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Data Science

DataFlash: Urban Institute’s “Do No Harm Guide”

PNR Data Science - Mon, 2021-11-22 10:02

A few months ago, I had the pleasure of attending a Public Library Association (PLA) webinar on data and came across a gem of a resource from the Urban Institute.  The Urban Institute has been around for over 50 years providing facts and knowledge in an accessible way to communities surrounding social and economic issues. This much needed resource on data ethics was published June 2021 from the Urban Institute and is authored by Alice Feng and Jonathan Schwabish and it is called the “Do No Harm Guide – Applying Equity Awareness in Data Visualization”.

This resource is AMAZING. It is a guide on how to develop data analytics that are accessible, diverse, inclusive, and equitable. It looks at data behind the point on a graph to really emphasize the person and lived experience behind each data point. As well, the “Do No Harm Guide …” teaches people how to create data visualizations with an equity lens so that communities are not harmed by the data and visualizations. The theme that is highlighted throughout the guide is the concept of reciprocity – that researchers need to exercise reciprocity when collecting data from communities especially marginalized ones. The question of how can communities benefit from the data collected and the research done is a central question asked and honored throughout this guide; so, rather than exploiting communities for their data, the “Do No Harm Guide…” encourages researchers to empower the communities that they work with by looking at ways the data could improve the lives of the people who make up the respective researched communities.

The most useful and helpful part of this guide is their reference section of ALL the material that they researched to write this great guide.  Alice and Jonathan share the books and websites that inspired and guided their own work in data analytics. If you are short on time, have a look at their one-page DEI data visualization checklist or their one-page DEI data visualization guide at the end of their report. Happy reading!!!

The post DataFlash: Urban Institute’s “Do No Harm Guide” first appeared on Region 5 Blog.
Categories: Data Science

DataFlash: What is Health Data Literacy and “Data Literacy for the Busy Librarian”

PNR Data Science - Mon, 2021-10-25 03:00

A face with numbers dropping down in front of the eyesBig Data is a buzzword in many industries these days including healthcare.  What is data literacy and how does it apply and impact healthcare?  According to MIT and Dalhousie University, data literacy is the ability to collect, manage, evaluate, and apply data in a critical manner.  Though, most individuals didn’t go to school to be data scientists, statisticians, computer scientists etc.  In fact, most people do not consider themselves to be data literate.

In the healthcare field where we are bombarded with all kinds of data, – laboratory and test results, vitals, costs, patient EHRs, and much more – it is absolutely important for the healthcare industry to maximize its usage of this critical data for the betterment of the healthcare field as a whole.  How do we solve data illiteracy? The key is to understand that organizations and individuals need to actively buy in and embrace the data revolution, especially leadership which can help set the standard for the culture of the organization to make good use of data. At the individual level, people need to be honest with oneself and address one’s own weaknesses and fill in the knowledge gaps they have for data literacy – i.e., the ability to read, work with, analyze, and argue with data.  Once, individuals can understand their data literacy weaknesses, then, they can begin to understand how they can improve their respective data skillsets.

In February of 2022, the NNLM Region 5 will be offering a course on data literacy called “Data Literacy for the Busy Librarian”.  This 2-week Moodle course is designed for the beginner and the busier librarian in mind who has an interest in improving their data literacy skillset.  Registration for “Data Literacy for the Busy Librarian” is open now.

The post DataFlash: What is Health Data Literacy and “Data Literacy for the Busy Librarian” first appeared on Region 5 Blog.
Categories: Data Science

DataFlash: MLA’s Data Services Specialization (DSS) Certificate and Region 5 Application Fee Sponsorship

PNR Data Science - Fri, 2021-10-01 10:38

Last January, MLA announced the Data Services Specialization (DSS) certificate that librarians can earn to demonstrate their attainment of the relevant knowledge and skills necessary to provide data services.

Best geared for health sciences librarians and information professionals and built upon the MLA Data Services Competency, the Basic Certification requires the completion of four 4-credit free Network of the National Library of Medicine courses. These courses cover 5 skill areas (i.e. principles of data literacy; data services; research data best practices across the data lifecycle, open science practices, and training and consultation on data-related topics) and are available on demand. An additional three credits in the five skill areas are required and several NNLM courses are listed on the NNLM Data Services Specialization page.

Registration for the NNLM courses is open and free.  MLA DSS certification costs for MLA members is $55 and for MLA nonmembers is $75. You can find more information about the DSS certificate, including cost, requirements, and skills on the MLA website.  If you are interested in having your application fee sponsored by Region 5, fill out this application form.

The post DataFlash: MLA’s Data Services Specialization (DSS) Certificate and Region 5 Application Fee Sponsorship first appeared on Region 5 Blog.
Categories: Data Science

DataFlash: Brent Dykes’ “Effective Data Storytelling” Book Review

PNR Data Science - Mon, 2021-09-27 08:05

These days, there are so many books on data storytelling that claim to do an effective job of explaining how to give impactful data narratives. Lately, I have to go through a pilBooks Logoe of books to find one that really works, sort of like trying to find a needle in a haystack. I stumbled across Brent Dykes’ book “Effective Data Storytelling” when it was first released back in December 2019, but just didn’t have the time to read it.  Finally, I set some reading time aside to read this gem of a book.  I’m so happy that I did!!!

Dykes’ “Effective Data Storytelling” uses fascinating and well-balanced historical stories and anecdotes to explain effective data storytelling; he obviously spent a great deal of time researching the history of data storytelling and data visualizations because it shows in his work!  He not only features historical facts about male pioneers that dominate the data visualization field and data visualization references like Edward Tufte but features historical facts about less talked about female influencers like the nursing pioneer Florence Nightingale and her influential statistical data visualization that demonstrated the disproportionate number of deaths due to infectious diseases rather than to battle injuries in order to convince British army leaders at the time that they needed to adopt better sanitary measures.  Her influential data visualizations on sanitary reforms ended up saving the lives of many British soldiers during both peacetime and during military conflicts.

In short, Dykes’ book on “Effective Data Storytelling” is exactly it.  He teaches about the three pillars of effective data storytelling which he identifies and elaborately but elegantly explains as being data, narrative, and visuals. Dykes goes into quite the detail to explain the psychology, ethics, and anatomy of a great data story.  I thoroughly enjoyed and updated my data storytelling knowledge through reading this great book.  The only thing I regret is not reading this book sooner!!!

Image Source: Bing.com under a Public Domain license

The post DataFlash: Brent Dykes’ “Effective Data Storytelling” Book Review first appeared on Region 5 Blog.
Categories: Data Science