

Transition and the Informational Turn in Energy

5.00 ECTS (2.00 SWS), SPL 23 - Soziologie
Continuous assessment of course work

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Exkursion 16.03.2018, 13:00 - 17:00 Uhr (ASCR Demo Center)

  • Monday 05.03. 14:00 - 16:00 Seminarraum STS, NIG Universitätsstraße 7/Stg. II/6. Stock, 1010 Wien
  • Wednesday 07.03. 11:30 - 13:30 Seminarraum STS, NIG Universitätsstraße 7/Stg. II/6. Stock, 1010 Wien
  • Monday 12.03. 10:00 - 12:00 Seminarraum STS, NIG Universitätsstraße 7/Stg. II/6. Stock, 1010 Wien
  • Wednesday 14.03. 11:30 - 13:30 Seminarraum STS, NIG Universitätsstraße 7/Stg. II/6. Stock, 1010 Wien
  • Thursday 15.03. 09:00 - 11:00 Seminarraum STS, NIG Universitätsstraße 7/Stg. II/6. Stock, 1010 Wien
  • Wednesday 21.03. 11:30 - 13:30 Seminarraum STS, NIG Universitätsstraße 7/Stg. II/6. Stock, 1010 Wien
  • Wednesday 21.03. 13:30 - 15:30 STS Bibliothek, NIG Universitätsstraße 7/Stg. II/6. Stock, 1010 Wien
  • Thursday 22.03. 13:45 - 15:45 Seminarraum STS, NIG Universitätsstraße 7/Stg. II/6. Stock, 1010 Wien

Information

Aims, contents and method of the course

This course will equip students to reflect and act on issues around big data, and will draw on conceptual and empirical work in the area of energy and sustainability. Big data is a phenomenon that affects all kinds of sectors, from energy to banking to sports to neuroscience, and most of the theories and concepts discussed in the course will be of use in understanding Big Data (and other data-intensive innovations) in other domains as well. It has a history going back several decades and has been shaped by tools and institutions, with the result that ‘big data’ has its own biases and tendencies. It is therefore crucial to analyse how big data approaches are a specific way of creating knowledge about energy and how this knowledge is used. In particular, we will trace how new forms of measurement yield data, that are then combined with particular kinds of statistics and database logics and how an informational turn is affecting the technologies and infrastructures in the area of energy.
The course will consist of three kinds of activities: (1) lecture sessions (lecture plus class discussion), (2) student presentations on energy transition and (3) an excursion.

At the end of the course, students will be able to
1. understand a set of concepts related to the use of data to produce knowledge about energy and sustainability
2. understand the intersection of informationalization and transition theory.
3. apply these concepts to identify and address key issues arising from the role of (big) data in a wide range of contemporary social dynamics, in the area of energy and beyond.
4. reflect on the relations between data, knowledge and society in essay form.
5. analyse an instance of discourse on energy transition and present their findings
6. find and use scientific sources (from literature and elsewhere) for their essay.

Assessment and permitted materials

To pass the seminar, students are expected to complete the following tasks:
an essay on a topic covered in the course (choice of 5 topics) (45 points)
a group presentation (groups of 3, one grade for group) on an instance of an ïmpasse in the energy transition, following the scheme set out in After Oil (30 points)
class participation (25 points)

Essay on a topic covered in the course (choice of 5 topics) (45 points)

Your assignment will be marked according to the following criteria:
Content (25 points)
o Originality of argument
o Relevance of case or empirical material
o Focus, no loose ends or asides
o Use of sources from the course
Formal Requirements (10 points)
o topic from course properly selected
o presentation, length, use of graphics, illustrations, tables
o language, spelling and grammar
o sentence and paragraph structure
Development, Structure and Coherence (10 points)
o Position clearly stated
o Position coherently argued
o Evidence and empirical material well presented
o Link between concepts and empirical material is explicit

Written feedback will be provided by the lecturer.

Group Project (30 points)

Your assignment will be marked according to the following criteria:
Formal Requirement (10 points)
o Relevant case found
o Group is well informed about topic
o Empirical material from case is well presented
o Analytic categories from scheme in After Oil are used
Content and Reflection on case (20 points)
o Insights derived from use of scheme found in After Oil
o Ability to reflect on position presented in case and to situate discourse
o Reflection on scheme, its usefulness in relation to case and possible shortcomings

Oral feedback will be provided by the lecturer and by fellow students.

Class participation (25 points)

required readings have been read
student come prepared to discuss readings in class
student contribute with insightful comments and interesting connections, and help foster a high level of energy and enthusiasm in the classroom learning environment
student listen to others and engage meaningfully in class discussions and interactions with peers and lecturer

Minimum requirements and assessment criteria

Grading Scheme
The grading scheme is based on a total of 100 points. These points will be awarded in relation to students’ performance in meeting the course learning aims in the different obligatory tasks.
The maximum number of points to be acquired for each task is:

Essay: 45 points, assessed individually, feedback by lecturer
Group Presentation: 30 points, assessed as group work,
feedback by lecturer
In-class Participation: 25 points, assessed individually, indication good/sufficient/insufficient by lecturer at halfway mark

Minimum requirements
A minimum of 50 points is necessary to successfully complete the course. Failure to meet the attendance regulations, to deliver course assignments on time or to adhere to standards of academic work may result in a deduction of points.

Grades
100-87 points Excellent (1)
86-75 points Good (2)
74-63 points Satisfactory (3)
62-50 points Sufficient (4)
49-0 points Unsatisfactory (5) (fail)

Attendance
Presence and participation is compulsory. Absences of four hours at maximum are tolerated, provided that the lecturer is informed about the absence. Absences of up to eight hours in total may be compensated by either a deduction of grading points or/and extra work agreed with the lecturer. Whether compensation is possible is decided by the lecturer.
Absences of more than eight hours in total cannot be compensated. In this case, or if the lecturer does not allow a student to compensate absences of more than four hours, the course cannot be completed and is graded as a ‘fail’ (5), unless there is a major and unpredictable reason for not being able to fulfil the attendance requirements on the student’s side (e.g. a longer illness). In such a case, the student may be de-registered from the course without grading. It is the student’s responsibility to communicate this in a timely manner, and to provide relevant evidence to their claims if necessary. Whether this exception applies is decided by the lecturer.

Important Grading Information
If not explicitly noted otherwise, all requirements mentioned in the grading scheme and the attendance regulations must be met. If a required task is not fulfilled, e.g. a required assignment is not handed in or if the student does not meet the attendance requirements, this will be considered as a discontinuation of the course. In that case, the course will be graded as ‘fail’ (5), unless there is a major and unpredictable reason for not being able to fulfill the task on the student's side (e.g. a longer illness). In such a case, the student may be de-registered from the course without grading. It is the student’s responsibility to communicate this in a timely manner, and to provide relevant evidence to their claims if necessary. Whether this exception applies is decided by the lecturer.
If any requirement of the course has been fulfilled by fraudulent means, be it for example by cheating at an exam, plagiarizing parts of a written assignment or by faking signatures on an attendance sheet, the student's participation in the course will be discontinued, the entire course will be graded as ‘not assessed’ and will be entered into the electronic exam record as ‘fraudulently obtained’. Self-plagiarism, particularly re-using own work handed in for other courses, will be treated likewise.

Examination topics

Reading list


Association in the course directory

Last modified: Sa 24.10.2020 00:25