UBDC Summer Training 2017: Using R - Mapping Spatial Data

The Urban Big Data Centre (UBDC) is a research centre and national data service based at the University of Glasgow. We promote the use of big data and innovative research methods to improve social, economic and environmental well-being in cities.UBDC has been jointly funded by the Economic and Social Research Council (ESRC), which is part of UK Research and Innovation (UKRI), and the University of Glasgow since 2014.

Urban Big Data Centre

The <A HREF="http://ubdc.ac.uk/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Urban Big Data Centre</A> at the University of Glasgow is pleased to announce the return of our <A HREF="http://ubdc.ac.uk/outreach-plus-training/sasnet/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">SASNet</A> data skills training programme for summer 2017.
The programme will run from 1st August - 6th September offering an opportunity for skills development in key areas of data analytics, methods, and data management. Please visit <A HREF="http://ubdc.ac.uk/outreach-plus-training/sasnet/summer-training-2017" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">http://ubdc.ac.uk/outreach-plus-training/sasnet/summer-training-2017</A> to view the full selection of courses.
Please contact <A HREF="mailto:keith.maynard@glasgow.ac.uk" TARGET="_blank" REL="nofollow noopener noreferrer">keith.maynard@glasgow.ac.uk</A> with any enquiries about the training programme.
 
<HR>
<H2 CLASS="MsoNormal">Using R: Mapping Spatial Data</H2>
Course instructor: <A HREF="http://www.gla.ac.uk/schools/socialpolitical/staff/jingyao/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Jing Yao</A>, UBDC, University of Glasgow
Course duration: 1 day (Tuesday 8th August 2017, 10:00am – 4:30pm)
Course location: Jura teaching lab, Level 4 Annexe, Glasgow University Library
Audience: Social scientists, students, practitioners
Fees:  £35 - For UK registered students     
          £60 - For staff at UK academic institutions, Research Council UK funded researchers, UK public sector             staff and staff at UK registered charity organisations           £100 - For all other participants
Pre-requisite knowledge: <A HREF="https://www.eventbrite.co.uk/e/ubdc-summer-training-2017-introduction-to-r-tickets-35012217485" TARGET="_blank" REL="noopener noreferrer">Introduction to R</A> or equivalent knowledge, and previous experience with GIS and spatial data manipulation is preferred.
Course summary:
Spatial data have been increasingly used in various applications to under spatially explicit problems, such as changes in real estate market, urban segregation and inequities in access to public services (e.g. public transport and public health) and so on. Desktop mapping is a straightforward way and powerful tool to explore spatial phenomena. There are many packages in R supporting visualizing/mapping spatial data. The purpose of this course is to introduce some common functions in R in relation to spatial data visualization and mapping, ranging from basic data manipulation to choropleth mapping. By the end of the course, you will be able to load geographic data into R, manipulate those data and generate various maps. 
Course content:
<UL>
<LI>Read spatial data from a variety of data files</LI>
<LI>Organize spatial data in various spatial data structures</LI>
<LI>Spatial data manipulation: join & merge</LI>
<LI>Classification of attribute/non-spatial data</LI>
<LI>Create maps using vector and raster data</LI>
</UL>
Payment and registration:
Lunch will be provided in the break room adjacent to the IT lab - please specify any dietary or access requirements when registering. 
Payment by card preferred. 
If you are unable to pay by debit or credit card we are able to accept payment by invoice. Please supply the following information by e-mail to <A HREF="mailto:keith.maynard@glasgow.ac.uk" TARGET="_blank" REL="nofollow noopener noreferrer">keith.maynard@glasgow.ac.uk</A> within 14 days of registering on Eventbrite in order to confirm your place on the course:
<UL>
<LI>Contact name for invoice</LI>
<LI>Purchase Order number (note that the supplier is University of Glasgow)</LI>
<LI>Contact e-mail address for payment correspondence</LI>
<LI>Full name of organisation/department</LI>
<LI>VAT registration (if applicable)</LI>
<LI>Currency</LI>
<LI>Address for Invoice to be sent and telephone number</LI>
</UL>
To cancel your place and request a refund, please email <A HREF="mailto:keith.maynard@glasgow.ac.uk" TARGET="_blank" REL="nofollow noopener noreferrer">keith.maynard@glasgow.ac.uk</A>. Please note that a refund of course fees less 10% administrative charge can only be issued if you cancel your place in writing at least 7 days prior to the course after which time fees will be non-refundable. Substitutes can be made at no extra charge up until 5pm on the last working day before the course. 
 
Related 2017 courses:
<A HREF="https://www.eventbrite.co.uk/e/ubdc-summer-training-2017-introduction-to-r-tickets-35012217485" TARGET="_blank" REL="noopener noreferrer">Introduction to R</A>
<A HREF="https://www.eventbrite.co.uk/e/ubdc-summer-training-2017-principles-of-visualising-data-with-r-and-ggplot-tickets-35177400552" TARGET="_blank" REL="noopener noreferrer">Principles of Visualising Data with R and ggplot</A>
<A HREF="https://www.eventbrite.co.uk/e/ubdc-summer-training-2017-getting-started-with-data-management-tickets-35232952710" TARGET="_blank" REL="noopener noreferrer">Getting started with Data Management</A>
<A HREF="https://www.eventbrite.co.uk/e/ubdc-summer-training-2017-introduction-to-areal-data-modelling-using-r-tickets-35177730539" TARGET="_blank" REL="noopener noreferrer">Introduction to Areal Data Modelling using R</A>
<A HREF="https://www.eventbrite.co.uk/e/ubdc-summer-training-2017-measuring-segregation-and-scale-in-r-tickets-35231781206" TARGET="_blank" REL="noopener noreferrer">Measuring Segregation and Scale in R</A>

Jura Teaching Lab, Level 4 Annexe

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UBDC Summer Training 2017: Using R - Mapping Spatial Data

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