Project of Data Visualization (COM-480)

Student's name	SCIPER
Adriana Orellana	376792
Angel Zenteno	376890
Jianan Xu	370489

Milestone 1 • Milestone 2 • Milestone 3

Website

Milestone 1 (29th March, 5pm)

10% of the final grade

This is a preliminary milestone to let you set up goals for your final project and assess the feasibility of your ideas. Please, fill the following sections about your project.

(max. 2000 characters per section)

Dataset

Find a dataset (or multiple) that you will explore. Assess the quality of the data it contains and how much preprocessing / data-cleaning it will require before tackling visualization. We recommend using a standard dataset as this course is not about scraping nor data processing.

Hint: some good pointers for finding quality publicly available datasets (Google dataset search, Kaggle, OpenSwissData, SNAP and FiveThirtyEight), you could use also the DataSets proposed by the ENAC (see the Announcements section on Zulip).

Our dataset was obtained from the IUCN Red List, focusing on animals classified under various conservation statuses: Extinct (EX), Critically Endangered (CR), Endangered (EN), Vulnerable (VU), and Near Threatened (NT). The original dataset, provided in CSV format, contained 25,183 entries, each detailing 20 attributes. To augment our data, we developed a script to scrap additional information through the IUCN Red List API, aiming for a detailed representation of conservation-challenged animals. The resulting dataset was organized into a directory with 1,799 subfolders, each representing an individual animal and containing six JSON files with additional attributes.

Initially, we identified that every animal has a unique ID. However, the initial CSV dataset faced two significant challenges: (1) the duplication of some animal entries and (2) the presence of numerous empty fields, a consequence of the limited information available on these conservation-challenged animals To transform our dataset into a valuable resource for visualization, we preprocessed and cleaned it. First, we merged the CSV and scraped data, then carefully eliminated duplicate animal entries and attributes with null values to ensure data integrity.

Through this process, we transformed our dataset into JSON format, incorporating 1,799 animals with 39 attributes. Below is an example illustrating how our dataset is formatted:

The final format ensures our dataset is ready for analysis and fits our project needs, as it organizes the data in a structured manner that is easily accessible for further interpretation.

You can access the final dataset at ./data_viz_animals/animals.json, while the raw data extracted from IUCN Red List API can be found within ./data_viz_animals/raw_data/ and the preprocessed csv originally provided by IUCN Red List is located at ./data_viz_animals/species.csv

Problematic

Frame the general topic of your visualization and the main axis that you want to develop.

• What am I trying to show with my visualization?
• Think of an overview for the project, your motivation, and the target audience.

General Topic and Main Axis Development

Every year, approximately between 1,000 and 30,000 species face extinction [1], raising a critical question: Will humans become the only inhabitants of Earth after several centuries? This pressing concern underscores the urgency for immediate conservation actions. The foundation of effective animal protection lies in enhancing public awareness and consensus, with data serving as a tool for this purpose. Visualization acts as the conduit, bridging the gap between data and public perception.

Overview, Motivation, and Target Audience

Our project aims to create a dynamic and informative webpage targeted primarily at students, fostering increased awareness about conservation-challenged animals. This initiative is driven by the belief that education and engagement can spark collective action towards animal conservation.

Visualization Content and Features

For the visual part of our project, we intend to incorporate several features designed to raise awareness about endangered animals:

1. 3D Navigable Globe: A visualization showcasing the global distribution of conservation-challenged animals, offering users a comprehensive understanding of their spread and hotspots.
2. Animals Profiles: Detailed profiles for each animal, including information on appearance, population, habitats, threats, and conservation measures.
3. Educational Content: Curated educational videos that highlight the importance of conservation efforts and inspire viewers to contribute to these causes.
4. Interactive Feature: We plan to integrate the following interactive element to further engage users:
   • EcoSurvival Game: A game where participants match conservation-challenged animals with their ideal ecological requirements, encompassing food, habitats, and more. High scorers will be awarded a certificate of achievement, fostering learning through engaging gameplay.

Exploratory Data Analysis

Pre-processing of the data set you chose

• Show some basic statistics and get insights about the data

Besides dataset pre-processing and cleaning mentioned in the Dataset section, we conducted exploratory data analysis. The details of pre-processing, cleaning, and EDA can be seen in EDA.ipynb. We present basic statistics as follows:

1. The number of animals in each conservation status, where categories represent:

• NT: Near Threatened
• VU: Vulnerable
• EN: Endangered
• CR: Critically Endangered
• EW: Extinct in the Wild
• EX: Extinct

This table helps us understand how urgently we need to work to conserve different species:

	category	counts
0	EN	579
1	VU	502
2	NT	410
3	CR	298
4	EX	9

2. The number of animals per habitat, where an animal can have more than one habitat:

	habitat	counts
0	Wetlands (inland) - Permanent Rivers/Streams/C...	1033
1	Forest - Subtropical/Tropical Moist Lowland	389
2	Wetlands (inland) - Permanent Freshwater Lakes...	254
3	Forest - Subtropical/Tropical Moist Montane	193
4	Marine Deep Benthic - Deep Sea Vents (Rifts/Se...	159
5	Wetlands (inland) - Permanent Freshwater Marsh...	131
6	Wetlands (inland) - Bogs, Marshes, Swamps, Fen...	109
7	Wetlands (inland) - Freshwater Springs and Oases	100
8	Forest - Subtropical/Tropical Swamp	91
9	Wetlands (inland) - Seasonal/Intermittent/Irre...	86
10	Wetlands (inland) - Seasonal/Intermittent Fres...	68
11	Forest - Temperate	59
12	Rocky areas (eg. inland cliffs, mountain peaks)	40
13	Forest - Subtropical/Tropical Dry	32
14	Grassland - Subtropical/Tropical High Altitude	31
15	Savanna - Dry	27
16	Wetlands (inland) - Seasonal/Intermittent Fres...	27
17	Grassland - Temperate	26
18	Shrubland - Temperate	23
19	Shrubland - Mediterranean-type Shrubby Vegetation	21

3. Top ten countries with the most endangered animals:

4. Progress of an animal's status over time: Using Herichthys labridens in Mexico as an example, we track the progress of an animal's conservation status over time.

5. Main threats to animals: This table outlines the top 20 threats that endangered animals face, highlighting problems that must be addressed to ensure their survival.

	threat	counts
0	Annual & perennial non-timber crops	819
1	Agricultural & forestry effluents	659
2	Dams & water management/use	634
3	Mining & quarrying	562
4	Logging & wood harvesting	535
5	Scale Unknown/Unrecorded	427
6	Agro-industry farming	409
7	Domestic & urban waste water	391
8	Livestock farming & ranching	371
9	Type Unknown/Unrecorded	333
10	Housing & urban areas	321
11	Small-holder farming	310
12	Soil erosion, sedimentation	296
13	Herbicides and pesticides	270
14	Unintentional effects: (subsistence/small scal...	261
15	Industrial & military effluents	256
16	Sewage	244
17	Fishing & harvesting aquatic resources	227
18	Nutrient loads	227
19	Unintentional effects: (large scale) [harvest]	224

Related work

• What others have already done with the data?
• Why is your approach original?
• What source of inspiration do you take? Visualizations that you found on other websites or magazines (might be unrelated to your data).
• In case you are using a dataset that you have already explored in another context (ML or ADA course, semester project...), you are required to share the report of that work to outline the differences with the submission for this class.

Originality

Our approach changes the way conservation-challenged animal data is presented by shifting from the traditional, static encyclopedic format to an engaging, dynamic user experience. We introduce a 3D navigable globe that embeds animal profiles, allowing users to explore species by region, inviting users to engage deeply with the content. Additionally, we innovate by integrating gamification through features like the EcoSurvival game. These elements are designed not just for engagement but to spur users into conservation actions, a significant leap beyond the informational offerings of most sites. Our originality lies in these interactive and educational enhancements, drawing on diverse inspirations to make environmental awareness both informative and enjoyable.

Source of Inspiration

After extensive brainstorming and reviewing some relevant websites, we've identified several sources (shown below) from which we're considering drawing inspiration. With preliminary approval from the websits' owners and our professors, we MAY adapt some of their innovative ideas to our project.

Species in Pieces, react-globe.gl, Animalia

References

[1] Sisk, T. D., Launer, A. E., Switky, K. R., & Ehrlich, P. R. (1994). Identifying extinction threats. BioScience, 44(9), 592-604.

Milestone 2 (26th April, 5pm)

10% of the final grade

You can find our website at the following link: website and our report for this milestone.

Milestone 3 (31st May, 5pm)

80% of the final grade

As we have deployed our website, so you don't need any additional technical setup, you can get access to our website, screencast, and process book by following links:

website

screencast

process book

Late policy

• < 24h: 80% of the grade for the milestone
• < 48h: 70% of the grade for the milestone