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Unit outline_

OLET2127: Communicating with Wikidata

Intensive July, 2022 [Block mode] - Remote

This OLE unit teaches students to load, use and interpret information using Wikidata. This free, open source repository gathers and stores content in the public domain. It will benefit students in any discipline who are interested in harvesting statistics freely and –as Wikidatauses SPARQL –without the need for query items to be contained in data bases. Published under CC0 1.0 Universal, the data can be reused, copied, modified, and distributed and stored in Wikidata. Wikidata is multilingual so can be used for translations. It can be used with specific datasets or to ask interesting questions like 'What is the capital city of every chocolate manufacturer and how many people live there?'

Unit details and rules

Academic unit English and Writing
Credit points 2
Assumed knowledge


Available to study abroad and exchange students


Teaching staff

Coordinator Jessica Sun,
Lecturer(s) Simon Liu,
Project supervisor(s) Frances Di Lauro,
Type Description Weight Due Length
Online task MCQ 1 - Policies and guidelines
Multiple Choice Quiz
10% Week -01
Due date: 01 Jul 2022 at 23:00

Closing date: 31 Oct 2022
10 questions equivalent to 10 words each
Outcomes assessed: LO1
Online task MCQ 1 - Editing Basics
Multiple Choice Quiz
5% Week -01
Due date: 01 Jul 2022 at 23:00

Closing date: 31 Oct 2022
6 questions equivalent to 5 words each
Outcomes assessed: LO1
Online task MCQ 1 - Citing Sources
Multiple Choice Quiz
5% Week -01
Due date: 31 Oct 2022 at 23:00
5 questions equivalent to 5 words each
Outcomes assessed: LO1
Online task MCQ 2 - Template Languages
Multiple choice quiz
10% Week -02
Due date: 08 Jul 2022 at 23:00

Closing date: 31 Oct 2022
5 questions equivalent to 20 words each
Outcomes assessed: LO2
Assignment Wikidata Statements
Complete 20 "statements" adding 2 of either Items, Properties or Values
20% Week -03
Due date: 15 Jul 2022 at 23:00

Closing date: 31 Oct 2022
20 statements eqiv. to 10 words each
Outcomes assessed: LO2 LO3
Assignment Wikidata-powered template
Create template & transfer knowledge to create Wikidata-powered template
20% Week -04
Due date: 22 Jul 2022 at 23:00

Closing date: 31 Oct 2022
500 word equivalent
Outcomes assessed: LO3 LO5 LO4
Assignment Visualisation creation
Extract information to create visualisations: graphs, data statements, etc.
30% Week -05
Due date: 29 Jul 2022 at 23:00

Closing date: 31 Oct 2022
1000 word equivalent
Outcomes assessed: LO3 LO6

Assessment summary

Students are assessed on their ability to apply the core policies and guidelines of editing Wikipedia. They must demonstrate an understanding of what sorts of data can be centralised in Wikidata. They must extract"actionable knowledge" from data and analytics, synthesise knowledge from information and create visualisations from raw data.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a High distinction indicates work of an exceptional standard, a Distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range


High distinction

85 - 100



75 - 84



65 - 74



50 - 64



0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

5% per day after due date or extension.

Academic integrity

The Current Student website  provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.  

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 Policies and Guidelines Editing basics Citing sources Online class (2 hr) LO1
Week 02 Template language. Types of data that can be centralised in Wikidata. The constituent parts of items harvested. Online class (2 hr) LO2
Week 03 Search queries, working with "statements", "Items", "properties" and "Values". Online class (2 hr) LO2 LO3 LO4
Week 04 Creating Wikidata-powered templates. Online class (2 hr) LO2 LO5
Week 05 Creating Visualisations: graphs, data statements, tables etc. Online class (2 hr) LO5 LO6

Attendance and class requirements

  • Attendance: According to Faculty Board Resolutions, students in the Faculty of Arts and Social Sciences are expected to attend 90% of their classes. If you attend less than 50% of classes, regardless of the reasons, you may be referred to the Examiner’s Board. The Examiner’s Board will decide whether you should pass or fail the unit of study if your attendance falls below this threshold.
  • Lecture recording: Most lectures (in recording-equipped venues) will be recorded and may be made available to students on the LMS. However, you should not rely on lecture recording to substitute your classroom learning experience.
  • Preparation: Students should commit to spending approximately three hours’ preparation time (reading, studying, homework, essays, etc.) for every hour of scheduled instruction.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 2 credit point unit, this equates to roughly 40-50 hours of student effort in total.

Required readings

Readings are available online through links embedded in Canvas material.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. apply the core policies and guidelines of Wikipedia when editing articles
  • LO2. demonstrate an understanding of what sorts of data can be centralised in Wikidata
  • LO3. extract "actionable knowledge" from data and analytics
  • LO4. synthesise knowledge from information
  • LO5. create a Wikidata-powered template - such as an info-box - for Wikipedia and other projects connected to Wikidata
  • LO6. work collaboratively to create visualisations from raw data

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities

This section outlines changes made to this unit following staff and student reviews.

This unit was offered for the first time in the April Intensive, 2021. Students suggested we provide more visuals – video and static – to help with understanding as what we teach in the unit complex so easier for some students to grasp quickly while others need more scaffolding to really digest what is being taught. For the February 2022 intensive session added more visual material to create different ways for students to learn. This was well received. Students in the February 2022 intensive session discussed their desire to extend on the material in the current modules and we look forwards to receiving your feedback on our revised modules during the July 2022 Intensive session.

Additional costs

Open educational resources (OER) are used for this unit so there are no additional costs for students.


The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.