Register Now for the Second Annual UC DATA Day

data dayThe University of Cincinnati Libraries and IT@UC announce the 2nd annual UC DATA Day. Scheduled for Thursday, March 23 from 8:30 a.m. – 3:30 p.m. in TUC 400 ABC (see directions), UC DATA Day 2017 will feature a full schedule of engaging events. All events are free and include lunch and an afternoon reception. The public is welcome.

Registration is now open at bit.ly/UCDataDay. Seats are limited, so register early.  Continue reading

Love Your Data Week Day 5 Rescuing Unloved Data

Today’s LYD post is by Amy Koshoffer, Science Informationist based at the Geology Math and Physics Library with editorial support from Dr. Eric J. Tepe, Assistant Professor of Biology and Curator of the Margaret H. Fulford Herbarium.

It has been sometime since I stepped over the threshold of my old lab in the Care/Crawley Building. Many changes occurred in the interim including a move to another floor of the building. There are times I miss the bench research and the data I created in my time as a senior research assistant. One of my favorite techniques was microscopy and particularly Electron Microscopy (EM). I remember the multitude of samples processed, the long wait for samples to be ready to image and then finally all the amazing images we captured. Processing samples for EM imagining is a long and sometimes challenging technique. The samples need to be dehydrated and then infiltrated with a resin to stabilize the structures and prevent destruction from the electron beam during viewing. You might not know if a sample has been ideally preserved until you get to the imaging lab and begin to examine the sample. But what joy when the images look amazing with crisp detail and no water holes. So much work and resources went into the sample preservation and acquiring images.

I wonder what will happen to that effort in the years and decades to come. Are there others who might want to use the physical samples and digital images in their own work? Did I do what was needed to make sure that someone could reuse all the data created? Continue reading

Love Your Data Week Day 4 – Finding the Right Data

Today’s LYD post is by Don P. Jason III, MLIS, MS, Clinical Informationist based at the Donald C. Harrison Health Sciences Library.

Welcome to Day 4 of “Love Your Data Week!” Whether you’re a student analyzing a data set for a school project or a researcher combining data sets to create new insights, finding the right data is essential! This blog post will list a few places you can look to find free, authoritative and unique data sets. The data sets have be broken down into three categories:  US Government Data Sets, International Data Sets and Google Data Sets.

US Government Data Sets

Data.gov http://data.gov – This web site has an eclectic mix of datasets from criminal justice to climate data.  This government site encourages people to use the data to create web and mobile applications and design data visualizations.

US Census Bureau http://www.census.gov/data.html – This web site provides data on the US population and economy.  Utilizing this site’s data has never been easier thanks to new: API’s, data visualizations, mobile apps and interactive web apps.

Healthdata.gov https://www.healthdata.gov/ – This web site includes US healthcare data.  The site is dedicated to making high value health data more accessible to entrepreneurs, researchers and policy makers.

National Climatic Data Center http://www.ncdc.noaa.gov/data-access/quick-links#loc-clim – This is the world’s largest archive of weather data. It has a robust collection of environmental, meteorological and climate data sets from the US National Climatic Data Center.

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Love Your Data Week Day 3 – Good data examples

Today’s Love Your Data Week’s post is by Tiffany Grant PhD, Interim Assistant Director for Research and Informatics at the Health Sciences Library (HSL) and Research Informationist.

Data, FAIR Data

If asked to define good data, the definitions would run the gamut, as the interpretation of the term will be specific to the types and formats of data typically collected by the individual. However, simply put, good data meets the standard of being of good quality, and data quality generally refers to the ability of data to serve the use it was intended. In short, data quality hinges on the reliability and application efficiency of data. The combination of good data quality and data documentation ensures accurate interpretation and reproducibility. Beyond documentation, a number of federal mandates dictate that data be shared beyond one’s own lab notebook, and in order to ensure proper interpretation and reproducibility of your data, it must be FAIR.

 

 

 

 

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Love Your Data Week Day 2 Documenting, Describing and Defining

Today’s Love Your Data Week’s post is by Tiffany Grant PhD, Interim Assistant Director for Research and Informatics at the Health Sciences Library (HSL) and Research Informationist.

The Big 3 of Data

Documenting, describing and defining your data are the 3 most critical components of good data management and your data legacy. If done properly, documentation ensures accurate interpretation and reproducibility of your data. Additionally, it improves the integrity of the scholarly record by providing a more complete picture of how your research was conducted.

Data Things to Do

  1. Document all file names and formats associated with your project
  2. Describe how your data was derived including a description of any equipment and/or software used in the process
    1. Describe your file naming conventions and folder structures
  3. Define any abbreviations, variables or codes used in your data or your file names/folders

Big 3 Data Basics

Who: Who are the contributors?

What: What kind of data was collected and what analyses were done to generate the data?

Why: Why was the project started, i.e. what questions did you hope to answer?

Where: Where did you get your data (if you aren’t the creator)? What is the physical location of the data?

How: How was your data generated?  

Message of the day

Good documentation tells people they can trust your data by enabling validation, replication, and reuse.

Love Your Data Week Day 1 Defining Data Quality

Today’s LYD post features the thoughts of Dylan Shields, the Graduate Assistant for the Chemistry-Biology Library and Chemistry Graduate Student in Anna Gudmundsdottir’s Lab.

Welcome back to another edition of Love Your Data Week!!

The first topic for this week is going to focus on DEFINING DATA QUALITY!

So what IS data quality? Well, first off it is important to note that data quality definitions and practices can differ quite vastly depending on the field of study. However, there are a few markers of data quality that can be broadly applicable to most research. These markers include: accuracy, consistency, completeness, and accessibility.

So what are these markers and why are they important?

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Spring Semester 2017 GIS Learning Community Meetings

If you have an interest in connecting with others using or learning about GIS, then please join the GIS Learning Community at an upcoming meeting.

Date: Feb 1st , March 8th , April 12th

Time: 3:15 pm to 4:25 pm

Venue: 462 Langsam

GIS stands for Geographic Information Systems.  The goal of the community is to create a user-driven forum for novice and expert practitioners to come together and discuss tools, resources and solutions to questions and new projects that develop as researchers consider the spatial aspects of their data.   We invite interested individual across all of UC to join us in building this community.

Contact Amy Koshoffer at koshofae@ucmail.uc.edu with questions or to be added to the GIS LC mailing list.

Visit UC Libraries Research Data and GIS Services website for more information: http://libraries.uc.edu/digital-scholarship/data-services.html

Presenting Geoffrey Pinski, Dec. 12, to Talk about Intellectual Property and Research Data

Geoffrey Pinski

Geoffrey Pinski

Are you wondering about IP?

Join the University of Cincinnati Libraries 1 p.m., Monday, Dec. 12, to learn about Intellectual Property (IP) and how it plays a role in your scholarship and research.

Geoffrey Pinski, director, UC Technology Accelerator for Commercialization, will talk on IP and Research Data.

Intellectual Property and Research Data

Date:  December 12, 2016

Time: 1:00 pm

Venue:  3351 Medical Sciences Building (MSB)

The talk is free and open to all.

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