Quality Assurance of Data Sets: NISO Spring Training Series

What You'll Want to Know!

This 8-week course on Quality Assurance of Data Sets will cover three main topics: Cleaning, Provenance, and Discoverability. Participants will learn about the importance of data quality and its impact on decision-making, as well as techniques for improving data quality. By the end of the course, participants will be able to:

  • Use data cleaning techniques to detect and correct errors, missing values, and inconsistencies in data sets
  • Understand and capture data provenance information to track and explain data cleaning operations 
  • Understand the impact of data cleaning on downstream analysis and detecting intentional and unintentional problems in data.

To register, please visit the event page.

About the Instructor

Dr. Leslie McIntosh, is the VP of Research Integrity at Digital Science and dedicates her work to improving research and investigating and reducing mis- and dis-information in science.

As an academic turned entrepreneur, she founded Ripeta in 2017 to improve research quality and integrity. Now part of Digital Science, the algorithms lead in detecting trust markers of research manuscripts. She works around the globe with governments, publishers, institutions, and companies to improve research and scientific decision-making. She has given hundreds of talks, including to the US-NIH, NASA, and World Congress on Research Integrity, and consulted with the US, Canadian, and European governments. Dr. McIntosh’s work was the most-read RetractionWatch post of 2022.

Dr. McIntosh has dedicated her work to improving science. Since 2014, this has focused on highlighting the need for reproducible science, transparently reporting science, and the need to build trust in science. 

She has experience leading diverse teams to develop and deliver meaningful data to improve scientific decisions. Dr. McIntosh is an accomplished biomedical informatician and data scientist. As an internationally known consultant and speaker, she is passionate about mentoring the next generation of data scientists. As with others, I stand on the shoulders of my ancestors. First, my great-grandmother, who labored picking cotton while supporting her seven children. Second, one who would be my grandmother. Third, one who would become the first person in my family to obtain a university-level education, going on to become a scientist and an inspiration for me.  

She holds a Master's and Ph.D. in Public Health with concentrations in Biostatistics and Epidemiology from Saint Louis University and a Certificate in Women’s Leadership Forum from Washington University Olin’s School of Business