Wikidata:Wikidata curricula


A Wikidata curriculum is a plan for study to assist anyone in meeting whatever learning goals they have that involves the use of Wikidata.
Curricula formats
editData literacy for everyone
editInstructors can use Wikidata as a tool to teach data literacy to anyone.
Learning objectives:
- Be able to form and express personal opinions on data and society
- Be able to join casual conversations of data science
- Using Wikidata examples, learn some applications of sharing and querying data
- Understand how Wikidata is different, including being open, nonprofit, in the Commons, federated, etc.
Consider skipping practical instruction on these topics:
- Basics of Wikimedia projects
- Editing Wikidata
- Performing Wikidata queries
Introduction to data science
editInstructors can use Wikidata as a tool to teach data science to anyone.
Learning objectives:
- Be able to form and express personal opinions on data science
- Be able to read popular publications on data science including the common jargon terms
- Using Wikidata examples, learn some applications of sharing and querying data
- Present Wikidata engagement as a path to learn and experience data science at any level
Consider skipping practical instruction on these topics:
- Basics of Wikimedia projects
- Editing Wikidata
- Performing Wikidata queries
Wikidata editing for everyone
editInstructors can use Wikidata as a tool to teach structured data and database editing to anyone.
Learning objectives:
- Using Wikidata examples, learn some applications of sharing and querying data
- Present Wikidata engagement as a path to learn and experience data science at any level
- Edit Wikidata items manually
Consider skipping practical instruction on these topics:
- Performing Wikidata queries
Wikidata queries for everyone
editInstructors can use Wikidata as a tool to teach structured data and database querying to anyone.
Learning objectives:
- Using Wikidata examples, learn some applications of sharing and querying data
- Present Wikidata engagement as a path to learn and experience data science at any level
- Perform Wikidata queries
Consider skipping practical instruction on these topics:
- Performing Wikidata edits
Wikidata for the Wikimedia community
editPersons who identify as Wikimedia community members come to Wikidata with a culture of expectations and particular interests in Wikidata. This demographic will want to connect their Wikidata engagement with their other Wikimedia interests.
Learning objectives:
- Learn some applications of sharing and querying data which Wikimedia editors apply to Wikimedia projects
- Present Wikidata engagement as a path to learn and experience data science at any level
- Perform Wikidata queries to get Wikimedia information
- Perform Wikidata edits to develop Wikimedia content
- Convey the possibility of automated integration of Wikidata with Wikimedia projects and external information repositories
Consider skipping practical instruction on these topics:
- Applications of Wikidata outside the context of Wikimedia projects
Wikidata queries for researchers
editResearchers come to Wikidata seeking data to help them with their off-wiki research interests. The initial interest of this group is in exporting data from Wikidata without otherwise interacting. This is a valuable demographic to target with outreach for partnership, yet it is also a group that has intent to take and not give back. Instructors without an agenda can meet their needs directly. An instructor with an agenda can encourage this demographic to check out Wikidata in their field of expertise and try to share data back.
Learning objectives:
- Perform Wikidata queries to get Wikimedia information
- Learn how to use Scholia
- Be able to have academic conversations about the nature of Wikidata
- Using Wikidata examples, learn some applications of sharing and querying data
- Understand the community ethics of Wikidata regarding sharing, licensing, data federation, and the commons
Importing datasets into Wikidata
editAnyone who talks about ingesting datasets into Wikidata has some background context of Wikidata and sharing datasets. For this demographic the objective is to make sure that they comply with community norms and avoid creating a huge mess.
Learning activities:
- Using Wikidata examples, review some case studies of how various projects have ingested Wikidata
- Present metrics evaluation plans by means of which an organization can measure the impact of its engagement in Wikidata
- Practice having conversations using Wikidata's internal communication interface
- Showcase all the channels through which a person can seek assistance and ask questions
- Demonstrate how to do a small example data donation then seek community feedback and oversight
- Point to the processes in place for staging a dataset for Wikidata ingestion
Wikidata for librarians
editModule 1: What is Wikidata?
editActivities:
- Introduce Wikidata interface
- Play one of the Wikidata games
- Describe relationship to other Wikimedia projects
Learning outcomes:
- Feel comfortable describing Wikidata to colleagues
- Understand how Wikidata relates to other Wikimedia projects
- Understand why linked open data is important in my work as a cataloging or teaching librarian
Module 2: Underlying concepts of Wikidata
editActivities:
- Describe RDF/triples
- Describe semantic web/structured data
- Explain how Wikidata compares with other data sets
- Walk through Wikidata one pager
Learning outcomes:
- Identify components of a Wikidata item page
- Know where to find information on navigating Wikidata
- Define what's different about open data and why it's important
- Understand what a triple is, and relate structure of a Wikidata statement to traditional metadata field structure
Module 3: Introduction to editing
editActivities:
- Find and edit an existing item
- Talk about norms in Wikidata (community, policies, etc.)
- Find lists of properties/relationships
- Use some curation tools (e.g. Author Disambiguator)
Module 4: Create new items
editActivities:
- Add statements
- Add references
- Add stable identifiers
Module 5: Introduction to querying
editActivities:
- Wikidata Query Service (SPARQL)
- Try examples (research published that week?)
- Explore Scholia
Module 6: Advanced
editActivities:
- Bulk uploads/harvests (lead to OpenRefine modules)
- Bulk edits
- Bulk creation/harvesting
Topics to consider
editFirst steps in data literacy
edit- open data (Q309901)
- structured data (Q26813700)
- machine learning (Q2539)
- data analysis (Q1988917)
- cloud computing (Q483639)
- metadata (Q180160)
- database (Q8513)
- data visualization (Q6504956)
- citizen science (Q1093434)
- data ethics (Q45933174)
- data sharing (Q5227350)
- scientific data (Q20081319)
- big data (Q858810)
- data literacy (Q17067559)
- data wrangling (Q5227374)
Popular data science
edit- data cleansing (Q1172378)
- data mining (Q172491)
- data management (Q1149776)
- natural language processing (Q30642)
- question answering (Q1074173)
- data format (Q494823)
- controlled vocabulary (Q1469824)
- application programming interface (Q165194)
- accuracy and precision (Q272035)
- query language (Q845739)
- data model (Q1172480)
- provenance (Q1773840)
For specialized use
editExisting curricula
editList of curricula
edit- Wikidata:MOOC has a curricula in French at Wikidata:MOOC/Course_outline. Seems to be relatively dormant since 2020.
- On October 2018 a new academic elective course which feature Wikidata opened at Tel Aviv University. The course is called "From Web 2.0 to Web 3.0, from Wikipedia to Wikidata" and was developed and is led by Educator and Wikimedian Shani Evenstein.
Curricula parts
editIndividuals and organizations typically make educational resources piece-wise to teach one activity. These resources are useful but without a broader learning plan, an individual may have challenges confirming their learning goals or identifying the order in which to learn skills.
When designing a curricula, an instructor may collect various educational resources and recommend that students use them in an order to accomplish their goal.