PIM
Projects
dataTUdiscovery

dataTUdiscovery (TU Wien - Future Fit)

AI/ML Service Center – Supporting Data-Driven Research at TU Wien

Abstract:

dataTUdiscovery is a cross-faculty service project at TU Wien funded through the fuTUrefit initiative. Its mission is to support researchers and students in the structured application and integration of Artificial Intelligence (AI) and Machine Learning (ML) methods within scientific projects.

The initiative acts as an interface between domain-specific research challenges and advanced AI/ML technologies. Its services include methodological consulting, feasibility assessments, technical implementation, and the prototypical development and evaluation of AI/ML workflows. Projects are supported from the initial idea and data review through model design and validation to final implementation and handover to the respective research groups.

By developing reusable methodologies, modular workflows, and sustainable implementation strategies, dataTUdiscovery strengthens data-driven research at TU Wien and enables efficient translation of innovative AI concepts into scientific practice.

Results:

dataTUdiscovery pursues several key objectives:

Building bridges between domain-specific research questions and modern AI/ML technologies.
Empowering research groups to apply AI-based methods confidently and in a scientifically rigorous manner.
Developing reusable workflows, models, and prototypes to increase efficiency and enable methodological transfer.
Lowering barriers to AI integration in research proposals and third-party funded projects.
Supporting students who wish to engage in applied research projects involving AI.

Workflow:

Detailed information on the process, participation opportunities, and current openings can be found on the official project website.

Lead:

Ass.-Prof. Esther Carina Heid

Faculty of Technical Chemistry

Contact Person for the Faculty of Mechanical and Industrial Engineering:

Univ.-Prof. Dr.-Ing. habil. Fazel Ansari

Email: fazel.ansari@tuwien.ac.at

Name	Purpose	Lifetime	Type	Provider
CookieConsent	Saves your settings for the use of cookies on this website.	1 year	HTML	Homepage TU Wien
SimpleSAML	This is needed to distinguish between the sessions of the logged-in users.	session	HTTP	Login TU Wien
SimpleSAMLAuthToken	This is needed to distinguish between the sessions of the logged-in users.	session	HTTP	Login TU Wien
fe_typo_user	Is needed so that in case of a Typo3 frontend login the session ID is recognized to grant access to protected areas.	session	HTTP	Homepage TU Wien
staticfilecache	Is needed to optimize the delivery time of the website.	session	HTTP	Homepage TU Wien
JESSIONSID	Is needed so that in case of a LectureTube the session ID is recognized to grant access to protected areas.	session	HTTP	LectureTube TU Wien
_shibsession_lecturetube	This is needed to distinguish between the sessions of the logged-in users.	session	HTTP	LectureTube TU Wien

Name	Purpose	Lifetime	Type	Provider
_pk_id	Used to store a few details about the user such as the unique visitor ID.	13 months	HTML	Matomo TU Wien
_pk_ref	Is used to store the information of the users home website.	6 months	HTML	Matomo TU Wien
_pk_ses	Is needed to store temporary data of the visit.	30 minutes	HTML	Matomo TU Wien

Name	Purpose	Lifetime	Type	Provider
facebook	Is used to Enable ad delivery or retargeting	90 days	HTTP	Meta
__fb_chat_plugin	Is needed to store and track interactions (marketing/tracking).	persistent	HTTP	Meta
_js_datr	Is needed to save user settings.	2 years	HTTP	Meta
_fbc	Is needed to save the last visit (marketing/tracking).	2 years	HTTP	Meta
fbm	Is needed to store account data (marketing/tracking).	1 year	HTTP	Meta
xs	Is needed to store a unique session ID (marketing/tracking).	1 year	HTTP	Meta
wd	Is needed to log the screen resolution.	1 week	HTTP	Meta
fr	Is needed to serve ads and measure and improve their relevance.	3 months	HTTP	Meta
act	Is needed to store logged in users (marketing/tracking).	90 days	HTTP	Meta
_fbp	Is needed to store and track visits to various websites (marketing/tracking).	3 months	HTTP	Meta
datr	Is needed to identify the browser for security and website integrity purposes, including account recovery and identification of potentially compromised accounts.	2 years	HTTP	Meta
dpr	Is used for analysis purposes. Technical parameters are logged (e.g. aspect ratio and dimensions of the screen) so that Facebook apps can be displayed correctly.	1 week	HTTP	Meta
sb	Is needed to store browser details and security information of the Facebook account.	2 years	HTTP	Meta
dbln	Is needed to store browser details and security information of the Facebook account.	2 years	HTTP	Meta
spin	Is needed for promotional purposes and social campaign reporting.	session	HTTP	Meta
presence	Contains the "chat" status of logged in users.	1 month	HTTP	Meta
cppo	Is needed for statistical purposes.	90 days	HTTP	Meta
locale	Is needed to save the language settings.	session	HTTP	Meta
pl	Required for Facebook Pixel.	2 years	HTTP	Meta
lu	Required for Facebook Pixel.	2 years	HTTP	Meta
c_user	Required for Facebook Pixel.	3 months	HTTP	Meta
bcookie	Is needed to store browser data (marketing/tracking).	2 years	HTTP	LinkedIn
li_oatml	Is needed to identify LinkedIn members outside of LinkedIn for advertising and analytics purposes.	1 month	HTTP	LinkedIn
BizographicsOptOut	Is needed to save privacy settings.	10 years	HTTP	LinkedIn
li_sugr	Is needed to store browser data (marketing/tracking).	3 months	HTTP	LinkedIn
UserMatchHistory	Is needed to provide advertising or retargeting (marketing/tracking).	30 days	HTTP	LinkedIn
linkedin_oauth_	Is needed to provide cross-page functionality.	session	HTTP	LinkedIn
lidc	Is needed to store performed actions on the website (marketing/tracking).	1 day	HTTP	LinkedIn
bscookie	Is needed to store performed actions on the website (marketing/tracking).	2 years	HTTP	LinkedIn
X-LI-IDC	Is needed to provide cross-page functionality (marketing/tracking).	session	HTTP	LinkedIn
AnalyticsSyncHistory	Stores the time when the user was synchronized with the "lms_analytics" cookie.	30 days	HTTP	LinkedIn
lms_ads	Is needed to identify LinkedIn members outside of LinkedIn.	30 days	HTTP	LinkedIn
lms_analytics	Is needed to identify LinkedIn members for analytics purposes.	30 days	HTTP	LinkedIn
li_fat_id	Required for indirect member identification used for conversion tracking, retargeting and analytics.	30 days	HTTP	LinkedIn
U	Is needed to identify the browser.	3 months	HTTP	LinkedIn
_guid	Is needed to identify a LinkedIn member for advertising via Google Ads.	90 days	HTTP	LinkedIn