Because our tutorials are online, and because we want to reach a broader audience at NYU, we have also listed a handful of offerings at times that are well-suited for those at the NYU Abu Dhabi and NYU Shanghai campuses. The Fall 2020 NYU Go Local list of featured tutorials is as follows:
- Data Visualization with Tableau – September 15, 9pm in New York or September 16, 9am in Shanghai
- Getting Started with Python Pandas – September 16, 9pm in New York or September 17, 9am in Shanghai
- Survey Design with Qualtrics – October 6, 9pm in New York or October 7, 9am in Shanghai
- Python for Harvesting Data on the Web – October 7, 9pm in New York or October 8, 9am in Shanghai
- Data Cleaning and Management Using Python – November 11, 9pm in New York or November 12, 10am in Shanghai
- Introduction to R – October 14, 8pm in New York or October 15, 8am in Shanghai
- Using RSQLite and Shiny Applications to Solve Business Problems – November 18, 7pm in New York or November 19, 8am in Shanghai
- Extracting Geospatial Data with the OverPass API – October 20, 12am in New York, 8am in Abu Dhabi, and 12pm in Shanghai
- Introduction to QGIS – November 9, 11pm in New York, 8am in Abu Dhabi, 12pm (Nov 10) in Shanghai
These tutorials are available to anyone in the NYU community, regardless of current location. They are not recorded because we want anyone who participates to feel comfortable asking questions, sharing examples, or interacting with us as we work through the software. For any questions about registering for Data Services classes, visit the Data Services homepage or email data.services@nyu.edu
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In order to access this data, go to this record in the Faculty Digital Archive or search within the NYU Libraries catalog. The record contains a text delimited file of the data and a codebook to interpret the variables. There are instructions on how to create a SQL table with the data, but you may also load it in SPSS, Stata, or other advanced quantitative software packages.
For the sake of convenience, and to demonstrate the spatial possibilities for this data, we have created a sample shapefile of all business locations within the borough of Brooklyn. You can access the file within NYU’s Spatial Data Repository.
If you have any questions about accessing or working with this data, don’t hesitate to contact us at Data Services. You can also see similar business data holdings by browsing the Virtual Business Library (VBL).
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Love Data Week (formerly Love Your Data Week) has arrived! This year’s theme is telling stories with data, and in that spirit Data Services will be hosting a series of workshops designed to think about how you can transform your data, code, and research into effective publications. We’ll look at how you can build an online profile that will allow you to persistently link your publications and data to your researcher identity, and look at ways to ensure you get credit for citations of your research. We’ll cover “executable papers” such as those created in Jupyter Notebooks and R Markdown that enable you to dynamically combine code with research findings, and look at ways to quickly move those papers to the web. We’ll also feature a “Love is in the Air!” day-long mapping event on Wednesday. Look for us on Twitter @nyudataservices to follow along with tips and tools, and right here on the Data Dispatch for more telling stories with data posts. See the schedule below for details and links to sign up.
Events at Bobst Library
Tuesday 13: Storytelling with Code & Data, room 743
3-4:30pm: Tools for Storytelling with Data | Register Here
4:30-6pm: Data Journalism with Meredith Broussard, Assist. Prof, NYU Journalism | Register Here
Wednesday 14: Love is in the Air – Let’s Map It! room 743 & 745
Register Here
9-10am: Evolution of GIS and Mapping
10:15-10:45am: Esri GIS Server
10:45-12pm: Spatial Analytics with ‘Insight’
1:15-4pm: GIS in the Field
4-5:30pm: Python for Spatial Analytics
Friday 16: Data Publishing Basics, room 743
3-4pm: Building a Citation Presence | Register Here
4-5pm: Documenting Your Data | Register Here
5-6pm: Data Publishing Platforms | Register Here
Wednesday, November 8th, 2017, 12-5 pm
We would like to cordially invite you to the Data Services Research Day celebration at NYU.
NYU Data Services is hosting a very exciting Data Services Research Day 2017 @ NYU event – an “All Things Research” information fair on Wednesday, November 8th from 12 to 5pm on 5th floor of Bobst Library.
We aim to build and foster the research community by bringing awareness about research technology; featuring cutting edge tools, services, & resources offered by Data Services and various partners from NYU IT and NYU Libraries; and showcasing some exciting applied research being done here at NYU. Registration for attending and for participating in the competition is now open.
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Registration: http://nyu.libcal.com/event/3569768
This workshop will introduce attendees to the HathiTrust Research Center’s tools and services for utilizing the massive HathiTrust Digital Library in computational text analysis. The HTRC leverages the scope and scale of HathiTrust Digital Library’s holdings to allow researchers the opportunity to perform text data mining. The workshop will be broken into two sessions, morning and afternoon. Topics that will be covered include:
- How the HTRC makes HathiTrust volumes available for text mining.
- How to identify relevant volumes and build worksets (collections) of content for analysis.
- How to use HTRC off-the-shelf tools for text analysis and visualization.
- How to access HathiTrust data and metadata via provided APIs, request procedures, and open datasets.
The workshop will be led by Eleanor Dickson, HathiTrust Research Center Digital Humanities Specialist at the University of Illinois, and Leanne Nay, Digital Engagement Librarian at the University of Indiana.
Registration is required for the workshop: http://nyu.libcal.com/event/3569768
There will be a follow up individual consultations session on Tuesday, October 17th, 9:00 am for participants in the workshop who need further guidance on a specific HTRC project that they are engaged with.
For those who are currently conducting research using text-as-data and data-mining projects using HathiTrust’s holdings, we will be hosting a lightning-talk session over the workshop lunch hour break on Monday, 12-2 pm. If you are interested in presenting a brief, 5-minute overview of your HTRC-based research, please indicate this on the registration form. The workshop will try to accommodate as many presenters as possible given time restraints.
Please contact digital.scholarship@nyu.edu with any questions.
]]>Also, refer to the video below for a 3D preview of what the data looks like when visualized.
About the Collection and Data Release
The 2015 LiDAR dataset is a landmark acquisition for geospatial data collections at NYU Libraries. It is the first time since the launch of our new Spatial Data Repository in 2016 that the GIS team has worked with researchers at NYU to bring a complex, multi-format original dataset into our collection. Many thanks to Stephen Balogh, Brittney ONeill, Ahn-Vu Vo, and others who put in incredible amounts of work on organizing the data for release and developing capacity for it.
Because of the size and complexity of the data, we had to take several new steps in order to present the data with enough spatial context to be useful to a range of geospatial researchers. One of the most frequent questions we anticipate about this data is, “what is it, and what can you do with it?” To help, the team has provided a 3D rendering of what the point cloud data looks like when visualized (see below).
This is just one section of point cloud data, which anyone can download and visualize with a library like Potree, though even this visualization is presenting a compressed and down-sampled version of the full waveform LiDAR, which is made available in LAS and Pulsewaves formats. Professor Laefer’s team has provided very robust documentation about the use of this data in research, and its application for urban informatics scholarship. To date, this type of data has been used to explore the detection of road curbs and obstacles, tree growth, and more.
The size and complexity of the data associated with the 2015 aerial laser scan has also required us to revise some of the ways that we have been presenting spatial data. In total, the data associated with just a two square kilometer area in Dublin is well over one terabyte and comes in at least four different formats, including point cloud, full waveform, and infrared GeoTIFF. We needed efficient ways for users to explore smaller subsets of the data and download files efficiently, so we expanded the interface of GeoBlacklight to afford for discovery according to individual flight paths or area of coverage.
Through our spatial discovery application, GeoBlacklight, users can find sections or subsets of the data that are important to them and download accordingly. We hope that this release of LiDAR data benefits the larger geospatial community, and we encourage you to explore the complete collection within NYU’s Spatial Data Repository.
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