1. A Research and Development Initiative Promoted by DI.S.T.A. Funded by EEC in the framework of BEEP project and by MURST in the framework of MITILUS project Project Management: Attilio Giordana (Computer Science) Aldo Viarengo (Biology) Team: M. Botta, Burlando, L. Portinale, A. Serra, M. Rapetti, G. Porcelli.

2. Project Goals To provide a user friendly apparatus world wide accessible for sharing and analyzing biological data collected by the environment monitoring laboratories To develop new data mining algorithms oriented to biological data analysis.

3. Hardware Support: Web server+DB server+Beowulf (20 Pentium III 800) Hermes (Oracle) now 0 now 1 now 2 now 3 now 7 now 8 now 9 now 10 now 4 now 5 now 6 now 11 now 12 now 13 now 14 now 15 now 16 now 17 now 18 now 19 switch WEB Server switch Beowulf (20 PC)

4. User Environment DB {a-i} Color Blue RedGreen White { m-t} {a-i} { b,g} { m,t} { d,e,f,h} { n,q} { c } { p,r,s } { a,i } Shape {e} Triangle SquareOval Circle {d,h} { n} Size {f} { q} {a-i} Color Blue RedGreen White { m-t} {a-i} { b,g} { m,t} { d,e,f,h} { n,q} { c } { p,r,s } { a,i } Shape {e} Triangle SquareOval Circle {d,h} { n} Size {f} { q} x1x1 x2x2 1 2 3 4 o1o1 o2o2 +1 x1x1 x2x2 1 2 3 4 o1o1 o2o2 Every user will benefit of a personal database together with an application specific set of data-mining tools

5. Software Architecture WEB Server Oracle Database Manager Data Mining Algorithms Java Interface Servelets Data Storage (192 Gbytes)

6. A User Fiendly Graphic Interface........ Dataset name Tool1Tool2Tool3Tool4Tool5 view 1 view 2 op1op2op3 op1op2op3op4..............................

7. Data Intensive Algorithms Run in Parallel on the Beowulf D-Tree Neural Net G-net.............. Algoritm Server Cluster Servlets Algorimi ad uso interattivo Sequence Analysis

8. Workpackages WP1: Database Design + Meta data WP2: Graphic Interface design and implementation 2.1: Approach selection 2.2: User autentication procedure 2.3: Oracle interafce 2.4: Data visualization WP3: Tool configuration interface 3.1 G-Net 3.2 Mine-Rule 3.3 Clustering Algorithms 3.4 Characterization Algorithm 3.5 Decision/Regression Trees 3.6 Neural Networks

9. Workpackages..... WP4: Servlet implementation WP5: Algorithm server implementation 5.1: Design 5.2: implementation WP6: Algorithm implementation 6.1: New KDD algorithm implementation 6.2: Existing algorithm revision

10. Work-Flow Wp1 Wp2.1 Wp4 Wp3.1-Wp3.6 Wp5.1 Wp6.1 - Wp6.2 Wp2.2 - Wp2.4 Wp5.2 15/1/2001 Wp1 (revision) 15/2/200115/3/2001