I am in the process of revising the report. I have gathered information useful in providing me with the context about technical aspects of the topic and was able to organize it in a way that helped me understand details about the inefficiency of traditional software and features of the software I proposed. However, I need additional research that supports the connection between my problem and solution sections considering that the logic of my argument makes claims about concepts beyond just the software in itself. Moving forward, I need to make the current body of my report more concise so that I can make space to clearly connect the problem to my solution throughout the paper.
As the rubric mentioned, I need to make my central purpose and argument apparent to the reader.
I pasted my Executive Summary below because I need support in clarifying my focus:
“There is a pressing problem of inefficiency regarding analysis of data related to global climate change. Given the large quantity of diverse data related to global climate change, there is unanswered demand for implementation of a scalable software capable of accurately conducting broad integrative analysis. Consequentially, there is limited collaboration amongst geoscience experts and a lack of fulfilling potential in terms of informing the best strategic action.
The solution to the problem is Software as a Service (SaaS), specifically a cloud computing framework that brings ease of use and demonstrated efficiency to the table. Not only is cloud computing phenomenally productive in itself, but it is also a launching pad for other technological developments. Crucially, cloud computing is a gateway to facilitate synthesis of various climate science data, and its capability to cultivate increased collaboration brings the potential to derive key insights necessary to make massive progress in mitigating climate change. However, while providing SaaS in the form of cloud computing is a valuable starting point to address the problem, there is a need for additional research to understand how to continue moving forward in improving efficiency of broad integrative data analysis tools.”
My questions: Are there any gaps in understanding the problem? How can I more clearly define the problem? How can I draw a stronger connection between the problem and solution aside from presenting the insufficiency of the traditional software and features of cloud computing? Does the solution effectively address the problem?
Successes:
One of my key strengths is that I have highly reputable sources. They are reliable, current and are all peer-reviewed sources. So, I need to ensure the additional research I gather also follows a high standard of excellence.
I also did well at knowing my audience in terms of deciding not to explain global climate change to them because defining climate change to the Center for Climate and Energy Solutions would be redundant.
I provided a compelling statistic from NASA to communicate the large quantity and high degree of diversity in global climate change data.
Moreover, I did well at outlining the evolution of technology that created the increasing accumulation of diverse global climate change data as well as the insufficiency of traditional data analysis software. I also provided some valuable answers regarding how cloud computing addresses insufficiency of traditional data analysis software. I introduced lack of collaboration as a component of the problem and mentioned an example of how cloud computing has helped cultivate collaboration amongst scientists.
Another one of my key strengths is my grammar. I put a lot of attention into editing the paper before turning in the Report Draft assignment. So, the prose is great.
I also selected a topic that has high potential for attaining a lot of originality of thought and design. I am passionate about enhancing the operations involved in mitigating global climate change. I see potential for my voice to shine through if I appropriately build the argument.
Challenges:
My main challenge is finding sources that focus on proving my sub-arguments and effectively inserting information from them into the argument.
As a subset of the main challenge, I need to improve in the breadth of material I use to demonstrate significance of the problem. I gloss over the large volume and degree of diversity in climate science data and then narrowly focus the remainder of the problem on conveying insufficiency of traditional software. I need to first start by showing the inefficiency regarding analysis of data related to global climate change that is unrelated to software because there are more ways to convey that point aside from only elaborating on the weaknesses of traditional software. I also need to expand upon the lack of broad integrative analysis and collaboration currently taking place. From there, my challenge is to highlight how insufficiencies of traditional data analysis software segregates scientists and prohibits them from collaborating in brainstorming impactful action.
Similarly, my solution needs to focus on explaining how sufficient data analysis software plays a part in the entire solution. Particularly, I need to convey how cloud computing facilitates collaboration by inserting my original ideas to bring significance to cloud computing features that I illustrated. From there, I need to depict how collaboration cultivates key insights informing climate change action.
My evaluation section is going to be based on the additional information I discover while enhancing the problem and solution sections. Instead of only focusing on how to make cloud computing even more efficient, I can consider how other solutions not related to software may compliment cloud computing with the full scope of my problem in mind. I can also evaluate how I could have done better in approaching the subject matter and gaps in my understanding.
My challenge is being comfortable with using sources that do not even mention software. I had restricted myself because I was concerned sources that did not mention software would not be relevant to my paper. However, my argument will be stronger if I focus on finding relevant information from articles in a variety of subjects.
My question: Do ya’ll have recommendations of sources that speak to the sub-arguments I aim to expand upon?
Inserting the additional information also brings the remaining challenge to implement the peer feedback I received to incorporate more numerical statistics into my explanation. While I inserted a few numerical statistics into the Report Draft, my argument will only be enhanced by including more of that type of support. Also, considering my audience is going to be a group of experts that aims to combat a global climate change problem holding a high regard for scientific data in communicating truth, I need to incorporate more numerical support into the report.
Checklist:
1) Create outline for the problem and solution sections of my paper based on the sub-arguments in the executive summary
2) Make the explanations of the software more concise and include only the degree of technical language about the software that is appropriate for the given audience
3) Find additional, reputable sources to gather information that supports each component of the outline so that I effectively prove sub-arguments
4) Extract information from the additional sources and insert it into paper with a concentration on the transition between ideas
5) In order to create a thorough evaluation section of the report, complete a separate free write reflection regarding how other solutions not related to software may compliment cloud computing. Take into account the full scope of my problem, how I could have done better in approaching the subject matter, and remaining gaps in my understanding. Organize the brainstormed ideas to supplement the evaluation section of the report. Revise to present it in a creative way that smoothly transitions into the conclusion.
Comment by Kyle Pesek:
Hello Mary,
It sounds like you have a solid idea of all the additional revisions and research left before you finalize your Report according to what you have laid out in your post. Regarding your question on how to include sources that do not directly mention these software as a service (SaaS) solutions, I imagine that research covering the practical implementation considerations of cloud computing infrastructure could yield interesting results. Since you are examining how SaaS can be best-paired to process the large quantities of climate change datasets produced by researchers around the world, it makes synergistic sense to have the servers running the SaaS be outputting as minimal of a carbon footprint as possible. I would suggest looking into any research that examines the on-site renewable energy generation compatibility with the power demands of a typical cloud computing facility. Since cloud service providers are typically cheaper and more efficient than traditional data centers such that “the transition to cloud computing between 2021 and 2024 should prevent at least 629 million metric tons of CO2 from entering the atmosphere” (Francis 2021), the inclusion of renewable energies drastically reduces total overall emissions originating from what promises to be a quickly growing sector in the approaching years. Best of luck on finding this and other numerical sources that research the practical considerations of SaaS handling climate change data!
References:
Francis, Taylor. 2021. “The Next Big Cloud Competition is the Race to Zero Emissions.” World Economic Forum, September 20. https://www.weforum.org/agenda/2021/09/the-next-big-cloud-competition-is-the-race-to-zero-emissions/
My Comment:
Hi Kyle,
Thanks for the insightful comment! This is so useful. It supports me in diving deeper into implementation of the cloud computing as part of the solution section. As mentioned in the comment, considering how to have the servers running the SaaS be outputting as minimal of a carbon footprint as possible helps tie the elements of my solution together which is the over-arching goal I have moving from my draft to the final version.
It is great that the cloud service providers are typically cheaper than the traditional data centers because showing my solution is cost-effective is crucial.