Many humanities researchers have some form of geographical information included in their research, such as objects, images, or texts from or about a particular place; narratives about a person’s movement or a place’s change over time; or information about networks of people or organizations. Whether places and spaces are at the heart of your research or are a part of it, mapping can help answer research questions and generate new ones by visualizing your data in new ways. It can help tell a story about place or space. This two-part workshop series will help humanities researchers map their place-based research with ArcGIS.

The Spatial Elements of Textual Analysis
The first workshop will cover the nuts and bolts of getting started mapping with ArcGIS. We will discuss how to extract data from your research, get it ready for analysis, and upload it into ArcGIS. The workshop will help humanities researchers explore and map the spatial elements of their research with ArcGIS.

By the end of this workshop, participants will be able to:

• extract data from their research;
• get their data ready for spatial analysis;
• upload data into ArcGIS Online;
• use some basic mapping techniques with ArcGIS Online.

Software: ArcGIS Online (participants will not need their own computer)

Workshop page (SFU Canvas): GIS workshops page includes workshop descriptions and suggested streams for different disciplines, handouts, slides, and example datasets

Creating Story Maps
The second workshop will cover spatial analysis - the potential applications of your geographic information. We will demonstrate the analytic functions included in ArcGIS and discuss how to create context for your spatial data. We will also introduce Story Maps, an app that helps turn place-based information into narratives with a combination of maps, images, and text. Note: for this workshop, we will assume that you have already attended the first workshop or are comfortable with the material covered there.

By the end of this workshop, participants will be able to:

• create a Story Map;
• extract spatial context from text.

Many humanities researchers have some form of geographical information included in their research, such as objects, images, or texts from or about a particular place; narratives about a person’s movement or a place’s change over time; or information about networks of people or organizations. Whether places and spaces are at the heart of your research or are a part of it, mapping can help answer research questions and generate new ones by visualizing your data in new ways. It can help tell a story about place or space. This two-part workshop series will help humanities researchers map their place-based research with ArcGIS.

The Spatial Elements of Textual Analysis
The first workshop will cover the nuts and bolts of getting started mapping with ArcGIS. We will discuss how to extract data from your research, get it ready for analysis, and upload it into ArcGIS. The workshop will help humanities researchers explore and map the spatial elements of their research with ArcGIS.

Software: ArcGIS Online (participants will not need their own computer)

By the end of this workshop, participants will be able to:

• extract data from their research;
• get their data ready for spatial analysis;
• upload data into ArcGIS Online;
• use some basic mapping techniques with ArcGIS Online.

Creating Story Maps
The second workshop will cover spatial analysis - the potential applications of your geographic information. We will demonstrate the analytic functions included in ArcGIS and discuss how to create context for your spatial data. We will also introduce Story Maps, an app that helps turn place-based information into narratives with a combination of maps, images, and text. Note: for this workshop, we will assume that you have already attended the first workshop or are comfortable with the material covered there.

By the end of this workshop, participants will be able to:

• create a Story Map;
• extract spatial context from text.

Software: ArcGIS Online (participants will not need their own computer)

Workshop page (SFU Canvas): GIS workshops page includes workshop descriptions and suggested streams for different disciplines, handouts, slides, and example datasets

Academic Writing for Graduate Students is a non-credit, 10-week co-curricular course designed for graduate students for whom English is an additional language (EAL).  You will learn how to apply your analytical skills to the discourses of your chosen disciplines and to explore how effective academic writing in Western scholarly tradition is achieved in order to position yourself as junior scholars in your chosen academic communities. 

The course is offered as a collaboration between the Student Learning Commons, Research Commons, and The Center for English Learning, Teaching and Research (CELLTR).

Required textbook (supplied)

Swales, John M., & Feak, Christine B. (2011). Academic Writing for Graduate Students: Essential Tasks and Skills (3rd Edition). Ann Arbor: U of Michigan Press (ISBN: 978-0472-03475-8).

To support for the on-going development of students' academic writing skills, the textbook will be provided free of charge to registered students (for this first course offering only), compliments of the Library and The Centre of English Language Learning, Teaching, and Research (CELLTR).

Spring 2019 term course dates, times, and location:

January 14 - March 27, 2019
Mondays and Wednesdays, 10:30 AM-12:20 PM
Bennett Library, Research Commons, Room 7010

**NOTE: No classes during Reading Break (February 18-24, 2019)

Speaker: Mike Larsen

Mike Larsen is President of the BC Freedom of Information and Privacy Association (FIPA) and Co-Chair of the Criminology Department at Kwantlen Polytechnic University. He teaches courses on socio-legal studies, criminological theory, police accountability, and surveillance and privacy issues, and his research deals with contestations around government secrecy, public accountability, and the right to know.

This presentation will provide you with an overview of findings from the recent data release of the 2017 Aboriginal Peoples Survey (APS) and the Aboriginal Peoples Survey – Nunavut Inuit Supplement (APS-NIS). It will present findings about the labour market experiences of First Nations people living off reserve, Métis, and Inuit from the APS, and findings about Nunavut Inuit and government employment from the APS-NIS.

The APS provides key statistics on labour, education, language, housing and health to inform policy and programming activities aimed at improving the well-being of Aboriginal people.

The OSF is a free, open-source web app that manages research projects at all stages of the research lifecycle. It is used for documentation, file storage, versioning, collaboration, and it connects the various tools researchers currently use. The OSF is produced by the Center for Open Science (COS) and has over 60,000 users across various academic disciplines. Attend the workshop to learn more and explore the OSF.

In this workshop we will focus on collecting data from a online source, follow by cleaning and parsing data for analysis and visualization. We will explore a few libraries in R, including tidyverse, rvest and stringr for data manipulation and analysis.

Requirements

• Intermediate knowledge in R;
• Dependency: R, RStudio,
• Library: tidyverse, rvest, stringr

-------------------

Note: This workshop is organized and facilitated by SciProg. SciProg—short for Scientific Programming Study Group—is dedicated to building a community of SFU researchers who perform computational data analysis as part of their academic work. SciProg promotes skill sharing and collaboration by (1) organizing 60 to 90-minute interactive workshops covering a wide range of software tools, (2) providing Q&A sessions for peer-to-peer assistance and collaboration, and (3) bringing researchers together at social events like Hacky Hours.

This workshop will cover the fundamentals of data visualization design and data storytelling. The topics covered will include perception, reasoning strategies, visual thinking, best practices, and narrative structures. As this is a workshop, a data visualization design activity will also be included at the end.

Requirements

Participants are expected to be at least somewhat familiar with rudimentary exploratory data analysis and statistical thinking. As the exercise is going to be primarily focused on designing data visualizations, participants are encouraged to explore sketching using pen and paper, however the workshop will also accommodate data visualization tools such as Tableau.

-------------------

Note: This workshop is organized and facilitated by SciProg. SciProg—short for Scientific Programming Study Group—is dedicated to building a community of SFU researchers who perform computational data analysis as part of their academic work. SciProg promotes skill sharing and collaboration by (1) organizing 60 to 90-minute interactive workshops covering a wide range of software tools, (2) providing Q&A sessions for peer-to-peer assistance and collaboration, and (3) bringing researchers together at social events like Hacky Hours.

In this workshop participants will go through a brief introduction to time series analysis using ARIMA models in R. This can be applied in business forecasting, business decision-making, stock analysis, medicine, etc.

Requirements

• Basic knowledge of R programming language
• Data analysis practices: parsing, cleaning, analysing data
• Install R, R studio along with libraries TSA.

-------------------

Note: This workshop is organized and facilitated by SciProg. SciProg—short for Scientific Programming Study Group—is dedicated to building a community of SFU researchers who perform computational data analysis as part of their academic work. SciProg promotes skill sharing and collaboration by (1) organizing 60 to 90-minute interactive workshops covering a wide range of software tools, (2) providing Q&A sessions for peer-to-peer assistance and collaboration, and (3) bringing researchers together at social events like Hacky Hours.

This workshop will cover downloading data from online databases using the requests Python library. Participants will also practice parsing obtained information in JSON and CSV format. Data will then be used for analysis and visualization.

Requirements

Intermediate knowledge of Python programming language:

• function definition,
• testing and
• implementation.

Familiarity with pandas dataframes and matplotlib.

-------------------

Note: This workshop is organized and facilitated by SciProg. SciProg—short for Scientific Programming Study Group—is dedicated to building a community of SFU researchers who perform computational data analysis as part of their academic work. SciProg promotes skill sharing and collaboration by (1) organizing 60 to 90-minute interactive workshops covering a wide range of software tools, (2) providing Q&A sessions for peer-to-peer assistance and collaboration, and (3) bringing researchers together at social events like Hacky Hours.

This workshop is intended as a gentle introduction to GIS. No prior GIS or ArcMap experience is needed. The emphasis is on the novice user who is curious about how to use GIS software for their research.

The workshop will discuss different types of geospatial data sources and alternative GIS tools (e.g. SimplyAnalytics) and then provide a hands-on workshop focused on creating a map in ArcMap using 2016 Census data, Vancouver neighbourhood boundaries, homeless shelter and non-market housing point datasets accessible through the City of Vancouver Open Data Catalogue.

The Lab is equipped with QGIS so you don't need to bring a laptop, although you are welcome to bring one if you would prefer.

Many humanities researchers have some form of geographical information included in their research, such as objects, images, or texts from or about a particular place; narratives about a person’s movement or a place’s change over time; or information about networks of people or organizations. Whether places and spaces are at the heart of your research or are a part of it, mapping can help answer research questions and generate new ones by visualizing your data in new ways. It can help tell a story about place or space. This two-part workshop series will help humanities researchers map their place-based research with ArcGIS.

The Spatial Elements of Textual Analysis
The first workshop will cover the nuts and bolts of getting started mapping with ArcGIS. We will discuss how to extract data from your research, get it ready for analysis, and upload it into ArcGIS. The workshop will help humanities researchers explore and map the spatial elements of their research with ArcGIS.

By the end of this workshop, participants will be able to:

• extract data from their research;
• get their data ready for spatial analysis;
• upload data into ArcGIS Online;
• use some basic mapping techniques with ArcGIS Online.

Software: ArcGIS Online (participants will not need their own computer)

Workshop page (SFU Canvas): GIS workshops page includes workshop descriptions and suggested streams for different disciplines, handouts, slides, and example datasets

Creating Story Maps
The second workshop will cover spatial analysis - the potential applications of your geographic information. We will demonstrate the analytic functions included in ArcGIS and discuss how to create context for your spatial data. We will also introduce Story Maps, an app that helps turn place-based information into narratives with a combination of maps, images, and text. Note: for this workshop, we will assume that you have already attended the first workshop or are comfortable with the material covered there.

By the end of this workshop, participants will be able to:

• create a Story Map;
• extract spatial context from text.

Many humanities researchers have some form of geographical information included in their research, such as objects, images, or texts from or about a particular place; narratives about a person’s movement or a place’s change over time; or information about networks of people or organizations. Whether places and spaces are at the heart of your research or are a part of it, mapping can help answer research questions and generate new ones by visualizing your data in new ways. It can help tell a story about place or space. This two-part workshop series will help humanities researchers map their place-based research with ArcGIS.

The Spatial Elements of Textual Analysis
The first workshop will cover the nuts and bolts of getting started mapping with ArcGIS. We will discuss how to extract data from your research, get it ready for analysis, and upload it into ArcGIS. The workshop will help humanities researchers explore and map the spatial elements of their research with ArcGIS.

Software: ArcGIS Online (participants will not need their own computer)

By the end of this workshop, participants will be able to:

• extract data from their research;
• get their data ready for spatial analysis;
• upload data into ArcGIS Online;
• use some basic mapping techniques with ArcGIS Online.

Creating Story Maps
The second workshop will cover spatial analysis - the potential applications of your geographic information. We will demonstrate the analytic functions included in ArcGIS and discuss how to create context for your spatial data. We will also introduce Story Maps, an app that helps turn place-based information into narratives with a combination of maps, images, and text. Note: for this workshop, we will assume that you have already attended the first workshop or are comfortable with the material covered there.

By the end of this workshop, participants will be able to:

• create a Story Map;
• extract spatial context from text.

Software: ArcGIS Online (participants will not need their own computer)

Workshop page (SFU Canvas): GIS workshops page includes workshop descriptions and suggested streams for different disciplines, handouts, slides, and example datasets

The analysis of place-based (or spatial) data requires a basic understanding of how to process the data. For example, what are the routes taken by Anna’s hummingbird (Calypte anna) during winter migration and where do their routes overlap with predator territory? If we have data on the locations of Anna’s hummingbird and their predators, we could process their network (or routes) and then analyze the overlap with predator territory.

Researchers in various disciplines will find this workshop helpful as an introduction to basic geoprocessing tools and workflow automation in ArcGIS. In this workshop, participants will learn to run basic and advanced geoprocessing tools using Python and an automated workflow process tool called Model Builder. During the workshop, participants will:

• explore different data formats that work with ArcGIS;
• use tools to their full extent in ArcMap;
• learn about kernel density analysis;
• automate geoprocessing tools; and
• use Python in IDLE and in ArcMap.

Software requirements:

Participants will need to bring their own computer, running the Windows operating system. This workshop requires the use of ArcGIS Desktop, which is available for download and can be installed on Windows operating systems only. Instructions on installing ArcGIS Desktop and other necessary information will be sent out to participants closer to the workshop date.

Prerequisite:

This workshop assumes prerequisite knowledge of introductory Python. Please contact data-services@sfu.ca if you do not have previous experience with Python as we may be able to recommend other self-guided tutorials.

Take your cartography to the next level by making your maps interactive and online! An interactive map helps your map viewers explore your data with greater detail and control. In this workshop, we’ll use open source software to turn our shapefiles into interactive online maps.

Learning Outcomes: By the end of this workshop you will be able to:

• Export data from QGIS to a web-readable format (GeoJSON)
• Create a Leaflet-based web map
• Customize the styling in that web map

Software: QGIS, Leaflet, HTML & CSS

Core Competencies: web mapping, cartography

Pre-Requisite: Some familiarity with ArcGIS or QGIS, and have used/dabbled in HTML and CSS but may not be fluent in them.

Workshop page (SFU Canvas): GIS workshops page includes workshop descriptions and suggested streams for different disciplines, handouts, slides, and example datasets

Raster data is continuous, pixelated data. For example, aerial photographs, LIDAR data, and digital elevation models store information as raster data. In contrast, vector data is discrete and is stored as geometric objects: points, lines and polygons. The tools available to you, and the kind of analysis you can conduct, with raster data are different than those for vector data. This session will focus on working with raster data in ArcGIS.

By the end of this workshop, participants will be able to:

• distinguish between different types of raster data;
• work with digital elevation models (DEMs);
• explore raster surface data (hill shade, contour, aspect data);
• create and work with mosaic datasets.

Software: ArcGIS Desktop 10.6 (participants will not need their own computer)

Workshop page (SFU Canvas): GIS workshops page includes workshop descriptions and suggested streams for different disciplines, handouts, slides, and example datasets

The lessons in this workshop will cover how to open, work with, and plot vector and raster-format spatial data in R.

Additional topics include:

• working with spatial metadata (extent and coordinate reference systems),
• reprojecting spatial data,
• and working with raster time series data.

By the end of this workshop, participants will be able to:

• import and export raster and vector data from R;
• analyze and edit raster and vector data;
• explore spatio-temporal data in R.

This full-day workshop will follow the Data Carpentries' syllabus.

Prerequisites:

• This lesson assumes you have some knowledge of R. If you've never used R before, or need a refresher, start with the Carpentries' Introduction to R for Geospatial Data lesson.
• This lesson also assumes you have some knowledge of geospatial data types and common file formats. If you have never worked with geospatial data before, or need a refresher, start with the Carpentries' Geospatial Project Organization and Management lesson.

Software requirements:

• Participants will need to bring their own laptops with the most recent version of R and Rstudio installed. For installation instructions and to download the data used in this lesson, see the workshop homepage.

Workshop page (SFU Canvas): GIS workshops page includes workshop descriptions and suggested streams for different disciplines, handouts, slides, and example datasets

Python is a popular language for scientific computing, and great for general-purpose programming as well. In fact, almost everyone who uses Python likes it so much they get upset about having to learn any other programming language.  This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. This workshop uses curricula from Software Carpentry, whose mission is to help researchers get more work done in less time and with less pain by teaching them basic lab skills for scientific computing.  It also provides a good technical basis for the two-day GIS workshop which will follow, which is an introduction to automated geoprocessing using Python to perform analysis with ArcGIS. Given this, you might be able to do St. Patrick one better, and with the power of Python, drive the snakes back into Ireland!

Software requirements:

Participants will need to bring their own computer. Instructions on installing Python and other necessary information will be sent out to participants closer to the workshop date.

Prerequisite:

This workshop is designed for people with no background in Python.

The analysis of place-based (or spatial) data requires a basic understanding of how to process the data. For example, what are the routes taken by Anna’s hummingbird (Calypte anna) during winter migration and where do their routes overlap with predator territory? If we have data on the locations of Anna’s hummingbird and their predators, we could process their network (or routes) and then analyze the overlap with predator territory.

Researchers in various disciplines will find this workshop helpful as an introduction to basic geoprocessing tools and workflow automation in ArcGIS. In this workshop, participants will learn to run basic and advanced geoprocessing tools using Python and an automated workflow process tool called Model Builder. During the workshop, participants will:

• explore different data formats that work with ArcGIS;
• use tools to their full extent in ArcMap;
• learn about kernel density analysis;
• automate geoprocessing tools; and
• use Python in IDLE and in ArcMap.

Software requirements:

Participants will need to bring their own computer, running the Windows operating system. This workshop requires the use of ArcGIS Desktop, which is available for download and can be installed on Windows operating systems only. Instructions on installing ArcGIS Desktop and other necessary information will be sent out to participants closer to the workshop date.

Prerequisite:

This workshop assumes prerequisite knowledge of introductory Python. Please contact data-services@sfu.ca if you do not have previous experience with Python as we may be able to recommend other self-guided tutorials.

This workshop will cover downloading data from online databases using the requests Python library. Participants will also practice parsing obtained information in JSON and CSV format. Data will then be used for analysis and visualization.

Requirements

Intermediate knowledge of Python programming language:

• function definition,
• testing and
• implementation.

Familiarity with pandas dataframes and matplotlib.

-------------------

Note: This workshop is organized and facilitated by SciProg. SciProg—short for Scientific Programming Study Group—is dedicated to building a community of SFU researchers who perform computational data analysis as part of their academic work. SciProg promotes skill sharing and collaboration by (1) organizing 60 to 90-minute interactive workshops covering a wide range of software tools, (2) providing Q&A sessions for peer-to-peer assistance and collaboration, and (3) bringing researchers together at social events like Hacky Hours.

Need help moving forward with your qualitative data analysis? If you’re already comfortable with bringing in documents and coding them, you’re ready to move on to analyzing your material. In this hands-on workshop, Graduate Peer NVivo Facilitators will walk you through visualizations and queries using sample data and may be able to address other topics depending on the needs of the group.

PREREQUISITE:
Before registering for this workshop, you must be familiar with coding in NVivo and/or have already taken the Introduction to NVivo workshop.

NVivo is a qualitative data analysis software program, but what does that mean -- and what does it mean for your research? Find out what NVivo is, when to use it, and how to get started.

In this hands-on introductory workshop, you'll take a tour of the NVivo software environment, using sample data. You’ll be introduced to NVivo’s functions and you’ll leave equipped with the basic info you need to begin working with NVivo. Topics introduced may include importing files and beginning coding.

This workshop is suitable for those with little or no experience using NVivo or other qualitative data analysis software.

This interactive workshop introduces importing and coding of literature review materials and key tools that can be particularly helpful when reviewing literature in your area of research.

Topics covered include:

• introducing NVivo and setting up a project
• working with your information
• identifying themes, topics and ideas and collecting data to support them
• using tools such as text search query, matrix coding query, and Framework Matrix.

What will you achieve from this session? You will have the knowledge to set up a literature review in NVivo, and begin to work with your information. You will also be able to use NVivo to organize your content and begin to identify themes, topics or ideas. It is appropriate for those who have had some experience with NVivo. For more information about NVivo at SFU, please visit NVivo Software for Research Analysis.

Participants should also have some familiarity with citation management software (Zotero, Mendeley, Refworks, EndNote, etc). Zotero will be used during this workshop.

This workshop is designed for non-science students interested in the statistical computing program R. No prior knowledge of R is required. Often data outside of the sciences includes textual data, such as a corpus or series of surveys. In this workshop we’ll learn how to process textual data in R, as well as the basic skills to start analyzing it. Specific topics covered include the R environment (directories, workspace, scripts, and packages), data structures (vector, matrix, data frames, lists), and the beginnings of simple data analysis (built-in statistical packages, elementary statistics, etc.).

Note: Workshop participants will need to bring their own laptops, with R and RStudio installed prior to attending the workshop.

This two day workshop introduces the programming language R.  R is an open-source, widely used, and increasingly popular tool for statistical and data analyses, text mining, geospatial analysis, modelling, and a growing number of other applications. No prior knowledge is required. Students will learn the skills needed to start analyzing their own data.

The topics covered include:

• the R environment (directories, workspace, scripts, and packages),
• simple commands to get you started,
• data structures (vector, matrix, data frames, lists),
• basic data analysis tools (built-in statistical packages, plotting, etc.)

 As time permits, an introduction to functions may also be covered.

Requirements:

• Participants need to bring a laptop with the latest versions of R and RStudio installed.

In this workshop we will focus on collecting data from a online source, follow by cleaning and parsing data for analysis and visualization. We will explore a few libraries in R, including tidyverse, rvest and stringr for data manipulation and analysis.

Requirements

• Intermediate knowledge in R;
• Dependency: R, RStudio,
• Library: tidyverse, rvest, stringr

-------------------

Note: This workshop is organized and facilitated by SciProg. SciProg—short for Scientific Programming Study Group—is dedicated to building a community of SFU researchers who perform computational data analysis as part of their academic work. SciProg promotes skill sharing and collaboration by (1) organizing 60 to 90-minute interactive workshops covering a wide range of software tools, (2) providing Q&A sessions for peer-to-peer assistance and collaboration, and (3) bringing researchers together at social events like Hacky Hours.

The lessons in this workshop will cover how to open, work with, and plot vector and raster-format spatial data in R.

Additional topics include:

• working with spatial metadata (extent and coordinate reference systems),
• reprojecting spatial data,
• and working with raster time series data.

By the end of this workshop, participants will be able to:

• import and export raster and vector data from R;
• analyze and edit raster and vector data;
• explore spatio-temporal data in R.

This full-day workshop will follow the Data Carpentries' syllabus.

Prerequisites:

• This lesson assumes you have some knowledge of R. If you've never used R before, or need a refresher, start with the Carpentries' Introduction to R for Geospatial Data lesson.
• This lesson also assumes you have some knowledge of geospatial data types and common file formats. If you have never worked with geospatial data before, or need a refresher, start with the Carpentries' Geospatial Project Organization and Management lesson.

Software requirements:

• Participants will need to bring their own laptops with the most recent version of R and Rstudio installed. For installation instructions and to download the data used in this lesson, see the workshop homepage.

Workshop page (SFU Canvas): GIS workshops page includes workshop descriptions and suggested streams for different disciplines, handouts, slides, and example datasets

In this workshop participants will go through a brief introduction to time series analysis using ARIMA models in R. This can be applied in business forecasting, business decision-making, stock analysis, medicine, etc.

Requirements

• Basic knowledge of R programming language
• Data analysis practices: parsing, cleaning, analysing data
• Install R, R studio along with libraries TSA.

-------------------

Note: This workshop is organized and facilitated by SciProg. SciProg—short for Scientific Programming Study Group—is dedicated to building a community of SFU researchers who perform computational data analysis as part of their academic work. SciProg promotes skill sharing and collaboration by (1) organizing 60 to 90-minute interactive workshops covering a wide range of software tools, (2) providing Q&A sessions for peer-to-peer assistance and collaboration, and (3) bringing researchers together at social events like Hacky Hours.

This presentation will provide you with an overview of findings from the recent data release of the 2017 Aboriginal Peoples Survey (APS) and the Aboriginal Peoples Survey – Nunavut Inuit Supplement (APS-NIS). It will present findings about the labour market experiences of First Nations people living off reserve, Métis, and Inuit from the APS, and findings about Nunavut Inuit and government employment from the APS-NIS.

The APS provides key statistics on labour, education, language, housing and health to inform policy and programming activities aimed at improving the well-being of Aboriginal people.

This workshop will cover the fundamentals of data visualization design and data storytelling. The topics covered will include perception, reasoning strategies, visual thinking, best practices, and narrative structures. As this is a workshop, a data visualization design activity will also be included at the end.

Requirements

Participants are expected to be at least somewhat familiar with rudimentary exploratory data analysis and statistical thinking. As the exercise is going to be primarily focused on designing data visualizations, participants are encouraged to explore sketching using pen and paper, however the workshop will also accommodate data visualization tools such as Tableau.

-------------------

Note: This workshop is organized and facilitated by SciProg. SciProg—short for Scientific Programming Study Group—is dedicated to building a community of SFU researchers who perform computational data analysis as part of their academic work. SciProg promotes skill sharing and collaboration by (1) organizing 60 to 90-minute interactive workshops covering a wide range of software tools, (2) providing Q&A sessions for peer-to-peer assistance and collaboration, and (3) bringing researchers together at social events like Hacky Hours.

Tableau is a data visualization tool that can help you analyze your data and illustrate the patterns and insights behind them. This interactive workshop will introduce researchers to Tableau Public, a free access version of Tableau.

• connect datasets to your Tableau workbook;
• create a variety of basic chart types (including bar charts, line graphs, and maps);
• use Tableau's built-in analysis features, like reference lines, trend lines and calculated fields; and
• publish and share publication-quality interactive charts and graphs.

Being anxious about academic writing can lead to unhelpful writing habits like avoidance and procrastination. Join us for a discussion on how to make more progress by alleviating writing anxiety!

Believe it or not, it’s not just a long summary of relevant literature. Your literature review serves many purposes including improving your research, focusing your thesis or project, and perhaps most importantly, aptly demonstrating your new-found expertise to your reader while providing a strong first impression for your final written product.

Today’s informal workshop borrows its name from a 2018 University Affairs article with the same title, written by Letitia Henville. Writing for an audience of academics has unique benefits and challenges: these individuals are intelligent, willing to read, and might even have high interest in your topic, but they are also indescribably busy, likely sleep-deprived, and are juggling a multitude of priorities. Join us today for some tips on how to get your message across to readers whose demanding schedules might leave them feeling a bit intoxicated by the time they open your file!

Get to the point. Say more in fewer words. Bring your own strategies for writing concisely and learn some new ones, too. As Dante reminds us: “Let thy words be counted.”

Thesis reBoot is a day-long thesis writing retreat designed for graduate students who have already participated in Thesis Boot Camp.  

Along with a comfortable, quiet working environment, writing and research support, and snacks and lunches, this day-long writing retreat offers students community and motivation in that final push towards the completion of their dissertation or thesis.

More information can be found on the Thesis reBoot page.

Are you getting feedback that your writing is “choppy”? Are you overusing certain transitional words and phrases like “however” or “on the other hand”? Join today’s discussion on how to use transitions thoughtfully so that your reader can comprehend your writing with ease and clarity.

Knowing when to revise, what to look for, and when it's time to proofread will help you edit your own writing more effectively.

Learning how to accurately and skillfully use our own words to describe other scholar’s ideas remains a challenging process for many graduate students, and understandably so. While practicing and improving paraphrasing is guaranteed to level-up your writing, doing so without plagiarizing can and should be an ongoing concern. Come to this discussion to learn more about that foreboding beast "plagiarism," and its lesser known version "patch writing," so that you are better able to both spot it in students' writing and avoid it in your own.

Thesis reBoot is a day-long thesis writing retreat designed for graduate students who have already participated in Thesis Boot Camp.  

Along with a comfortable, quiet working environment, writing and research support, and snacks and lunches, this day-long writing retreat offers students community and motivation in that final push towards the completion of their dissertation or thesis.

More information can be found on the Thesis reBoot page.

This demonstration introduces you to the Thesis Assistance wepage,  Thesis Submission process and the Thesis Template. This workshop will be broken down into four parts:

1. It will begin with an introduction to required copyright permissions from the Copyright Office at SFU. (about 30 minutes)
2. SFU Library's research data specialists will give instruction on how to preserve and, if appropriate, share research data for future uses. (about 15 minutes)
3. The Theses Office will provide an overview of the Thesis Assistant website and go over the overall submission process (including deadlines and supporting documentation). (about 30 to 40 minutes)
4. The technical part of the workshop will follow, where you will be walked through the overall structure of your thesis and the functionality of the thesis template. (about 30 to 40 minutes)

Students are encouraged to bring their own computer and thesis document(s) to work along with the facilitator during the workshop.

Learn how to:

• request copyright permissions (if your thesis includes reproductions of copyright protected images, including  figures, drawings, paintings, photographs, logos, maps, diagrams, tables or charts, and even screen captures on the web, then you might need to request copyright permission)
• write in the MS Word template-based file
• format your text using styles
• bring text in from other documents
• insert figures, images, and auto-numbered captions
• generate the Table of Contents, List of Tables, List of Figures, etc.

If you’ve begun writing, send your document to theses@sfu.ca in advance of the workshop; one might be used in demonstrating the Library’s thesis template. After the session, the formatted document will be returned in which the student can continue his/her work.