1. 22.02.2012 1 KLAUS FP ESRIN, February 22 nd 2012

2. 2 KEO: summary history (1/3) In the field of images (either SAR or Optical) exploitation ACS has been working on CBIR techniques since 2000 in the frame of international cooperations with major partners as ESA, DLR, CNES. A Knowledge-driven Information Mining (KIM) system based on stochastic search was first developed to support image classification and search of EO images in large archives. As a further step in Image Information Mining, ACS started in 2004 the development of KEO which implements a distributed component-based programming and processing environment, for the extraction of information from EO images: To Create & semantically identify internal/external Processing Components To Chain (graphically) Processing Components into Processing Chains To Store outputs (i.e. classification maps) into Web Servers (WFS, WMS, WCS) 22.02.2012

3. 3 KEO Projects IIM-TS (Image Information Mining – Time Series) 2008-2009 The IIM-TS project aims at delivering functionality aimed at making multi-temporal analysis possible in into the KEO Knowledge-Based Earth Observation system via the design, development, validation and integration of both a supervised interactive probabilistic explorative analysis element based on the KIM subsystem and a coherent inventory of automatic Feature Extractor Processors (FEPs) providing well- known algorithmic answers to a broad set of clearly specified applicative issues related to the analysis and exploitation of Satellite Image Time Series (SITS) for direct exploitation by a community of users. MIMS (MERIS Image Mining System) 2005-2006 To implement and deliver an operational system: Permitting, from MERIS RR1 products: Content Based Image Selection (CBIS), for the identification of MERIS images free from clouds over the user Area of Interest (AOI), as a service via the SSE or through an existing catalogue, by feeding it with the necessary data; Content Based Image Retrieval (CBIR) and Information Discovery of other features via dynamic user interactions including new system training. Permitting, from MERIS FR and other products, Information Discovery and Scene Understanding on system or user provided images via user interactions or SSE. Interfaced with: The image source(s), External catalogue(s), to transfer data related to image information content. PIMS-DLR (Partner Image Mining System – DLR) 2005-2006 Aimed to:  Identify DLR services (also based on IIM tools resulting from ESA contracts), which can be made available from the DLR environment through the SSE;  Identify the missions data on which these services can be based for easier user access;  Implement at DLR a system permitting to create IIM based services;  Integrate the services (derived or not from IIM) into the SSE;  Validate and demonstrate the system and the services for a few months. 22.02.2012 KEO: summary history (2/3)

4. 4 KEO Projects KIMV (KIM Validation for EO archived data exploitation support) 2003-2005 Aimed to demonstrate the effectiveness of the support provided to the user and to.identify:  key applications or services likely to benefit at most from access to images via content,  interface issues connected to an existing archive, verify the performance of the data ingestion chain in a quasi-operational environment,  best methods to interact with existing catalogues for complementing access via standard spatio-temporal queries with access via content,  best approach to envelope the available functions as services for simple user activation KES (EO domain-specific Knowledge Enabled Services) 2003-2005 Aimed to identify the technologies, and demonstrate them through a prototype at different deepness levels, applicable to a number of fields required to support image information mining and related user interactions. The fields to explore include learning systems, knowledge acquisition and sharing within user communities, image interpretation support, semantic interactions, automatic system adaptation to user behaviour. Apply above techniques to demonstrate knowledge supported Information Mining from EO images. KES-B (Knowledge Enabled Services) 2003-2005 Implement a prototype to:  define and implement an environment for easy, scheduled and controlled exploitation of resources (e.g.: data, algorithms, procedures, storage, processors,...), for example to automate the generation of products;  support users in easily identifying and accessing required information or products by using their own vocabulary, domain knowledge and preferences. KIM (Knowledge Driven Information Mining in Remote Sensing Image Archives) 2001-2002 A next generation architecture to help the user to gather relevant information rapidly and a tool that can manage and add value to the huge amounts of historical and newly acquired satellite data-sets. 22.02.2012 KEO: summary history (3/3)

5. 5 KEO vs KLAUS  KEO-3 In the frame of KLAUS the main objective to be pursued by KEO were essentially to: Improve the SW infrastructure in terms of reliability and removal of bottlenecks (i.e. data transfers) Provide system with user authentication and user access rights tools Include tools to simplify debugging of modules Extend the existing flow control features Fix known bugs on CPE and KIM systems Open the system to support interaction with other KEO installations 22.02.2012

6. 6 KEO V3.X Architecture (1/2) The new KEO architecture benefits of all recent enhancements on the open source libraries and products involved in its implementation: Application Server Glassfish 3.1 for the backend; Netbeans RCP v7 for the KAOS GUI JAX-WS 2.2, JAX-RS 1.1 and all new WS-I standard for communication layer Moreover, the new concept of CPE Domain was introduced and defined as a group of engines that shares a common data base, authentication service with own credential repository and authorization service with own grants database. 22.02.2012

7. 7 KEO V3.X Architecture (2/2) A new dispatching algorithm was designed to enable a huge optimization in the files exchange Through the introduction of evoluted MTOM and SAAJ capabilities the CPE communication layer was simplified avoiding the use of parallel FTP service. The new authentication follows JAAS specification, this enables the capability to plug a stack of different credential repository in the service (ie: Corporate LDAP, etc.) The architecture was simplified removing the Actuator components (now its functionalities are in charge of engines) and unnecessary components (Type Manager), this leads to a more steady and reliable environment. 22.02.2012

8. 8 KEO V3.X User Management (1/2) A new User’s Management mechanism was implemented to align the identification and authorization management to ESRIN implementation (Single Sign-On or LDAP). Main features: The new solution is based on two different web services: one for user’s authentication and one for user’s authorization. It uses JAAS (Java Authentication and Authorization Service) security framework that allows easy plug-in of different authentication modules, that will be tailored to access the new native KEO authentication and authorization web services. Users will never be managed from KAOS application. A new standalone java application allows the Administrator to manage KEO users, roles and privileges by the definition of only two entities: users and user’s groups. The web services have methods that permit the Administrator to easily control access rights and limit visibility of Processing Components (i.e. by permitting the Administrator to define specific user groups, classes of Processing Components and associations between groups and classes). The authorization web service will be always accessed by KARISMA, KAFE and KAOS with a token provided by the authentication web service, asking to access to a resource or to execute an operation. 22.02.2012

9. 9 KEO V3.X User Management (2/2) User Manager application - Main window 22.02.2012

10. 10 KEO V3.X KAOS Interface (1/3) KAOS V3.X was developed on top of NetBeans Rich-Client Platform (RCP) New interface allows greater control on windows management and fix some bugs of KAOS V2.2.2 It integrates new features (like linux terminal, or log monitoring) to improve system functionalities. The modular design will allow to add (or remove) components to meet new functionality, or to upgrade the interface. 22.02.2012

11. 11 KEO V3.X KAOS Interface (2/3) Log Panel Resources Panel Editor Window Properties Panel All windows/panels can be moved, detached, minimized or closed to change the default configuration 22.02.2012

12. 12 KEO V3.X KAOS Interface (3/3) Modules Palette Terminal Panel Log Panel (minimized) Resources Panel Editor Window Properties Panel (moved) 22.02.2012

13. 13 KEO V3.X FEP Designer The new FEP designer fixes some bugs of v.2.2.2 Offers a new flow control (IF-THEN-ELSE module) For every module it's possible to specify a “Preferred Node” for execution. The CLI module can now be tested before deploying it into a processing chain. The FEP runs into a separate detached process. Modules Palette Properties Panel Sketch Pad 22.02.2012

14. 14 KEO V3.X FEP Monitoring Monitoring Tool - a brand new tool to simplify debugging of modules Live Process Detailed Tracing Asynchronous Results Fetching Process Hierarchy Process Drill-Down Process Header Kill Function Process Search 22.02.2012

15. 15 KEO V3.X and OTB A new tool called MOJA–KEO (Mapping Tool for OTB Java APIs) was added. MOJA tool allows automatic generation of Java modules mapping some of the Orfeo Toolbox (OTB) image processing algorithms. It uses the OTB-Wrapping libraries (from CNES) that wrap the OTB algorithms to java classes. It dynamically performs a Java introspection on OTB-Wrapping libraries and build a set of Java modules that can be ingested in KEO. KEO V3.X MOJA tool release concentrates on a subset of OTB filters having Java primitive and String typed parameters (beyond input and output images). 22.02.2012

16. 16 KEO V3.X Semantic Search A semantic search of Processing components through Application terms was implemented. Tagging mechanism and semantic search: An ontology system, developed by Epistematica, is accessible through a web service. KAOS Gui permits to tag Processing Components with Application Terms (one or more) defined in the external thesaurus provided by the ontology system. The ontology search function available in KAOS permits to identify and rank the list of Processing Components from the associated Application Term. 22.02.2012

17. 17 KEO Federations 22.02.2012 Road towards the CPE Domain Integration (available in EOLIB) is set: User and resource authorization management are ready Cpe Engine remote execution functionalities are ready

18. 18 What’s after KLAUS: EOLIB The development initiated in KLAUS and aimed to the operational deployment of the KEO system will continue with EOLIB. In the frame of the EOLIB, ACS will further enhance the infrastructure along the lines agreed with ESA in the frame of a 24 months contract. Even in EOLIB KEO will maintain the KIM system inside although this will not be subject of new developments. A new concept of CBIR in replacement of KIM will be developed by DLR as part of their duties in the EOLIB context. 22.02.2012