elaboration and enhanced usage of data analysis tool damis+
TRANSCRIPT
Elaboration and enhanced usage of data
analysis tool DAMIS+Dr. Saulius Maskeliūnas
Vilnius University
Lithuania Turkey Collaboration Day
4 & 5 December 2017 – Eskişehir / TURKEY
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PROJECT IDEA NUMBER: .. (change in 1st slide of master)
The Institute of Mathematics and Informatics is a subdivision of Vilnius
University. It was a state scientific institute, a budgetary scientific
research institution until 30th September 2010;
IMI will become
Institute of Data Science and Digital Technologies since 2018.
IMI was set up to pursue important long-term research for the economy
of Lithuania and international cooperation.
There are 89 employees at the Institute.
67 researchers are working in the scientific departments, including: 11
doctors habilitatus and 48 doctors (11 doctors have completed
habilitation procedure); 19 professors, and 9 docents.
There are 52 doctoral students: 9 in Mathematics, 19 in Informatics
and 24 in Informatics Engineering; all of them are full-time students.
https://www.mii.lt/files/doc/en/imi-reports/research_at_vu_imi_2016.pdf
Vilnius University Institute of
Mathematics and Informatics (VU IMI)
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PROJECT IDEA NUMBER: .. (change in 1st slide of master)
VU IMI structure / research directions
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PROJECT IDEA NUMBER: .. (change in 1st slide of master)
Erasmus+ partners of VU Institute of
Mathematics and Informatics from Turkey
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PROJECT IDEA NUMBER: .. (change in 1st slide of master)
• Production Effectiveness Navigator (PEN)
Joint programme „EuroStars“ E!6232 Nr. 31V-20/LSS-580000-360
Turkish partner: HISBIM (coordinator)
May 2011 – October 2014.
https://web.archive.org/web/20141018082514/
http://www.eurekanetwork.org/project/-/id/6232
• ADHER: ADopt your HERitage.
Grundtvig project of Longlife Learning Program for adult
education, Nr. LLP-GRU-MP-2009-LT-00008.
Turkish partner: Atakum Adult Education Center
August 2009 – July 2011
http://www.adher.mii.lt/
VU IMI project with partners from Turkey
Project idea description & Key selling points
We have developed and are using [in the environment of
National Open Access Research Data Archive (http://midas.lt/), etc.]
the data analysis tool DAMIS (http://damis.lt/ ; demo / demo ).
Now DAMIS allows to carry out: (a) data preprocessing (clea-
ning, filtering, splitting, trasposing, normalising, feature selection);
(b) statistical handling; (c) dimensionality reduction
[PCA, SMACOF, DMA, relative DMS, SAMANN, SOM-MDS];
(d) classification, clustering [SOM, MLP, RDF, K-MEANS];
(e) viewing of results [chart and/or matrix view, technical details].
The proposed collaborative project DAMIS+ should develop:
(1) methodology, (2) platform, (3) toolbox – possibility to
dinamically extend functionality, capabilities of this data analysis
tool [with additional methods, etc.] by users themselves,
(4) expanded use cases for enhanced usage of
data analysis tool.
.
Partners & expertise
Partners already involved
- Vilnius University;
- Vilnius University Hospital Santaros Klinikos; Lithuanian Hospitals;
- Lithuanian Researchers (mainly from Universities).
Partners looking for
- Software and/or research companies/institutions;
- Any prospective users of data mining and knowledge discovery,
multidimensional data analysis, visualisation, etc. ...
Name Surname Saulius Maskeliūnas
Institution VU Institute of Mathematics and Informatics (after 2017: Institute of Data Science and Digital Technologies)
Email address [email protected]
Web address www.mii.lt
Telephone +370 5 2109342
Contact details
Functionalities and demonstration
• DAMIS is a web-based system http://damis.lt
(user name/password: demo/demo );
• The web interface does not require any software
installation; a web browser is enough for its usage;
• There is a possibility to choose
high performance computing resources
(VU MII cluster – VU MIF supercomputer);
• The usage is based on creation of scientific workflows;
• The results obtained can be saved in MIDAS and
in a user computer.
A sample of multidimensional data
(breast cancer data)C
5 1 1 1 2 1 3 1 1 b
5 4 4 5 7 10 3 2 1 b
3 1 1 1 2 2 3 1 1 b
6 8 8 1 3 4 3 7 1 b
4 1 1 3 2 1 3 1 1 b
1 1 1 1 2 10 3 1 1 b
2 1 2 1 2 1 3 1 1 b
2 1 1 1 2 1 1 1 5 b
4 2 1 1 2 1 2 1 1 b
... ... ... ... ... ... ... ... ... ... ...
8 10 10 8 7 10 9 7 1 m
5 3 3 3 2 3 4 4 1 m
8 7 5 10 7 9 5 5 4 m
7 4 6 4 6 1 4 3 1 m
10 7 7 6 4 10 4 1 2 m
7 3 2 10 5 10 5 4 4 m
10 5 5 3 6 7 7 10 1 m
... ... ... ... ... ... ... ... ... ... ...
4 8 8 5 4 5 10 4 1 m
Data upload
Data preprocessing
Statistical primitives
Dimensionality reduction
Matrix view of data after
dimensionality reduction by PCA
Data classification and clustering
Iris graphical representation
Experiments