OBJECTIVE:To develop a clear understanding of data interpretation and visualization techniques using real-world data from the NSW Water Valuation in Australia.
TASK:1Data Selection: Review the NSW Water Valuation Report, focusing specifically on Sections 4 and 5. This report contains a wealth of data regarding water valuation in New South Wales, Australia.
Figure Creation:Create two distinct figures (graphs or charts) using data extracted from either the tables or the narrative descriptions in the specified sections of the report.
Ensure each figure comprises at least five data points for comparison. These could be different values, time periods, geographical areas, or other relevant comparative measures.
Figure Specification:Each figure should have clearly labeled axes.
Include an appropriate and descriptive title for each figure that succinctly reflects its content and purpose.
Data Interpretation:Below each figure, write 2-3 concise sentences that capture the ‘take-home message’ of the figure. This message should encapsulate the key insight or conclusion that can be drawn from the data presented.
An explanation of “take home message” is found here.
Guidance on Good Figure Development:Consult the additional provided resource for understanding critical components of effective data visualization. This resource will offer valuable insights into creating figures that are not only accurate but also impactful and easy to understand.
Submission Format:Compile your figures and their explanations into a single document.
Acceptable formats for submission are PDF.
Requirements: 2-3 sentences | .doc file
task 2:
Objective:
To understand, analyze, and present data related to water use and sustainability using both traditional and creative visualization techniques.
Background:
Data doesn’t have to be dull. While bar graphs and pie charts have their place, there’s a vast landscape of visualization techniques waiting to be explored. Drawing inspiration from the Dear Data project, this assignment will challenge you to look at water data in a fresh, creative way.
Instructions (Additional Honors Assignment at the End):
Question Development and Topic Selection: Develop a question within a topic of your choice within the realm of water use and sustainability. This can range from topics like daily water consumption in households to the effects of climate change on global water resources.
Data Collection:Gather your own data or source it from reliable online platforms.
Ensure accuracy and relevance to your chosen topic.
Traditional Visualization:Start by representing your chosen data using traditional techniques like bar graphs, pie charts, or line graphs.
Ensure clarity and correct representation of the data.
Creative Visualization:Review the Dear Data project.
Dive deep into creativity. Explore unique ways of representing the same set of data. This could be hand sketches, digital art, or even an interactive online representation.
Remember, while aesthetics matter, clarity and effective communication of the data remain paramount.
Write-Up:Data Source: If you are collecting your own data, describe your methods for doing so and justify how they are answering your question. If you are getting data from another source, cite this information using APA format and justify how this data answers your question.
Data Message: In a minimum of four sentences, elucidate the primary message or insight that your visualizations (both traditional and creative) convey.
Comparison: Reflect on the two visualization techniques. In a separate paragraph, discuss whether they communicate the same story or offer different perspectives. Delve into the advantages and potential limitations of each method in conveying the data’s message.
Submission:Incorporate both your traditional and creative visualizations.
Attach or hyperlink your data source. Provide the original form in which the data was displayed (screenshots are acceptable).
Submit your visualizations and written reflections via the assigned platform or channel by the stipulated deadline.
Requirements: create dear data project
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