Grants:Project/mySociety/EveryPolitician/Midpoint

This project is funded by a Project Grant

Report accepted

This midpoint report for a Project Grant approved in FY 2017-18 has been reviewed and accepted by the Wikimedia Foundation.

To read the approved grant submission describing the plan for this project, please visit Grants:Project/mySociety/EveryPolitician.
You may still review or add to the discussion about this report on its talk page.
You are welcome to email projectgrantswikimedia.org at any time if you have questions or concerns about this report.

Welcome to this project's midpoint report! This report shares progress and learning from the grantee's first 3 months.

Summary[edit]

In a few short sentences or bullet points, give the main highlights of what happened with your project so far.

Nine countries now have rich data on politicians.
Key tools: the prompts, reports and PositionStatements bot are in active testing and expected for wider roll-out imminently.

Methods and activities[edit]

How have you setup your project, and what work has been completed so far?

Describe how you've setup your experiment or pilot, sharing your key focuses so far and including links to any background research or past learning that has guided your decisions. List and describe the activities you've undertaken as part of your project to this point.

The first part of the project experimented with ways to highlight issues with the data and testing various approaches.

Reports & Missions[edit]

First up was a proof of concept for 'reports'. Reports are mechanisms to flag with a human data editor that there is something in the data which requires attention, be it a gap, an inconsistency or an error.
Next up: we combined reports into 'missions' which are the public drives to improve data in a given report or set of reports.
- The mission on heads of government data and was very successful in completing each stage of the five-step mission within 24 hours of publication current head of government data.
- The final post in the series outlines what we learned from the experience and highlights some of the successes of the mission approach (including creating some first-time Wikidata editors!).
The next wave of missions focussed on some of the basic underlying data needed in order (e.g. number of seats per house). These missions took considerably longer to complete than the original head of government mission (possibly because the concepts are more abstract).

Prompts[edit]

Prompts allow you to compare data from Wikidata with an external CSV file. While we have developed these as part of a project about political data, we expect these to be much more widely applicable to other types of data.

The first prompts are now running on Wikimedia infrastructure.

See the following examples as proof of concept:

Prompts are currently being tested and documented.

Bots[edit]

A common problem with data about people's political careers is that people often hold the same position more than once. This creates an issue if one wishes to bulk import data via QuickStatements as QuickStatements is designed not to allow duplicate statements.

PositionStatements Bot adds P39 statements to items, using the same input format as QuickStatements. In contrast to the current version of QuickStatements, this bot can add a second version of a statement which already exists.

The bot was created for and successfully used to import data from the recent German legislative elections and will be useful in many countries which do not use term-specific memberships to model their data.

Events[edit]

Our first event! Wikifying Westminster took place on August 19th. Read the writeup.

Arrangements are currently being finalised for events in Wales, Spain, Greece and Bulgaria in November with potential additional events in a number of other countries to coincide with GLOW week.

Midpoint outcomes[edit]

What are the results of your project or any experiments you’ve worked on so far?

Please discuss anything you have created or changed (organized, built, grown, etc) as a result of your project to date.

Key grant metrics:

Number of countries with rich political data in Wikidata: Nine [UK, Scotland, Northern Ireland, Wales, Pakistan, Germany, Estonia, France, Netherlands]
Number of countries in which community actively collecting data: 12 [as above plus Argentina, Austria, Japan]

Finances[edit]

Please take some time to update the table in your project finances page. Check that you’ve listed all approved and actual expenditures as instructed. If there are differences between the planned and actual use of funds, please use the column provided there to explain them.

Then, answer the following question here: Have you spent your funds according to plan so far? Please briefly describe any major changes to budget or expenditures that you anticipate for the second half of your project.

Funds have been spent so far according to plan. The only major change has been to use more senior developers on the project and no junior developers after the beginning of the project.

Some changes are expected in the second half of the grant around event planning e.g. allocating more money for international events and less for UK events. We also intend to create a dedicated role for event support. More details and a budget change request will follow when plans have been finalised.

Learning[edit]

The best thing about trying something new is that you learn from it. We want to follow in your footsteps and learn along with you, and we want to know that you are taking enough risks to learn something really interesting! Please use the below sections to describe what is working and what you plan to change for the second half of your project.

What are the challenges[edit]

What challenges or obstacles have you encountered? What will you do differently going forward? Please list these as short bullet points.

Some parts of volunteer engagement are very resource intensive. In order to easily identify tasks for volunteers, an assessment must be made of the current state of the data in a country. This is very time consuming and requires some advanced SPARQL skills so tends to fall on specific team members.
While the original missions (Heads of Government) were very successful, they were also quite resource intensive. We put a lot of effort into creating a blog series which walked people through in a lot of detail what to do. We have since tried other missions, including the very similar *preceding* head of government mission, without the same level of promotion and they have not been so successful.
Common sources of confusion when using Wikidata can be found here.

What is working well[edit]

What have you found works best so far? To help spread successful strategies so that they can be of use to others in the movement, rather than writing lots of text here, we'd like you to share your finding in the form of a link to a learning pattern.

Your learning pattern link goes here

Next steps and opportunities[edit]

What are the next steps and opportunities you’ll be focusing on for the second half of your project? Please list these as short bullet points. If you're considering applying for a 6-month renewal of this grant at the end of your project, please also mention this here.

Now that key tooling is in place, focus will be applied to gaining momentum and bringing in new editors to the Wikidata to increase the pool of editors.
We will test the prompts and reports in other countries and work to enable others to set them up without our help.
With our tools now tested successfully we will use these to help accelerate the provision of rich data for remaining countries.
We are planning an intense series of events around Global Legislative Open Week (GLOW) to help bring the existing Civic Tech Community into using Wikidata.

A grant renewal will be sought in order to add data for more countries beyond the initial 30-40 countries and to develop tooling to make the data workflow even easier.

Grantee reflection[edit]

We’d love to hear any thoughts you have on how the experience of being an grantee has been so far. What is one thing that surprised you, or that you particularly enjoyed from the past 3 months?

Enjoyed working in the open. Having to write regular reports in the open encourages reflection on the goals of the project.
Have also enjoyed getting to know the community dynamics. We were initially quite surprised by how small the political Wikidata community is (something we hope to contribute to changing).