---
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.