How can you identify gaps in data visualization research?

1 What are gaps in data visualization research?

Gaps in data visualization research are areas or topics that have not been sufficiently explored, addressed, or solved by existing studies, publications, or frameworks. They can be related to technical, theoretical, or practical aspects of data visualization, such as design principles, evaluation methods, user needs, domain applications, or emerging technologies. Identifying gaps in data visualization research can help you discover new questions, problems, or solutions that can advance the field and your own data visualization projects.

2 Why are gaps in data visualization research important?

Gaps in data visualization research are important because they indicate the potential for innovation, improvement, and impact in data visualization. By finding and filling gaps in data visualization research, you can contribute to the development of new knowledge, methods, or tools that can benefit yourself and others who use data visualization. You can also gain a competitive edge, a unique perspective, or a deeper understanding of data visualization by exploring gaps in data visualization research.

3 How can you find gaps in data visualization research?

One of the most common and effective ways to find gaps in data visualization research is to conduct a literature review. A literature review is a systematic and critical analysis of existing sources related to a specific topic or question in data visualization. You can use online databases, journals, books, or websites to search for relevant sources and then synthesize, compare, and evaluate them. A literature review can help you identify what has been done, what has not been done, and what can be done better or differently in data visualization research.

4 How can you fill gaps in data visualization research?

Once you have identified gaps in data visualization research, you can fill them by conducting your own research or applying existing research to new contexts or problems. You can use various research methods, such as experiments, surveys, interviews, case studies, or prototypes, to collect and analyze data and generate new findings, insights, or recommendations. You can also use existing research to inform, inspire, or adapt your data visualization projects to different domains, audiences, or purposes.

5 How can you share gaps in data visualization research?

Sharing gaps in data visualization research is an important step to disseminate your work, get feedback, and collaborate with others who are interested in the same topic or problem. You can share gaps in data visualization research by publishing your research in academic journals, conferences, or books, or by presenting your research in workshops, webinars, or podcasts. You can also share gaps in data visualization research by creating and sharing your data visualizations online, on social media, or on platforms like Medium, Tableau Public, or Observable.