Tag Archives: Data Management

Spring 2016 Data Management Workshops

This semester, the Libraries will offer a workshop covering:

  • Best Practices for Managing Your Data
  • Data Management Plans, Data Sharing and Archiving
  • Reproducible Research

The workshop will repeat in two locations on:

  • Monday, March 7, 12-1:30 pm in the Library of Science and Medicine Conference Room (1st Floor)
  • Tuesday, March 8, 1:10 to 2:40 pm in Alexander Library Teleconference Lecture Hall (4th floor)

The two sessions are identical – no need to come to both.

The first part of the session will focus on Best Practices for Managing Your Data. 

  • We discuss methods to organize, describe, backup, and archive your research data in order to ensure its future usability and accessibility.  Developing good habits for handling your data from the start will save time and frustration later, and increase the ultimate impact of your research.

The second part covers Data Management Plans, Data Sharing and Archiving.

  • This portion is targeted to researchers who need to write data management plans (DMPs) and share their data as part of their grant application, research and publication process.  It reviews DMP guidelines, checklist, and general advice, along with options for sharing and permanently archiving research data.

The third part discusses Reproducible Research.

  • We cover the growing movement to make the products of research accessible and usable by others in order to verify, replicate, and extend research findings.  We review how to plan research, to create publications, code, and data in open, reusable formats, and maximize the impact of shared research findings.

No need to register, just come for what you are interested in.

Additional data management resources, including presentation slides, can be found here: http://libguides.rutgers.edu/datamanagement

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Fall 2015 Data Management Workshops

This semester, the Libraries will offer a workshop covering:

  • Best Practices for Managing Your Data
  • Data Management Plans, Data Sharing and Archiving
  • Reproducible Research

The workshop will repeat in two locations on:

  • Monday, October 19, 12-3 pm in the Library of Science and Medicine Conference Room (1st Floor)
  • Thursday, October 22, 1:10 to 4:10 pm in Alexander Library Room 415

The two sessions are identical – no need to come to both.

The first hour of the session will focus on Best Practices for Managing Your Data. 

  • We discuss methods to organize, describe, backup, and archive your research data in order to ensure its future usability and accessibility.  Developing good habits for handling your data from the start will save time and frustration later, and increase the ultimate impact of your research.

The second hour covers Data Management Plans, Data Sharing and Archiving.

  • This portion is targeted to researchers who need to write data management plans (DMPs) and share their data as part of their grant application, research and publication process.  It reviews DMP guidelines, checklist, and general advice, along with options for sharing and permanently archiving research data.

The third hour discusses Reproducible Research.

  • We cover the growing movement to make the products of research accessible and usable by others in order to verify, replicate, and extend research findings.  We review how to plan research, to create publications, code, and data in open, reusable formats, and maximize the impact of shared research findings.

No need to register, just come for portions you are interested in.

Additional data management resources, including presentation slides, can be found here: http://libguides.rutgers.edu/datamanagement

Spring 2015 Data Management Workshops

The final component of the Spring Data Workshop series are three workshops on aspects of data management, presented by Ryan Womack, Data Librarian, and Aletia Morgan, Research Data Manager at Rutgers University Libraries.

To go directly to the registration page for this series, click here.  A detailed calendar and descriptions of each workshop are below.

Logistics

Data management workshops for Spring 2015 will be held at the Library of Science and Medicine (Busch campus) in the Conference Room on the first floor.  Workshops are held on Thursdays from 1:40-3:00 pm according to the schedule below. 

Description of Workshops:

§ Best Practices for Managing Your Data  (February 26)

This workshop is targeted to graduate students who are generating data for their own research.  The session discusses methods to organize, describe, backup, and archive your research data in order to ensure its future usability and accessibility.  Developing good habits for handling your data from the start will save time and frustration later, and increase the ultimate impact of your research.

Additional data management resources can be found here: http://libguides.rutgers.edu/datamanagement

§ Data Management Plans, Data Sharing and Archiving (March 5)

This workshop is targeted to researchers who need to write data management plans (DMPs) and share their data as part of their grant application, research and publication process.  It reviews DMP guidelines, checklist, and general advice, along with options for sharing and permanently archiving research data.

§ Reproducible Research (March 12)

The workshop is targeted to any interested faculty and students who are interested in learning about the growing interest in making the products of research accessible and usable by others in order to verify, replicate, and extend research findings.  It reviews how to plan research, to create publications, code, and data in open, reusable formats, and maximize the impact of shared research findings.

Register for the workshops here

Statistical Software and Data Workshops – Spring 2015

Rutgers University Libraries Data Services Workshop Series (New Brunswick)

January 2015

This Spring, Ryan Womack, Data Librarian, will give a series of workshops on statistical software, data visualization, and data management, as part of the Rutgers University Libraries Data Services.  To go directly to the registration page, click here.  A detailed calendar and descriptions of each workshop are below.

Logistics

All workshops for Spring 2015 will be held in the Conference Room on the 1st floor of the Library of Science and Medicine (Busch Campus).  Workshops are held on Wednesday afternoons from 3:20 to 4:40 pm or Thursday afternoons from 1:40 to 3:00 pm.  The Wednesday series covers many aspects of the R open source statistical software environment.  The early Thursday sessions are introductions to commerical statisical software  (SPSS, Stata, SAS).  Later in the semester, the Thursday sessions will cover several aspects of research data management.

You are encouraged to bring your own laptop for these sessions.  Laptops are also available for borrowing during the workshops.  Room capacity is approximately 25.  SPSS, Stata, and SAS sessions will use the apps.rutgers.edu remote system.

If you can’t make the workshops, or would like a preview or refresher, screencast versions of many of the presentations are already available at http://libguides.rutgers.edu/data.  Additional screencasts are continually being added to this series.

Calendar of workshops

Wednesday   Thursday
Jan 28 Intro to R, part I, Statistical Functions Intro to SPSS Jan 29
Feb 4 Intro to R, part II, Graphics Intro to Stata Feb 5
Feb 11 Intro to R, part III, Data Manipulation Intro to SAS Feb 12
Feb 18 Data Visualization, part I, Principles & Use in lattice and ggplot2
Feb 25 Data Visualization, part II, Miscellany of Methods Best Practices for Managing your Research Data Feb 26
March 4 Data Visualization, part III, 3-D, Interactive and Big Data Data Management Plans, Data Sharing and Archiving March 5
March 11 Survival Analysis in R Reproducible Research  March 12
March 25 Time Series in R

 Register for the workshops here

Description of Workshops:

§ Introduction to R (Jan 28, Feb 4, and Feb 11) – This 3-part series provides an orientation to the R programming environment.  R is freely available, open source statistical software that has been widely adopted in the research community.  Due to its open nature, thousands of additional packages have been created by contributors to implement the latest statistical techniques, making R a very powerful tool.  No prior knowledge is assumed. The three parts cover:

(Jan 28) Part I – Statistical Techniques: getting around in R, descriptive statistics, regression, significance tests, working with packages

(Feb 4) Part II – Graphics:  comparison of graphing techniques in base R, lattice, and ggplot2 packages

(Feb 11) Part III – Data Manipulation:  data import and transformation, additional methods for working with large data sets

Additional R resources, including handouts, scripts, and screencast versions of the workshops, can be found here: http://libguides.rutgers.edu/data_R

R is freely downloadable from http://r-project.org

§ Introduction to SPSS (Jan 29) provides a single session overview of navigating the basics of SPSS.  SPSS is widely used statistical software with strengths in survey analysis and other social science disciplines.  If you are already using SPSS with some degree of success, this session may be too basic for you.

Copies of the workshop materials, a screencast, and additional SPSS resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208425

SPSS is made available by OIRT at a discounted academic rate, currently $100/academic year.  Find it at software.rutgers.edu.  SPSS is also available in campus computer labs and via the Apps server (see below).

§ Introduction to Stata (Feb 5) provides a single session overview of navigating the basics of Stata.  Stata is flexible and allows relatively easy access to programming features.  It is popular in economics among other areas. If you are already using Stata with some degree of success, this session may be too basic for you.

Copies of the workshop materials, a screencast, and additional Stata resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208427

Stata is made available by OIRT via campus license with no additional charge to install for Rutgers users.  Find it at software.rutgers.edu.

§ Introduction to SAS (Feb 12) provides a single session overview of navigating the basics of SAS.  SAS is a powerful and long-standing system that handles large data sets well, and is popular in the pharmaceutical industry, among other applications. If you are already using SAS with some degree of success, this session may be too basic for you.

Copies of the workshop materials, a screencast, and additional SAS resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208423

SAS is made available by OIRT at a discounted academic rate, currently $100/academic year.  Find it at software.rutgers.edu.  SAS is also available in campus computer labs, online via the SAS University Edition cloud service, and via the Apps server (see below).
 

Note: Accessing software via apps.rutgers.edu

SPSS, SAS, Stata, and R are available for remote access on apps.rutgers.eduapps.rutgers.edu does not require any software installation, but you must activate the service first at netid.rutgers.edu.

On Wednesdays, the R series will continue, including:

§ Data Visualization in R  in 3 parts (basics, more methods, interactive & big data)

§ Time Series in R 

§ Survival Analysis in R 

On Thursdays, other topics in Data Management will be addressed, including:

§ Data Management Best Practices 

§ Data Management Plans, Data Sharing and Archiving

§ Reproducible Research

Additional data management resources can be found here: http://libguides.rutgers.edu/datamanagement

Logistics, again

To repeat, All workshops for Spring 2015 will be held in the Conference Room on the 1st floor of the Library of Science and Medicine (Busch Campus) on Wednesday afternoons (starting at 3:20) and Thursday afternoons (starting at 1:40).  Bring your own laptop if you can, although there will be laptops available to borrow.

 Register for the workshops here

Data Dream Team?

Attending IASSIST 2013 was very therapeutic, and I have returned from Germany invigorated and with many new thoughts about improving data services.

One thing I now wonder about is what I would do if I could design a dream lineup for a Data Services team, assuming that I had 4 or 5 staff lines at my disposal to hire from scratch.  What would the ideal configuration look like?  My thoughts are primarily about an academic library setting similar to my own, but this would be an interesting exercise in other settings too.

Is it hierarchical (a head with subordinates)?  A team of equals?  Are responsibilities cleanly divided or shared?

Some technical skills that are required: statistical, mathematical and engineering software (R/SAS/SPSS/Matlab/Mathematica, etc. etc.), GIS, Qualitiative Analysis, Data Visualization.  Scripting languages (Python, Java), Database skills. How are these divided among positions?

We also need a knowledge of public data sources, outreach and instruction skills in person and via electronic media.  Research data management also requires one-on-one people skills to negotiate data acquisition and provide advice across many disciplines.  Is it better to split these along functional lines (RDM specialist vs. Public Services Data Librarian) or along subject lines (e.g., a science data librarian and a social sciences data librarian handle both instruction and individual RDM work in their respective disciplines)?  Does digital humanities fit in here, or is it a separate issue?

So here’s the thought exercise: List the five members of your dream data team…