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---
dataset_info:
features:
- name: task
dtype: string
- name: when it's due (days)
dtype: float64
- name: how long it takes (hours)
dtype: float64
- name: importance (1-10)
dtype: int64
- name: notes
dtype: string
splits:
- name: original
num_bytes: 29709
num_examples: 500
download_size: 15248
dataset_size: 29709
configs:
- config_name: default
data_files:
- split: original
path: data/original-*
license: mit
---
# Dataset Card for Project1
<!-- Provide a quick summary of the dataset. -->
This dataset contains task descriptions, importance, duration, and due date.
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
This dataset contains task descriptions, importance, duration, and due date. It has 500 rows and was created manually in a Google Sheet. It is primarily used to train a multi-task regression model for predicting task characteristics as part of an automated task prioritization system.
- **Curated by:** Sam Der and Smriti Chopra
- **License:** MIT
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
The direct use of this dataset is to train a model for predicting task importance, duration, and expected due date based on text descriptions, as part of an automated task prioritization app.
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
Each instance in the dataset represents a single task with the following attributes:
* `task`: Text description of the task.
* `when it's due (days)`: Deadline in days.
* `how long it takes (hours)`: Estimated duration in hours.
* `importance (1-10)`: Importance of the task on a scale of 1 to 10.
* `notes`: Additional notes about the task.
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
The dataset was created to provide labeled examples of tasks with associated characteristics (importance, duration, due date) to train a model to predict these characteristics from a task's text description. This is intended to support an automated task prioritization app.
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
The data was collected from a Google Sheet where tasks and their attributes were manually entered.
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
The importance, duration, and horizon of the tasks were estimated from previous experience or given to the data creators.
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
Created by Sam Der and Smriti Chopra
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
This dataset was created manually, so there may be biases in deciding task importance or expected duration due to personal preferences and experiences. |