State of the Art
The state of the art describes the current knowledge in a specific field through the analysis of a corpus of scientific publications. It serves as a basis for formulating the research question and developing related hypotheses.
"We are like dwarfs seated on the shoulders of giants. We see more, and farther, not because of the sharpness of our sight or the greatness of our stature, but because we are carried high and lifted up by their giant size."
Bernard de Chartres, 1159
Why to write a State of the Art?
In science, being the first to present research findings is crucial. For instance let's imagine that my research question is "How are colors and shapes transmitted from one generation to the next in pea?". You cannot gain recognition by rediscovering Mendel's laws of inheritance in peas and presenting them as your own. Mendel did it in 1865, and everyone knows it because he published it. When Mendel published his work, it was novel. Today, any researcher must demonstrate novelty by presenting a state of the art and showing that no one has yet answered the question they address. That’s why Mendel’s work remains foundational, whereas repeating the same experiment will not bring you recognition for you work as your research question is already answered.
Besides, they are many advantages to write state of the art:
- It is the best way to learn about your research question and refine it.
- It helps you to formulate relevant questions as the ones that many people in the field are trying to solve.
- Collection of different points of view and approaches to a solution. Which ones are promising, which ones are dead-end and which ones are unexplored yet.
- It gathers the tools, methods and elements previous researchers made for you to help you find a solution on your question.
- It's enough consistent to stand as publication on its own which can then be cited by next articles.
How to write a State of the Art?
1. Determine initial research question and field
Writting a good State of the Art relies on the problem definition. If your problem is not clearly defined, your report will be miscellaneous.
- What is the research question to be addressed?
- What field of knowledge will the search address?
2. Determine time frame
Some problems or fields have centuries of scientific works and publications. It is therefore crucial to define the scope of the literature we will consider. From which year onward we will focus.
- What historical markers help demarcate the time frame of now?
- What time frame can be justified to mark the beginning of the review?
3. Refine research question to fit with the new time frame
Given the information of the time frame and its main scope, you may adjust the initial question to align with the newly acquired information.
4. Strategy to find and classify relevant articles
- Establish a list of key words related to your question
- Search using key words or expressions an article that already did a state of the art. Then you can use this state of the art as a basis for yours and refine it.
- If you didn't find an already existing state of the art perfectly matching your question in the literature, then collect articles containing your key words.
- Systematically read only the conclusion & perspective of all the collected articles and keep articles that have conclusion related to your question.
- Use one of these article as a seed meaning list all the articles in the reference section that may be related to your question and apply step 4 again.
- After trying many seeds you should start to have a consistent corpus of articles. A good indicator is when the reference sections of the articles you are screening begin to repeat the same sources.
- Stop reading new articles.
- Organize your raw corpus of articles. You classify them according to a chronology, group them by ideas, themes, fields, technology, authors, etc. You can also visualize how articles are related to each others using tools like connectedpapers.
Another tip: check Github/Gitlab repositories to see if they are an existing tool available online. Compare published code source of tools addressing the same problem. Often, all these tools are redundant or forks so you may realise that lengthy articles are not necessary presenting great improvment or change on an original method. Even more often, they are no published tool or source code at all despite the claim of the author in their article. You can try to contact the authors to ask the archive of the source code by e-mail. But again, often you will have no answer. This help you to filter articles and associated work that are not relevant.
Last tip: check travaux parlementaires of the French Senate. Often this is first class scientific reports with excellent basis for a state of the art. It also give you a non-scientific point of view on a field or a scientific problem. This may help you to check if you didn't forget articles and point of views related to your research question.
5. Analyses
Read the articles to become familiar with the corpus.
- What are the similarities across articles?
- What are gaps and assumptions in the current knowledge?
- Which articles support or contradict your thinking?
- Do certain authors dominate the literature?
6. Technological watch
Once you did your first state of the art, the work is not over. You will continue to watch what other researchers are publishing. This require a system for recording and summarizing your readings. Use bibliography softwares such as Zotero to record every day your understanding of what your read.
References
How to Conduct a State-of-the-Art Literature Review
Erin Barry, Jerusalem Merkebu, Lara Varpio
Journal of Graduate Medical Education, 2016. DOI: PMC9765899
Relevant Tags
About the Author
Latest Articles
-
Chado: the GMOD Database Schema
Chado is a relational database schema that underlies many GMOD installations. It is capable of representing many of the general classes of data frequently encountered in modern biology such as sequence, sequence comparisons, phenotypes, genotypes, ontologies, publications, and phylogeny. It has been designed to handle complex representations of biological knowledge and is the most sophisticated relational schemas currently available in molecular biology.JAN 2025 · PIERRE-EDOUARD GUERIN -
Error Messages with a CLI
I am an anxious person. So error messages always makes my heart beat faster. Hopefully, following the Pareto Principle, 80% of error messages are mild while 20% are the really tough one. The point is to solve the first kind as quickly as possible and effortless. To do so, allow the user to solve the issue by himself with clear messages and hints (in the case of errors related to input files or parameters). Clear presentation of the context and precise localization of the error in the code will save a lot of useless and tedious work to the developer. The time spared on the easy errors just by having better messages, then can be reallocated to the second kind of errors, the troublemakers.NOV 2024 · PIERRE-EDOUARD GUERIN -
Generative AI: Integrate openAI API with Python
I was fortunate to follow the course of Sven Warris about software tools to integrate genAI into your own work and applications. The course is aimed at data scientists and bioinformaticians.MAY 2024 · PIERRE-EDOUARD GUERIN