Join us for Love Data Week

Love Data Week retro banner

Love Data Week (February 12 - 16, 2024) is an international celebration of all things data, scheduled annually in the week of Valentine’s day. Its aim is to engage community and increase awareness with events that highlight the prominence, value, and appropriate handling of data in our lives and research.

For Love Data Week 2024, libraries at SFU, UBC, UNBC, and UVic have collaborated to offer a series of talks and workshops. All events will be hosted online via Zoom and registration is open to everyone.

Additionally, we invite you to check out the Love Data Week programs delivered by the Inter-university Consortium for Political and Social Research (ICPSR), an international consortium of more than 750 academic institutions (including SFU) and research organizations. ICPSR maintains a data archive of more than 250,000 files of research in the social and behavioral sciences. It hosts 21 specialized collections of data in education, aging, criminal justice, substance abuse, terrorism, and other fields.


Monday, February 12th, 2024

 11:00am - 12:00pm (PST

Ocean Networks Canada’s Suite of Data Tools and Services

From State of the Ocean plots to navigating the depths of Hydrothermal Vents with ROV footage, learn how to access, view, and download ONC’s data through our suite of tools and services. This presentation will focus on Oceans 3.0 and its various sources for data. Data Preview, Plotting Utility, Data Search, and SeaTube v3 will all be discussed and demoed. A curated Jupyter Notebook/DeepNote will also be provided for those who would like some examples of data applications.

Sean Tippett is the Acting Research Data Management Team Lead at Ocean Networks Canada. Having a background in Biology, Sean is a data steward with responsibilities for ONC’s biological data initiatives.

Register

 


Tuesday, February 13th, 2024

 10:00am - 11:00am (PST)

Canadian Housing Data / Statistics Canada

Recent years have seen rising concerns about housing affordability in Canada, spurring policy debates at the federal, provincial and municipal level. In this context, academic researchers have increasingly sought out reliable housing data. The presentation will introduce three sources of housing data at Statistics Canada – The Canadian Housing Statistics Program (CHSP), the Canadian Housing Survey (CHS) and the Census of Population. Presenters will provide an overview of the types of data available from each source and provide examples of how they can be used by scholars and students.  

The CHSP, for its part, provides comprehensive information on residential properties and their owners. It provides granular information on the properties owned and the owners’ characteristics. The CHS, meanwhile, collects information about housing needs and experiences from a sample of Canadian households. In the survey, information is collected on core housing need, dwelling and neighbourhood satisfaction, housing moves, and other aspects of well-being related to housing. Lastly, the Census of Population provides a longer time-series of local and national information on dwellings and people by their demographic, social and economic characteristics.  

These three sources of housing data complement each other and offer comprehensive information on housing in Canada. By using this data, researchers can gain insights into housing trends and the needs and preferences of Canadian residents. 

Josh Gordon is a Senior Analyst with the Canadian Housing Statistics Program (CHSP). In 2023, Josh published two articles for the CHSP, focused on the profile and role of real estate investors. Before joining Statistics Canada, Josh was an assistant professor at the School of Public Policy at Simon Fraser University. His academic research focused on the Canadian housing market and the politics of labor market policy. He received his Ph.D. from the University of Toronto in 2012.  

Jeff Randle began his career at Statistics Canada as a student in the summer of 2006. After completing an undergraduate degree in economics, he continued in the Income Statistics Division as an analyst working on household surveys focusing on income and socioeconomic well-being. In 2014, he joined the housing subject matter unit responsible for the housing content and analysis on the Census of Population and homelessness analytical and data development projects. Jeff now manages the Housing Need Projects section responsible for the Canadian Housing Survey, National Social and Affordable Housing Database, National Housing Strategy program data integration projects, and Homelessness Projects and Partnerships. 

David Heisel is a housing analyst with the Census of Population. David is involved in the data processing, development and publication of the housing content in the Census products. He has a Bachelor of Mathematics from Carleton University.

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 1:00pm - 3:00pm (PST)

Introduction to Machine Learning: Regression Models (UBC)

This workshop focuses on regression models to provide participants with a foundational understanding of machine learning concepts, techniques, and tools used for linear and nonlinear regression. Through a combination of lectures and hands-on exercises, participants will gain practical experience with regression algorithms, one Tof the most popular machine-learning techniques. The workshop begins with an overview of regression, exploring its various types and applications and continues with training regression models, interpreting the results, and making predictions using real-world datasets. Additionally, participants will gain insights into advanced topics such as regularization and feature selection. By the end of this workshop, you will have a solid understanding of regression models and be familiar with popular Python libraries and tools to implement them.

In this workshop, we will use cloud-based platforms, so you don’t need to have Python installed. Please make sure that you have a Google Colaboratory (https://colab.research.google.com/) account. This workshop will involve hands-on exercises that require the use of programming tools and libraries commonly used in machine learning, such as Python and Scikit-learn. As such, prior familiarity with Python programming is recommended for participants to fully benefit from the practical component of the workshop.

Register

 


Wednesday, February 14th, 2024

 10:00am - 11:00am (PST)

History buffs: Learn how to find Statistics Canada information pre-1981 / Elizabeth Nash (Statistics Canada)

The Statistics Canada Library is happy to invite you to a virtual presentation that will highlight how you can access historic Statistics Canada data. In this presentation, you’ll learn:

  • How to use the Statistics Canada Library’s catalogue
  • How to search the historical catalogue to find the information you need
  • How to navigate the Historical Resources InfoGuide

Please note that this presentation will help you find published data, not raw data. In addition, this session is geared towards beginners or those who would like a refresher with published non-census data.

Elizabeth Nash is a librarian at the Statistics Canada Library in Ottawa, Ontario. She graduated from The University of Western Ontario with a bachelor's degree in English, and from McGill University with a master's degree in Information Studies. She enjoys getting lost in the stacks and discovering the stories that historic data can tell

.Register

 

  2:00pm - 3:30pm (PST)

Pandas DataFrames in Jupyter Notebooks / Cairo Sanders (UVic)

Pandas is an open-source Python library for data structuring and analysis. Its capabilities are flexible and can be integrated with other Python Libraries. It is also efficient for automating repetitive processes.

Jupyter Notebook is a web-based environment for interactive computing that helps researchers and scientists easily view programming output. In contrast to traditional programming environments, users can view output one section at a time, which can help for breaking down tasks and debugging. There is no need for console knowledge.

This workshop uses the https://syzygy.ca/ Jupyter Notebook software because it is free for many Canadian universities and avoids the hassle of downloading new software. This workshop is primarily hands-on practice with Pandas DataFrames in order to learn to use key features of the software.

Cairo Sanders is UVic Libraries Data Analyst supporting the Libraries with organizational analysis, including data collection and reporting.

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Thursday, February 15, 2024

  10:00am - 11:00am (PST) 

SOMAR: Exploring the Innovations of the Social Media Archive at ICPSR, featuring Meta Content Library API (ICPSR

Explore the groundbreaking innovations of the Social Media Archive (SOMAR) at socialmediaarchive.org. Discover how SOMAR revolutionizes the preservation and exploration of the vast digital landscapes of social media data. This webinar will delve into the importance of archiving social media data and the invaluable insights it offers future generations.

You will meet the SOMAR staff who will navigate the key features and functionalities of SOMAR, showcase the practical applications, and discuss its advanced capabilities in organizing and preserving the ever-evolving world of social media data. 

Register

 

 10:00am - 11:30am (PST)

Data Visualization with ggplot2 / Siobhan Schenk (UBC)

This workshop will introduce concepts and tools for visualizing data in R, with emphasis on the ggplot2 package. Participants are expected to already be familiar with R and the RStudio environment. The workshop is one hour, followed by an optional 30 minute practice period to reinforce what you learned or consult with the instructors. 

 Workshop materials are available.

Siobhan Schenk is a Ph.D. candidate in Botany at UBC. She studies how bacteria influence the health of kelps in stressful abiotic conditions and on kelp farms. Siobhan is a member of the Quantitative Data Analysis team in the UBC Library Research Commons and offers workshops and consults on statistical analysis and data visualization through R, python, and SPSS.

Register

 

 1:00pm - 3:00pm (PST)

Designing Web Maps with Mapbox / Lily Crandall-Oral (UBC)

This workshop is intended for anyone with a basic understanding of web mapping who wishes to expand their skillset and design more customizable maps. There are 3 main sections: an introduction to Mapbox and its products, a guided developer environment set-up, and a hands-on portion where we will modify given code to design an interactive map powered by Mapbox and Leaflet.

Lily Crandall-Oral is a geographer and cartographer passionate about integrating art and science through mapping. As member of the Geospatial Information and Technology team in the UBC Library Research Commons, they offer consults and lead workshops on map making and spatial analysis using geographic information systems (GIS).

Register

 


Friday, February 16, 2024

  12:00pm - 1:00pm (PST)

SFU's Big Data Hub Presents Data Visionaries Series: Visualizing Data

With the increasing volume of data generated and used by organizations, discover how Data Visualization can guide you through some of the intricacies of decision-making. Join us for an engaging session with guest speaker Vladimir Karakusevic from Boeing as we explore the transformative world of Data Visualization and its pivotal role in reshaping the way businesses operate, innovate, and cater to customer needs. During this session, you will also learn from a practical application as we walk through a live Jupyter Notebook workbook demonstration, offering you a firsthand experience on transforming complex data into actionable insights

Vladimir Karakusevic is an Enterprise Technical Fellow with the Boeing Company.

Register


 

Love Data Week events around the world

Want more? The International Consortium for Political and Social Research (ICPSR) is compiling a list of Love Data Week events from around the world.

Please visit ICPSR's Love Data Week page to see event details and registration.


 

Date(s)
February 12 - 16
Location
Online
Sponsors
SFU Library, UBC Library, UNBC Library, UVic Library
Contact for further information
data-services@sfu.ca