Live Validation:

Live Validation involves real time data cleaning conducted during a mapathon. It aims to give feedback to mappers as soon as possible after they mark a task in the Tasking Manager as mapped.

How Live Validation is done:

1.A validator joins a mapathon (either remote or in-person) accompanying the mapathon trainer. Ideally the validator gets a chance to introduce themselves near the start of the session and explain their role.

2.Once mapping has started, the validator uses Tasking Manager to focus on most recently mapped tasks: Within a project in the Tasking Manager under the ‘Tasks’ section select tasks that are ready for validation and sort by ‘most recent’. Carry out validation using JOSM and give feedback in the Tasking Manager.

3.After main training elements are covered - validator gives verbal feedback while screen sharing during the mapathon. It tends to be more polite not to mention mapper names - participants typically recognize the task they have been working on when you share your screen.

Advantages:

1.Capture data quality issues very early to prevent further occurrences by giving mapper feedback to improve.

2.Live validation helps the trainer to identify recurring issues where the mappers might need more guidance during the mapathon. The trainer can then adapt quickly and focus their training on those issues.

3.Live validation gives the validator the chance to give verbal feedback while also sharing those issues visually on their screen - this is an impactful way to give feedback, particularly compared to the typical method which only involves text-based feedback.

4.A validator gets the chance to demonstrate feedback channels (Tasking Manager notifications) with mappers to make them aware of where they can find feedback after a mapathon - this improves communication between the mappers and validators.

5.It visually demonstrates what validation is - it can sometimes be a difficult concept for new mappers to gain an understanding of. It gives mappers confidence that their mapping is being checked and this can encourage them to continue mapping.

6.When things go very wrong it demonstrates how much work is needed by a validator to clean things up. This may encourage a greater focus on accuracy by participants. Thereby it may improve data quality and make validation easier and faster.

Task selection