Application Programming Interfaces (APIs) are parts of a website’s code made available to the public, which can be used to query data in controlled amounts. Web scraping is described as the act of pulling down (usually large) amounts of data from a website. Though both are increasingly used as tools in scholarship, the ethics regarding the use of either of these tools is hotly debated: How should we store data that contains potentially sensitive and/or identifying information? Should scholars be beholden to a business’s terms and conditions, even if that corporation is a multi-billion dollar company? APIs are legally sound, but what kinds of data should be scraped?

This tutorial will provide attendees with a basic understanding of APIs and web scraping, as well as the tumultuous history of using both in scholarship. Attendees will then be encouraged to participate in critical discussion surrounding the ethics of each for scholarly use.

Notes:

• This workshop is geared towards participants who want to use APIs and web scraping in their own research, or who have used these methods and are interested in discussing their ethical considerations. Therefore, prior knowledge of APIs or web scraping is useful but not required.
• Please bring a laptop.

Using the Tracery story-grammar generation tool, participants will learn how to turn simple JSON lists into full-fledged Twitter bots like @Gastwon, (https://twitter.com/gastwon) @TaySEliot (https://twitter.com/tayseliot) or even @SoftLandscapes. (https://twitter.com/softlandscapes). No programming experience is necessary.

Please bring a fully charged laptop.

This seminar-style workshop series is designed for graduate students for whom English is an additional language (EAL). The workshop focuses on writing tasks that may be required in the earlier stages of a graduate program.  You will learn how to apply your analytical skills to the discourses of your chosen disciplines and explore how effective academic writing in Western scholarly tradition is achieved in order to position yourself as junior scholars in your chosen academic communities. Students will complete several reading, writing, and grammar tasks, all of which will be used to provide personalized feedback.

Required textbook:

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).

Do you work with research data in spreadsheets? If so, this workshop is designed for you! We’ll be covering the best practices for Data Organization in Spreadsheets, according to Data Carpentry. Then we’ll look at formatting values, fixing dates, merging/splitting columns, and more. By the end, you’ll be prepared to take your spreadsheets to the next level.

Protect your research data by following strong security practices. This workshop will cover topics including:

• cloud storage,
• full disk encryption,
• threat modelling,
• communication and file sharing,
• account security,
• two-factor authentication (2FA), and
• digital preservation.

Learn how to keep data secure with SFU resources.

Then we move to Python, a popular language for scientific computing and great for general-purpose programming as well.  This workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. This workshop is offered by The Carpentries, whose mission is to help scientists and engineers get more research done in less time and with less pain by teaching them basic lab skills for scientific computing. 

Participants will need to bring their own computer/laptop. Please see note above for instructions for installing Python and other necessary files.

Want to make your research and writing more efficient? Hate the last minute rush of trying to create a correctly formatted bibliography? This workshop is for you! We will introduce Zotero, a citation management tool that can help you import, organize, share, and manage your citations and documents, as well as create correctly formatted in-text citations and bibliographies in almost any style -- in seconds.

Bring your laptop: this interactive workshop will cover registration, installation, and everything that you need to know to get up and running with Zotero.

Have questions about using citation management software, like Zotero or Mendeley? We can help! Our citation management experts can introduce you to citation management tools, answer questions, and demonstrate features and techniques. Bring your laptop and your questions!

• Which areas in Ontario are susceptible to drought? Which areas are susceptible to longer periods of drought and which to shorter periods?
• What is the travel route of the Anna's hummingbird (Calypte anna)? Does it pass close to areas where predators are present, specifically those which prey on eggs?
• Are neighbourhoods with low socioeconomic status spatially correlated to high morbidity rates?

Many of these questions ask about the spatial relationship between two or more phenomena. This workshop is an introduction to spatial thinking and the use of Geographic Information Systems (GIS). This workshop assumes attendees have no previous experience with GIS.

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

• think spatially about their research;
• understand the elements of GIS;
• use a leading industry software (ArcGIS);
• create simple maps using geospatial data;
• look for and find geospatial data and resources.

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

Georeferencing is the process of connecting images (e.g. aerial photographs, scanned historical maps, satellite images) with their geographic locations in a coordinate system so that the images can be used as spatial layers in GIS software. This workshop will teach you the skills needed to georeference images in ArcGIS so that you can view, make queries, and analyze your image-based data with other geographic data.

Software

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

Learning outcomes

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

• choose an appropriate projection for georeferencing;
• georeference an image without coordinates;
• create vector data on the image for further analysis.

Core competencies

• georeferencing, projections, vector digitizing

This workshop will cover two very practical skill areas for ArcGIS users:

• finding Canadian Census data that is accessible to university researchers,
• and mapping it using ArcGIS software.

This workshop will guide you through tips for mapping large amounts of census data quickly and for working with spatial patterns and relationships among census variables.

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

• find and choose Census data required for their research;
• extract relevant Census data from Census files;
• understand the census spatial units;
• map census data using census spatial units.

Software: ArcGIS Online, ArcGIS Desktop (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. You can attend the Python workshop on Feb 8 & 9, or if you can't make it to this Python workshop, you may learn on your own the first 5 modules of Software Carpentry Programming with Python, which should sufficiently prepare you for this series of workshop.  Please contact data-services@sfu.ca if you have any questions.

Researchers often have to analyze many individual datasets separately using the same process. For example, maybe you need to convert 100 CSV files into shapefiles and create buffers with increasing increments around them, in each one. Sometimes even working spatial analysts don’t have access to premade tools that can run this analysis; in which case, they need to create the tool themselves to automate most of this processing.

Almost all uses of GIS involve a repetition of work, and this creates the need for methods to automate, document, and share multiple-step procedures known as workflows. Geoprocessing allows you to automate your GIS tasks and perform spatial analysis and modeling. This workshop will guide participants in the creation of custom geoprocessing tools in ArcGIS using Python. At the end of the workshop, participants will be able to:

• create a geoprocessing workflow in ArcGIS Model Builder;
• create a geoprocessing workflow using Python code;
• run basic geoprocessing and shapefile editing tools using Python code; and
• code a single tool that can be used in ArcMap to run the entire workflow.

Software requirements:

Participants will need to bring their own computer, running the Windows operating system. This workshop requires the use of ArcGIS Desktop and Python. ArcGIS Desktop 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 and Geoprocessing in ArcGIS  materials or their equivalent. You can attend the Python workshop on Feb 8 & 9, or if you can't make it to this Python workshop, you may learn on your own the first 5 modules of Software Carpentry Programming with Python, which should sufficiently prepare you for this series of workshop.  Please contact data-services@sfu.ca if you have any questions.

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. This full-day workshop will be guided through parts of the Data Carpentries' syllabus, parts from Robin Lovelace's Geocomputation with R workbook, and parts from the Rspatial.org workbooks.

This lesson assumes you have some knowledge of R. If you have never used R before, or need a refresher, you could take one of the R workshops offered through the Research Commons or you could 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

• The most recent version of R and RStudio (participants will need their own computer).
• For installation instructions and to download the data used in this lesson, see the workshop homepage. 
• Make sure you have set up a RStudio project for this lesson, as described in the setup instructions.
• If you don’t have an RStudio project, you will need to manually set the working directory with setwd([your-directory-name]) so R can find the data files to load.

Learning outcomes

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.

Core competencies
spatial analysis, aligning data, plotting data, publication quality graphics

Vector data is discrete data stored in points, lines and polygons. The tools at your disposal and the kind of analysis you can conduct with this type of data is different than those for raster data. This workshop will deepen your knowledge of attribute tables that accompany vector data. You will learn to add new data in an existing table, import data from an Excel worksheet, join two tables together, convert a list of X-Y coordinates to a shapefile, and create simple SQL-queries.

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

• edit and add information to an attribute table;
• import Excel tables and X-Y coordinates into ArcMap;
• formulate queries;
• join data from two separate sources;
• and, explore spatial patterns in data.

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

Making a map isn’t difficult, but making a visually appealing map is much harder. A bad map is difficult to understand, and makes viewers more likely to ignore it entirely. A beautiful map will not only better communicate your ideas, but can transform an average poster, paper, or presentation into a great one.

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

• Import data into QGIS (from ArcGIS)
• Find and use custom basemaps
• Understand the elements of good cartographic design
• Use QGIS map layouts to make maps faster and more consistently
• Export maps for publication

Software: QGIS (Windows version) - installed on Lab computers

Core Competencies: cartography, map layout, basemaps

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

GIS software doesn’t have to be expensive! QGIS is a free, open source GIS platform with powerful tools and wide variety of plugins. Learn how to use the basic tools in QGIS for your spatial projects. 

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

• Import data to and export data from QGIS
• Edit data within QGIS
• Do basic vector analysis in QGIS
• Do basic raster analysis in QGIS
• Export simple maps using the layout manager

Software: QGIS is installed on the computers in the lab where this workshop is delivered. However, we encourage you to bring your own laptop with QGIS installed because you may need to download plugins and it is best you can run QGIS on an environment you are comfortable with. QGIS runs on Linux, Windows and Macs. To download QGIS, please visit https://qgis.org/en/site/forusers/download.html

Core Competencies: vector analysis, raster analysis, data management

Pre-Requisite: Basic knowledge of GIS and/or some familiarity with ArcGIS. Otherwise, we suggest taking Intro to Spatial Thinking and ArcGIS workshop.

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

ArcGIS Pro is Esri's newest desktop software. This workshop will introduce ArcGIS Pro and show users how they can move their files from ArcMap to ArcGIS Pro. Along the way we will also explore the differences between the two software and new tools users may not have in ArcMap.

Software
ArcGIS Pro, ArcMap 10.7 (this workshop takes place in the computer lab so participants will not need their own computer)

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

• create map documents in ArcGIS Pro;
• load and analyze data in ArcGIS Pro;
• understand the pros and cons of using ArcGIS Pro (as of the date of the workshop)

Then we move to Python, a popular language for scientific computing and great for general-purpose programming as well.  This workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. This workshop is offered by The Carpentries, whose mission is to help scientists and engineers get more research done in less time and with less pain by teaching them basic lab skills for scientific computing. 

Participants will need to bring their own computer/laptop. Please see note above for instructions for installing Python and other necessary files.

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. You can attend the Python workshop on Feb 8 & 9, or if you can't make it to this Python workshop, you may learn on your own the first 5 modules of Software Carpentry Programming with Python, which should sufficiently prepare you for this series of workshop.  Please contact data-services@sfu.ca if you have any questions.

Researchers often have to analyze many individual datasets separately using the same process. For example, maybe you need to convert 100 CSV files into shapefiles and create buffers with increasing increments around them, in each one. Sometimes even working spatial analysts don’t have access to premade tools that can run this analysis; in which case, they need to create the tool themselves to automate most of this processing.

Almost all uses of GIS involve a repetition of work, and this creates the need for methods to automate, document, and share multiple-step procedures known as workflows. Geoprocessing allows you to automate your GIS tasks and perform spatial analysis and modeling. This workshop will guide participants in the creation of custom geoprocessing tools in ArcGIS using Python. At the end of the workshop, participants will be able to:

• create a geoprocessing workflow in ArcGIS Model Builder;
• create a geoprocessing workflow using Python code;
• run basic geoprocessing and shapefile editing tools using Python code; and
• code a single tool that can be used in ArcMap to run the entire workflow.

Software requirements:

Participants will need to bring their own computer, running the Windows operating system. This workshop requires the use of ArcGIS Desktop and Python. ArcGIS Desktop 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 and Geoprocessing in ArcGIS  materials or their equivalent. You can attend the Python workshop on Feb 8 & 9, or if you can't make it to this Python workshop, you may learn on your own the first 5 modules of Software Carpentry Programming with Python, which should sufficiently prepare you for this series of workshop.  Please contact data-services@sfu.ca if you have any questions.

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.

Bring your laptop and your NVivo questions to this drop-in lab session! Our facilitators are experienced NVivo users, and can help orient researchers to using NVivo software for organizing, coding, and analyzing textual, audiovisual, social media, and other data. They can also support other uses of NVivo, such as organizing literature reviews and handling survey data.

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.

Notes:
1. This workshop is for NVivo for Mac. The Windows interface is significantly different. Please check here for NVivo for Windows workshops being offered.
2. This workshop takes place in a Mac lab, so you don't need to bring your own laptop. However, if you wish to use your Mac laptop, please make sure you preload it  with the latest version of NVivo. You can download NVivo and the license key with your SFU computing ID by using the self-serve download link here. If you are unable to get past the authentication page, then please email nvivo-rc@sfu.ca.

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.

Note: You will need to bring your own Mac laptop, installed with the latest version of NVivo for Mac.

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.

Although R is known for its statistical computing and graphical capabilities, it also provides many powerful tools for handling, processing, and analyzing strings and text data. This workshop gives an introduction to handling strings using both Base R and the stringr package, and an introduction to regular expressions in R.

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

• use common operations and functions to manipulate strings
• learn what regular expressions are and how to use them in R
• apply these concepts to perform text analysis in R

Note:

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.

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. This full-day workshop will be guided through parts of the Data Carpentries' syllabus, parts from Robin Lovelace's Geocomputation with R workbook, and parts from the Rspatial.org workbooks.

This lesson assumes you have some knowledge of R. If you have never used R before, or need a refresher, you could take one of the R workshops offered through the Research Commons or you could 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

• The most recent version of R and RStudio (participants will need their own computer).
• For installation instructions and to download the data used in this lesson, see the workshop homepage. 
• Make sure you have set up a RStudio project for this lesson, as described in the setup instructions.
• If you don’t have an RStudio project, you will need to manually set the working directory with setwd([your-directory-name]) so R can find the data files to load.

Learning outcomes

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.

Core competencies
spatial analysis, aligning data, plotting data, publication quality graphics

Growing amount of data is available over the web. However, this data is usually presented in an unstructured HTML format which poses a challenge to researchers who want to automatically capture the data and convert it into a form appropriate for analysis. Web scraping is a computational method that offers means to meet such challenges. In this workshop you will learn how to scrape unstructured web pages using rvest R package and prepare the captured data for analysis. You will gain some hands-on experience working on a few small projects that underlie common scraping strategies/issues. The last project will include scraping of multiple web pages.

Prerequisites: Functional knowledge of commonly used base R commands (for an overview see https://www.rstudio.com/wp-content/uploads/2016/05/base-r.pdf).

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

Text mining techniques can be applied to various data sources (e.g., newspaper articles, emails, online discussion posts, etc.) to efficiently extract useful data for different research purposes. For example, health science researchers may be interested in investigating a frequency of a particular disease name mentioned in a large set of newspaper articles. Educational researchers, on the other side, may wish to extract and categorize students' opinions from discussion forum in a high enrollment course. R offers a comprehensive set of functionalities for text mining. In this workshop, you will learn how to implement basic methods for preprocessing textual data, metadata management, a creation of term-document matrices over the collection of textual documents, sentiment analysis, text tokenization, word relationship extraction and text visualization.

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

Are you interested in publishing your academic work, extending the reach of your research, and developing your online presence? The day includes three workshops which will give you everything you need to prepare to publish and share the word about your research.

Preparing to Publish
This workshop will focus on navigating the peer review process and will also touch on the topics of open access, working with an editor, and co-authorship.  It will include a discussion of copyright transfer agreements and licenses and provide insight into publishing venues for assuring your research has the best possible visibility, accessibility, and impact.

Who is looking at your research and how can you measure it?
Find out more about research impact – what it is, how to measure it and how to leverage it.

Raising Your Online Research Profile
This workshop will look at the big picture and context for developing your online academic narrative: why do you want a research profile? How do you get your work out there? The workshop will provide a hands-on introduction to tools for privacy, social media, and auditing and building your online academic portfolio.

Application Programming Interfaces (APIs) are parts of a website’s code made available to the public, which can be used to query data in controlled amounts. Web scraping is described as the act of pulling down (usually large) amounts of data from a website. Though both are increasingly used as tools in scholarship, the ethics regarding the use of either of these tools is hotly debated: How should we store data that contains potentially sensitive and/or identifying information? Should scholars be beholden to a business’s terms and conditions, even if that corporation is a multi-billion dollar company? APIs are legally sound, but what kinds of data should be scraped?

This tutorial will provide attendees with a basic understanding of APIs and web scraping, as well as the tumultuous history of using both in scholarship. Attendees will then be encouraged to participate in critical discussion surrounding the ethics of each for scholarly use.

Notes:

• This workshop is geared towards participants who want to use APIs and web scraping in their own research, or who have used these methods and are interested in discussing their ethical considerations. Therefore, prior knowledge of APIs or web scraping is useful but not required.
• Please bring a laptop.

This interactive workshop focuses on the literature review and literature search. At this session you will learn:

• conventions of literature reviews,
• search strategies,
• advanced features of research databases,
• and tips to further develop effective and efficient research skills.

Academic writing can be more than boring readers and emulating stuffy styles. In fact, expressing complex ideas in your own voice can be one of the best ways to make your work stand out. Join us for a conversation on conformity, creativity, and originality and begin your journey toward discovering your academic voice.

Have you ever received feedback that your writing seems “choppy”? Are you having concerns about how to order your ideas or how to transition from one section to the next? This workshop is focused on developing some strategies for producing cohesive academic writing that “flows.”

Need to write an abstract? Wondering how you can put all of the crucial information about your research into just one paragraph? Join us for this workshop, and after applying some of our drafting, revising, and editing strategies, you can walk out with a concise, informative, attention-grabbing draft! Helpful for students writing abstracts for completed or in-progress research, and for those developing abstracts to submit as part of symposium or conference applications. Note: This workshop is for graduate students and undergraduates applying for the Undergraduate Research Symposium (UGRS).

A concept map is a tool that can be used to support learning and writing through visualizing the relationships between concepts. Concept mapping (or mind mapping) at any stage of the writing process can help clarify how ideas, terminology, themes, etc. relate to each other, to your research questions, and/or the main points of your project. Concept mapping is for everyone, but can be especially helpful for those trying to manage a longer writing project for the first time (like a thesis), those who rebel against outlining, and those who want to benefit from deconstructing (or reconstructing) the linear form that writing ultimately must take. For many, concept mapping is a writing process game-changer.

Strategies for using lay language will help you convey technical and advanced ideas in ways that are more effective than “dumbing it down.” You may be preparing a grant or fellowship proposal, writing for online purposes or fine tuning your “job talk”— all of which require you to translate your work and research to persons outside of your core field of study.

You might already be aware of “free writing” as an exercise that can aid the drafting process, but does this task ever seem too free to help you produce quality text that you can use in academic writing? Join this workshop to practice some helpful guidelines for free writing. We’ll provide just enough structure so that your “free” writing doesn’t instead simply feel “lost.”

A concept map is a tool that can be used to support learning and writing through visualizing the relationships between concepts. Concept mapping (or mind mapping) at any stage of the writing process can help clarify how ideas, terminology, themes, etc. relate to each other, to your research questions, and/or the main points of your project. Concept mapping is for everyone, but can be especially helpful for those trying to manage a longer writing project for the first time (like a thesis), those who rebel against outlining, and those who want to benefit from deconstructing (or reconstructing) the linear form that writing ultimately must take. For many, concept mapping is a writing process game-changer.

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!

After you have defended, the final step for graduation eligibility is submitting your thesis, project, or extended essay(s) to the Library. This workshop will walk you through the thesis submission process.

Note: A good time to take this workshop is sometime during the semester that you’ll be defending or sometime after you know when your defence date is.

You will learn:

1. How to log into the Thesis Registration System (TRS)

2. What required documents you need to upload to the TRS

3. What “if applicable” documents you need to upload to the TRS

4. What happens after you have submitted

Prerequisite: This workshop assumes that you have taken the Thesis Word Template: The Basics workshop or equivalent

This workshop covers more advanced features of the Library’s MS Word thesis template. The workshop can help with fixing issues with your thesis or addressing any personal preferences you might have (that are allowable within the template). Topics covered may include, but are not limited to:

• how to fix margins
• how to fix page numbering errors
• how to properly include terms in the List of Acronyms and Glossary sections
• how to create a landscape page to better fit your figure or table
• how insert an 11x17 page to fit larger tables or figures
• how to crop your figures in Word
• tips on table design and tweaking tables to fit your data without making your text smaller
• how to see all of your footnotes at once

If you have any issues with the thesis Word template that you want to discuss, please bring them to the workshop.

The SFU Library thesis template is a Microsoft Word file designed to assist students in preparing theses, projects, and extended essay(s) in accordance with formatting standards and requirements for submission to the Library.

There are 3 parts to this workshop:

1. SFU Library's research data specialists will give instruction on how to store, preserve (archive) and, if appropriate, share research data for future uses. (15 to 20 minutes)

2. SFU Copyright Office will briefly explain copyright law as it relates to reproducing copyright protected material in your thesis and other published works, and explain how to request permission from copyright holders when required. (30 to 40 minutes)

3. For the remainder of the time, the Theses Office will walk through the overall structure of your thesis and demonstrate the functionality of the thesis template. You will learn how to:

• download the thesis template (a Microsoft Word file) and set up some defaults
• format your text using styles (ie. block quotes, lists, references, etc.)
• insert figures/images and tables and generate auto-numbered captions
• update the Table of Contents, List of Tables and List of Figures
• bring in text from other documents