Analyze & Use
Data have value when they are used. Careful work in data planning, generation, collection, and processing (collectively data management) come to fruition through data analysis and other uses such as decision support to better manage ongoing studies.
Research Computing Service Links
- GENIE HPC Cluster
-
Data
On-prem Storage
- LMS:
- Description:
- Isilon Leased mass storage is file storage for groups and/or individuals of data on a server that is managed and maintained by IMS and includes workstation set up and maintenance of user storage areas (includes group and individual shares). LMS covers basic file/print services only. Server based applications and layered product support must be requested and agreed to on a case-by-case basis and will incur an additional charge. IMS will ensure that the storage leased is backed up to tape on a routine basis. This includes off-site storage. Request for recovery of data from backup tapes will be at an additional charge after the number of recoveries indicated in the table below. Backup tapes are normally retained for one year. Longer retention times must be requested and agreed to on a case-by-case basis. There may be an additional charge for longer retention times.
- Purpose:
- Frequently Accessed
- Shared within and outside of your department
- IMS managed permissions
- Storage Type: On-prem Tiered
- Data Policy:
- Confidential 1
- Published 1
- Controlled 1
- Backup Available?: Yes
* As changes in University policies and state/federal regulations occur, this table may be revised. Please check this page occasionally to ensure you stay aware of the current guidelines.
1 – See explanations for confidential, controlled, and published data in the Data Classification table below
2 – “Personal Work Data” are the day-to-day files you create and work with as part of your job that don’t fall into the confidential, controlled, or published data categories (documents, spreadsheets, presentations, etc.)
3 – 1TB is the initial setup for UT OneDrive storage but this amount can be increased by request
4 – Departmental pricing is based on the volume of data stored
5 – In compliance with PCI-DSS requirements
6 – Applies to existing internal SharePoint sites only; requests for new sites will reside in Microsoft's Office 365 cloud
7 - Personnel must request an exemption to utilize Non University Acquired Cloud Services for storing/processing Non Confidential or Non Controlled data
- Big Storage
Off-Prem Storage
- Cloud
- Blob
- Azure
- TACC
Archive Storage
- Description: Microsoft Cloud storage platform
- Purpose:
- Azure archive storage is designed for long-term archival of data that is not often accessed.
- Storage Type: Cloud
- Data Policy:
- Confidential 7
- Published 1
- Controlled 1
- Backup Available?: No
* As changes in University policies and state/federal regulations occur, this table may be revised. Please check this page occasionally to ensure you stay aware of the current guidelines.
1 – See explanations for confidential, controlled, and published data in the Data Classification table below
2 – “Personal Work Data” are the day-to-day files you create and work with as part of your job that don’t fall into the confidential, controlled, or published data categories (documents, spreadsheets, presentations, etc.)
3 – 1TB is the initial setup for UT OneDrive storage but this amount can be increased by request
4 – Departmental pricing is based on the volume of data stored
5 – In compliance with PCI-DSS requirements
6 – Applies to existing internal SharePoint sites only; requests for new sites will reside in Microsoft's Office 365 cloud
7 - Personnel must request an exemption to utilize Non University Acquired Cloud Services for storing/processing Non Confidential or Non Controlled data
- Servers and Virtual Machines
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Cloud Services
Compute
HPC
Cloud
Cycle Cloud
On-Prem
PACC
Genie
Web
Cloud
On-Prem
Database
Cloud
On-Prem
Application
Cloud
On-Prem
Storage
Active
Archive
Cloud
Azure Blob Storage
Share
On-Prem:
LMS
Off-Site:
Blob
-
Research Infrastructure
HPC
PACC
Overview
High level diagram
Compute
Storage
Interconnect
Data Transfer:
Globus: New Globus Service
Request new Globus endpoint collection setup
UT Health San Antonio internal knowledge base article for how to use the Globus service
Support for data management projects involving Compute Storage, Data Collaboration, Data workflows and Data Backup
Getting Starte with Globus
Data Classification & Security
UT Health SA HOP 5.8.31 classifies all cloud services as a risk. UT Health SA has a BAA with Microsoft cloud services, which include Azure, OneDrive, and Office 365. UTHSA-IT (formerly IMS) is utilizing Cloud App Security, which provides visibility, control over data travel, and analytics to identify security violations or abnormalities across Microsoft's cloud services by monitoring and analyzing audit logs.
Determining the sensitivity of your dataThe types of data being stored and how it is to be used are very important when deciding what form of storage to use. All sensitive data types (Confidential/High Risk) identified in Handbook of Operating Procedure 5.8.21 must be stored on internal servers. Cloud storage is excellent for collaborating with others, while on-prem servers provide the greatest degree of security.
Data ClassificationDescription Examples Comments Confidential/High Risk Information or data is classified as Confidential if it must be protected from unauthorized disclosure or public release based on State or Federal law or regulation, and by applicable legal agreement to the extent permitted by law.
Protected Health Information (PHI): clinical patient records, identifiable patient research records.
Student Identifiable Information (SII): student demographic information, performance, financial, or health records, etc.
Personally Identifiable Information (PII): institutional and departmental personnel records that contain private information on an employee.
Sensitive Digital Research Data: Electronic data requiring highest levels of protection
Credit Card Information
Social Security Number (SSN)
This classification is reserved for information that is protected from public release based on state or federal law, or a legally binding order or agreement.
Controlled Data The Controlled classification applies to data that is not generally created for or made available for public consumption, but may be subject to release to the public through request via the Texas Public Information Act or similar State or Federal law.
Operational records, operational statistics, employee salaries, budgets, expenditures.
Internal communications that do not contain confidential Information.
Research data that has not yet been published, but which does not contain confidential Information protected by law.
This classification likely encompasses the greatest volume of Data within the University.
Published Data Published data includes all data made available to the public through posting to public websites, distribution through email, social media, print publications, or other media
Statistical reports
Fast Facts
Published research
Unrestricted directory information
Educational content available to the public at no cost
Information can migrate from one classification to another based on the information life-cycle. Unpublished research may fit the criteria of “Controlled Information” until published, upon which it would become Published Information.
News & Events
PACC is a joint initiative of IT and Research departments. By combining resources and funding, these departments can acquire a cutting-edge HPC system that can manage complex calculations and big datasets with speed. This system can be used to speed up research and development, enhance data analysis
PACC is a joint initiative of IT and Research departments. By combining resources and funding, these departments can acquire a cutting-edge HPC system that can manage complex calculations and big datasets with speed. This system can be used to speed up research and development, enhance data analysis, and enable various applications. By cooperating, the IT and Research departments can ensure that the HPC system is well maintained and used to its maximum capacity, serving UT Health research.