[Sandbox for Accessibility] Data Services

Data Services offers consultations, teaching, and support for data, learning, analysis, and research. Our staff strives to provide quality advice, information, and support for those working with our supported software platforms, finding and interpreting data, and implement practices for data management and reproducibility.

General Expectations and Guidelines

The following expectations are intended to prepare patrons and students to interact with our services productively.

• Patrons of all Libraries services must abide by the NYU Libraries' Policies. We reserve the right to deny service at our discretion for violations of the Code in consultations or workshops.
• As a general rule, Data Services provides consultation specifically for software and coding platforms we support. In most cases, we do not offer deep methodological support, though we do offer support in best practices for data management, and strategies for data finding. We also routinely suggest resources to support methodological choices (resource requires login with NYU NetID and password), assist learners as they understand the implications of those choices, and help learners execute these choices within a supported software package.
• Data Services supports requests directly connected to the research and educational goals of the university. Examples include scholarly research, course assignments and projects, dissertation/thesis work, grant proposals, and other related forms of intellectual inquiry. We are not able to assist with projects involving individual entrepreneurship, outside employment, externships, or paid consultancies.
• Though Data Services consults on content, principles, and literacies present in student assignments, the service is not intended to be a step-by-step homework help or tutoring support service. We support learners in applying concepts and techniques to their own work independently. Staff may suggest that users take our introductory tutorials, use sample datasets as guidelines, reference learning resources and documentation, or recommend that learners confer with advisors (i.e. teaching assistants, professors, department advisors) to receive help with an assignment.
• We do not provide protracted, for-hire, or contract-based consultation services.
• Data Services staff typically does not provide detailed troubleshooting with software installation. We do our best to couple software access and licenses with helpful documentation so that users can install programs effectively, and when possible, we will point to recommended resources for users who are installing software, particularly in cases where software needs are occasioned by remote learn
• Classified or sensitive data: Data Services provides consultations and research data management advice for data projects involving classified or sensitive data, but we ask that patrons do not provide us with access to that data or introduce such data at the time of consultation into our computing environment, which is not secured to handle such data. To learn more about sensitive and secure data, please see the resources below:
  • Data Risk Classification
  • Data and System Security Policy
  • Electronic Data and System Risk Classification Policy

Consultation Guidelines

Expectations for Scheduled Consultations  

• We come to our consultations with the expectation that you, the patron, have made a reasonable effort  to accomplish your objective with the supported software package prior to requesting the appointment.
• We do not provide individualized, out-of-the-box consultations or introductions to software platforms. In such cases, users will be asked to register for upcoming tutorials and introductory classes. We do our best to distribute our classes across a range of days and times.
• Scheduled consultations are limited to one hour. We expect that complicated or time-intensive requests be broken into multiple consultations if necessary.
• Please provide at least 24-business-hours notice when scheduling an appointment. This allows us to match requests with our staff availability and find the person best prepared to help.
• Confirm your appointment and provide project files, sample data, and questions in advance, when possible. Having access to files, working code, or sample data enables our consultants to prepare in advance and make the time more productive.      

Expectations for Receiving Desk Encounter or Virtual Help

The Data Services lab on the 5th floor of Bobst and our chat services are staffed with consultants who are able to provide assistance with data-related questions or challenges. In cases where  chat or desk assistance becomes more complicated or involved, our consultants will instruct you to fill out a consultation request and reserve a dedicated time to work in greater depth.

Statement on Repeat Consultations

Current members of the NYU community, which includes students, faculty, and staff, are not limited in the number of times they can schedule consultations or receive virtual or on-the-spot help. However, the Data Services team supports students and researchers from across the entire NYU community and addresses many competing demands on our time and expertise. While we strive to assist patrons in overcoming data challenges and obstacles in their research, should the number of requests from a patron be deemed excessive or burdensome to our staff, we may refer patrons to consult with their instructor, advisor, academic department, or outside tutoring service, for further assistance.

Other Expectations

Many of the specific teams and service areas within Data Services have expectations that are more specific to the guidelines addressed here. See:

• Quantitative support guidelines
• Visualization support guidelines
• Geospatial Information Systems support guidelines
• Qualitative support guidelines

Data Retention

We maintain records of our appointment requests for planning and outreach purposes and may contact you in the future as part of our ongoing service planning/assessment.

High-Performance Computing (HPC)

NYU High Performance Computing provides access to state of the art supercomputer hardware and cloud services to eligible faculty and students across all of NYU. HPC regularly offers classes orienting newcomers to using HPC systems; check the class offerings by HPC on the main Library classes feed.

JupyterHub for Instruction

The NYU Instructional Tools for Coding service team offers a centralized JupyterHub deployment for course instructors. Access to the JupyterHub environment is granted by request each semester for faculty for their courses. Instructions on how to request and use the JupyterHub service are available on the NYU IT knowledge base.

Digital Studio

The NYU Digital Studio helps scholars create, use, store, and share multimedia materials (video, audio, text, images) for their research, teaching, and learning. Scholars work hands-on with Digital Studio hardware, software, and online tools to accomplish their projects. The Digital Studio trains users on the tools and software to accomplish their work, and it consults on best practices, project scoping and design. The Digital Studio is available to NYU faculty, students, and staff. An NYU NetID is required for access.

Research Workspace

Research Workspace, a collaborative service led by Digital Library Technology Services and Data Services, offers mountable storage for projects requiring high capacity storage for data during the active analysis stage of research projects. The services is provided by request, and is available for faculty or faculty-sponsored researchers.