Past Workshops

New for Spring 2013

Historical GIS (Class materials)

This class will show some ways that ArcGIS can be used for the analysis and visualization of historical spatial data. Topics discussed will be: sources for GIS layers reflecting the past, georeferencing a scanned historic map, creating new layers from scratch based on known locations of features, editing existing GIS layers to reflect former features and vectorizing a scanned map to create editable features.

Introduction for GIS (Class materials)

Do you want to find out how geographic information (GIS) software can aid your research? This class will provide an overview of how ArcGIS software can help you analyze or visualize digital data that has a locational component, as well as discuss starting points for obtaining data. Examples will focus on social science data, but attendees are encouraged to ask questions regarding their own needs and will be welcome to make one-on-one appointments later for more focused instruction.

Introduction to Data Visualization

Data Visualization is a broad field that offers many possibilities for researchers in any discipline. This introduction will begin with an exploration of different categories of visualizations. The workshop will then address a typical workflow for visualization projects, including how to match the visualization type to the needs of a research project and a set of users. Finally, there will be a discussion of stylistic and formatting considerations that may arise during publication of visualizations.

Introduction to Google Refine

Google Refine is a tool for working with messy data. It allows you to detect and fix inconsistencies in your data, transform your data from one structure to another, and provides a simple way to understand patterns in your data. If you've ever faced the task of trying to harmonize names, ISBNs, or titles in a spreadsheet, Refine provides an appealing way of dealing with these common challenges. In this hands-on class, we'll explore how Refine can help with common data cleaning challenges.

Introduction to Tableau Public (Class materials)

Tableau Public is a free service that allows researchers and students to create quick and interactive visualizations of their research data. This workshop will focus on using Tableau Public to create data visualizations, starting with an overview of the structure of the program and the terminology used and proceeding through a sample data visualization project. It will also cover designing a dashboard with multiple visualizations, adding interactivity and publishing to the Tableau Public web server.

Introduction to Text Analysis

Many research projects involve textual data, and computational advances now provide the means to engage in various types of automated text analysis that can enhance these projects. Understanding what analysis techniques are available and where they can appropriately be applied is an important first step to beginning a text analysis project.

This hands-on approach to text analysis will give a quick overview of small- and large-scale text-based projects before addressing strategies for organizing and conducting text analysis projects. Tools for data collection, cleaning and eventual analysis will be introduced and demonstrated. The workshop will focus on acquiring and preparing text sources for small-scale projects and text-based visualizations, but many of the techniques will be useful for larger projects as well. For this introduction, the focus will primarily be on using web applications and common Desktop programs like Microsoft Word and Excel, instead of programming languages and command line approaches.

MATLAB for Data Processing and Visualization

MATLAB is an integrated technical computing environment that combines numeric computation, advanced graphics and visualization and a high-level programming language. On Tuesday, June 18, OIT, in partnership with Duke University Libraries, will host a one-day course on MATLAB that focuses on using this software for Data Processing and Visualization. The course will cover importing data, organizing data and visualizing data in a hands-on format (See a detailed outline). The course assumes some existing familiarity with MATLAB.

Online Mapping: Fusion Tables/Google Earth/Geocommons (Class materials)

Compare and contrast three products intended for quick geospatial visualization (e.g., a map to embed in a blog or a PowerPoint presentation, or for a poster session) and for some elementary GIS data analysis. (1) Google Earth: emphasis on its features particularly applicable in an academic setting; (2) GeoCommons: both a repository for spatial data as well as an analysis and visualization tool; and (3) Google Fusion Tables: merge datasets, filter and aggregate data and visualize data by creating online maps and graphs.

R Basics

Explore the basics of the R programming language for statistics and graphing in this introductory workshop. The workshop covers the basics of loading, managing, graphing and analyzing data in R.

Research Data Management: What, Why, How?

Did you know that as of January 2011, anyone submitting a grant proposal to NSF must also submit a data management plan, explaining what they will do to appropriately manage, share and preserve data generated from the funded research? NIH, NEH, and others have similar requirements. And did you know that Duke has a policy requiring research records (including digital data) to be kept for at least 5 years, in their original form?

In this presentation, Paolo Mangiafico and Joel Herndon will give an overview of the requirements, talk about what they're trying to accomplish and describe some approaches for meeting requirements. We will ask the audience to share how they do data management now and will talk about planning underway for new services at the university to help with data management.

Top 10 Dos and Don'ts for Charts and Graphs

Simple charts and graphs can be incredibly effective at summarizing data. They are common and thus easier for a wide audience to understand. They are also easy to produce in the tools many people regularly use for other data analysis or project management work. With a few simple tips and tricks, you can avoid common missteps and make sure your charts are clear and easy to understand.

Stata Basics

Stata Basics focuses on the core concepts of using stata. Attendees will learn how to load, manage and analyze data. The workshop will also include a brief introduction to Stata graphics as well. No experience with Stata is required.

New for Fall 2012

Introduction to Data Visualization
Fall 2012

Data Visualization is a broad field that offers many possibilities for researchers in any discipline. This introduction will begin with an exploration of different categories of visualizations. The workshop will then address a typical workflow for visualization projects, including how to match the visualization type to the needs of a research project and a set of users. Finally, there will be a discussion of stylistic and formatting considerations that may arise during publication of visualizations.

Excel Charts
Fall 2012

Data processing and visualization for small projects can easily be accomplished by using Excel and the many chart options it offers. In this workshop, we will outline the types of charts available in Excel and identify the data needs for the major chart types. We will also cover basic data terminology and Excel functions that may be useful for some data transformations.

Historical GIS (Sample Data)
Fall 2012

This class will show some ways that ArcGIS can be used for the analysis and visualization of historical spatial data. Topics discussed will be: sources for GIS layers reflecting the past, georeferencing a scanned historic map, creating new layers from scratch based on known locations of features, editing existing GIS layers to reflect former features and vectorizing a scanned map to create editable features.

Introduction to Text Analysis
Fall 2012

Many research projects involve textual data, and computational advances now provide the means to engage in various types of automated text analysis that can enhance these projects. Understanding what analysis techniques are available and where they can appropriately be applied is an important first step to beginning a text analysis project.

This hands-on approach to text analysis will give a quick overview of small- and large-scale text-based projects before addressing strategies for organizing and conducting text analysis projects. Tools for data collection, parsing and eventual analysis will be introduced and demonstrated. The workshop will focus on acquiring and preparing text sources for small-scale projects and text-based visualizations, but many of the techniques will be useful for larger projects as well. For this introduction, the focus will primarily be on using Graphical User Interface (GUI) tools like Microsoft Excel and Google Refine, instead of programming languages and command line approaches.

Online Mapping: Fusion Tables/Google Earth/Geocommons (Sample Data)
Fall 2012

Compare and contrast three products intended for quick geospatial visualization (e.g., a map to embed in a blog or a PowerPoint presentation, or for a poster session) and for some elementary GIS data analysis. (1) Google Earth: emphasis on its features particularly applicable in an academic setting; (2) GeoCommons: both a repository for spatial data as well as an analysis and visualization tool; and (3) Google Fusion Tables: merge datasets, filter and aggregate data and visualize data by creating online maps and graphs.

New for Spring 2012

GeoCommons (Sample Data)
Spring 2012

GeoCommons serves as an open repository of spatial data and maps. In this workshop, we'll cover how to search for data stored by GeoCommons as well as how to upload your own spatial data to share with others. You can edit, filter and combine your GeoCommons data. GeoCommons also serves as a spatial data visualization tool to build maps and animate your data based on time or space. The visualizations can be shared and embedded in other applications.

Ongoing

Introduction to ArcGIS (Sample Data)
Fall 2012, Spring 2012, Fall 2011, Spring 2011

Do you want to find out how geographic information (GIS) software can aid your research? This class will provide an overview of how ArcGIS software can help you analyze or visualize digital data that has a locational component, as well as discuss starting points for obtaining data. Examples will focus on social science data, but attendees are encouraged to ask questions regarding their own needs and will be welcome to make one-on-one appointments later for more focused instruction.

Data Management Plans: Grants, Strategies and Considerations
Fall 2012, Spring 2012, Fall 2011, Spring 2011

In the last few years granting agencies across the disciplines have increasingly required data management plans as part of a grant proposal that detail strategies to manage, share and preserve research data as part of a funded grant project. NSF, the NIH, the National Endowment for the Humanities and other organizations have similar requirements, and Duke policy requires that research records (including digital data) be kept for at least five years. How should researchers respond? In this presentation, we’ll give an overview of research data management challenges and opportunities and describe some approaches for meeting them. We’ll ask the audience to share how they do data management now, and we’ll talk about planning underway for new services to help with data management at Duke.

Stata Review (Slides and Sample Data)
Fall 2012, Spring 2012, Fall 2011, Spring 2011

A basic overview of using Stata for social science research projects with a focus on common questions and procedures.

Introduction to Tableau Public
Fall 2012, Spring 2012

Tableau Public is a free service that allows researchers and students to create web based visualizations of their research data. The workshop explores how to load your data in tableau, popular visualizations, and the most appropriate uses of the software.

Introduction to Google Refine
Spring 2012, Fall 2011

Google Refine is a tool for working with messy data. It allows you to detect and fix inconsistencies in your data, it transforms your data from one structure to another, and it provides a simple way to understand patterns in your data. If you've ever faced the task of trying to harmonize names, ISBNs or titles in a spreadsheet, Refine provides an appealing way of dealing with these common challenges. In this hands-on class, we'll explore how Refine can help with common data cleaning challenges.

Google Earth Pro
Spring 2012, Fall 2011

Learn about some of the features of Google Earth and Google Earth Pro, with an emphasis on those features particularly applicable in an academic setting. Special attention will be given to GIS capabilities and comparison with ArcGIS.

Fall 2011

Google Fusion Tables
Fall 2011

Introduction to the features of Google Fusion Tables — which include merging datasets, filtering and aggregating data and visualizing data by creating online maps and graphs. For certain tasks, it can serve as an alternative to using statistical software such as Stata or GIS software such as ArcGIS.

Working with Stata
Fall 2011

A workshop exploring basic data management and analysis using Stata. This workshop is aimed at researchers new to Stata or seeking a refresher on Stata basics.

Fall 2010

Adding Your Own Data to GIS Layers (Joins and Spatial Joins in ArcGIS)
Fall 2010

We'll look at ways of adding variables to a layer's attribute table in ArcGIS (the spreadsheet data associated with the layer's features). These include joining your own data based on common attribute values as well as adding the attributes of another layer based on spatial location. We'll also touch on geo-referencing scanned maps or digital images to turn them into GIS layers, so that other layers will properly overlay.

Elementary Editing of Layers and Features
Fall 2010

A discussion of techniques in ArcGIS to make layers smaller (clipping, selecting), combining layers (the merge and append tools) and combining features within the same layer (dissolve tool and the merge editing function).

Keeping Your Layers in Line: Projections, Coordinates and Datums in GIS
Fall 2010

Projections and coordinate systems are one of the most frequent stumbling blocks when trying to overlay GIS layers from different sources, to do proximity analysis or to create attractive maps. This class will provide an overview of what these terms mean and how to deal with some common problems, will focus on ArcGIS software and touching on Google Earth and will use example data from sources such as the U.S. Census Bureau.

Tell Me if I am Close: Measure, Nearness and Proximity Analysis in GIS
Fall 2010

Focusing on ArcGIS software, this session will give an overview of some of the proximity tools — such as Near, Point Distance and Buffer and take a look at some of the other measurement calculation techniques in the program.

Where Am I? ... Adding Address Data and Plotting Geographic Coordinate Data to GIS Maps
Fall 2010

If you've got data that includes addresses, we'll look at how to plot the locations of your data points in Google Earth and in ArcGIS. We'll do the same for data that includes X/Y coordinates, such as longitude and latitude information. 

Historical GIS

This class will show some ways that ArcGIS can be used for the analysis and visualization of historical spatial data. Topics discussed will be: sources for GIS layers reflecting the past, georeferencing a scanned historic map, creating new layers from scratch based on known locations of features, editing existing GIS layers to reflect former features and vectorizing a scanned map to create editable features.