Difference between revisions of "Progress Tracking"

From Organic Data Science Framework
Jump to: navigation, search
(Added PropertyValue: Participant = YolandaGil)
(Deleted PropertyValue: Participant = YolandaGil)
Line 20: Line 20:
 
<!-- Do NOT Edit below this Line -->
 
<!-- Do NOT Edit below this Line -->
 
{{#set:
 
{{#set:
Participant=YolandaGil|
 
 
Participant=Felix}}
 
Participant=Felix}}

Revision as of 09:26, 2 June 2014


Mockup 3 Progress Tracking.png
Progress Tracking Mockup

High, Medium, and Low-Level Tasks

Tracking the progress of hierarchical nested tasks need to address different problems on different task abstraction levels. A task on the root level can take a long time and has probably a high abstraction. E.g. “The Age of Water” Task in this wiki. Tasks on the leaf level can be characterized by low abstraction and shorter duration. Therefor we decide to introduce three different task types “Low-Level”, “Medium-Level” and “High-Level” tasks. The type prefix describes the level of abstraction that means a “Low-Level” task has a low abstraction. Every type has a different color, on “Low-Level” task the degree of abstraction is low and the progress estimation is exact this is expressed with the dark green color. Light green represents the “High-Level” tasks with lower progress estimation accuracy. “Low-Level” tasks are tracked in percentage directly by asking the task owner. “Medium-Level” tasks are intermediate tasks in between high and low level tasks.

Automatic Estimation of Progress

The progress is tracked by aggregating the progress of all related subtasks.

The progress tracking is based on the structured properties attributes described in the task representation and timeline tracking. To ensure a preferably accurate measurement which represents the current state of a “High-Level” task, the progress calculation is based on start and target date. Our assumption is that after half of the task duration, the expected task progress would be 50 percent. In case we would use the aggregation method as described for the medium level tasks the estimation would be far inaccurate. The aggregation concept is optimal when most of the subtasks are known at the tasks start date. In reality especially high level tasks will emerge during the time. E.g. one subtask is known at the start of a high level task and more subtasks are added during the time. In an early task state the progress would be much too high due to the fact that that the later added subtasks not considered by the progress calculation via aggregation. High level tasks are probably uses most on root level tasks but depending on the degree of abstraction within the tasks hierarchy high level task can be used in lower hierarchy levels.

I think the above needs to be explained better -- Yolanda


Yandex.Metrica