SPIDERS Semantic P2p data Interchange with Distributed

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1 SPIDERS Semantic P2p data Interchange with Distributed
agEnts among netwoRk management Systems W3C Workshop on RDF Access to Relational Databases 25-26 October, 2007 — Cambridge, MA, USA TELEFÓNICA I+D Date: 25th October 2007 Sergio Garcí á Gómez © 2007 Telefónica Investigación y Desarrollo, S.A. Unipersonal

2 01 Objectives 02 Today’s approach 03 Requirements 04 Conclusions Index
- Motivation - Vision - Ingredients - Goals 02 Today’s approach - IU Screenshots 03 Requirements 04 Conclusions

3 01 SPIDERS motivation Operations Support Systems (OSS) and Business Support Systems (BSS) in an incumbent operator compose a complex ecosystem of legacy systems. Each system supports different functionalities and manages and shares with other systems large amounts of data. Data is propagated by remote invocations, message passing systems, ad-hoc interfaces and also by manual data loads. These are error prone procedures. Problems in the quality of data may cause delays and failures in network management processes and therefore, higher operation costs (OPEX) and delays in the time-to-market. It also hampers the automation of management processes and the development of autonomic communications systems and elements.

4 Sistemas de Gestión de Averías Sistemas de Soporte al Negocio (BSS)
01 SPIDERS motivation e-agora EECC VPN-IP GAM Gestión Actividad CARPE CIOCO VIPE SINPLEX (4 provincias) GEOPLANTA Planta Exterior SIRP DIPE_VP Sistemas Supervisión Planta Exterior FO.interUrb SERA SSP EBR Red Ibermic (JDS, WDM, JDP) Red Transporte Sistemas Supervisión Red Transporte (JDS, WDM, JDP) Red Ibermic Needs Trouble tickets Sist. Medidas, Prestaciones y Contabilidad ENRUTA SCAR DITRA SSP Otras ... MCE TELESAP Sistemas de Gestión de Averías Red GigADSL Red ATM Red RIMA Red Imagenio Red NIMBA HADA Customer SIGA-HD Aplicaciones Prueba Sistemas Supervisión Red GigADSL Red Imagenio Red ATM Red RIMA Red NIMBA GRI APO Sist. Medidas, Prestaciones y Contabilidad e-agora E-DICRE EECC Orders Plan 1000 GRILLO Otras ... ARI SGT SERA Aplicaciones Prueba Sistemas Supervisión RTC Red Señ. Nº 7 Red FITL Red Señ. Nº 7 Red FITL RTC SAMGRED CAT Sist. Medidas, Prestaciones y Contabilidad SERES Energía Red Sistemas Supervisión Red Energía RPE MAPA Sistemas de Soporte al Negocio (BSS) Gestión Actividad GESCAL GAOM ATLAS SIAAM PLC SIGA CARMELA Red GigADSL Red ATM Red RIMA Red Imagenio Red NIMBA INTEGRA SCRABA SONIX SEMTA SIGA SPRA SPCI OVSA SERA GEDEÓN MCP PORTICO e-agora e-agora Sist. Operación Planta Sist. Operación Planta Sist. Operación Planta Red Transporte (JDS, WDM, JDP) Red Ibermic Red GigADSL Red ATM Red RIMA Red Imagenio Red NIMBA Red Telefónica Conmutada Red Señalización Nº 7 Red Acceso FITL EECC EECC

5 01 Vision OSS 1 To create a semantic layer which makes up a federated and consolidated view of information throughout the network and service management ecosystem. Local Ontology Relational BD OSS 2 OSS 3 Local Ontology De forma más específica, nos planteamos crear un modelo semántico, una ontología, que represente el modelo de datos de cada uno de los sistemas. Estos modelos semánticos pretendemos unificarlos en una visión federada, común, de los modelos de todos los sistemas, de manera que, por poner un ejemplo sencillo, un número de teléfono signifique los mismo para todos los sistemas. Para lograr esta visión federada, partimos de un vocabulario que ya existe en los sistemas de gestión de red, que es el Shared Information and Date del Telemanagement Forum. Una vez que tenemos esa base construida, se pueden definir los mecanismos para hacer y automatizar consultas y extracciones de datos de otros sistemas. Para ello, en cualquier caso, hace falta crear una red completamente distribuida que permita que cada nodo interactúe con los demás a conveniencia, y que el sistema en su conjunto no dependa de un nodo que centralice la información de todos los demás. P2P Network Local Ontology Relational BD Relational BD

6 Ingredients (some buzzwords)
01 Ingredients (some buzzwords) Semantic technology: ontology (OWL) based data models and SPARQL queries. P2P: each legacy OSS is a peer node in a network. Distributed Agents: every peer system Network Management Systems: systems are, in fact, Operations Support Systems (OSS) NGOSS: New Generation Operations Systems and Software. SID: NGOSS Shared Information and Data. SPIDERS: Semantic P2p data Interchange with Distributed agEnts among netwoRk management Systems

7 01 Goals To model the SID as an ontology and to extend the model to the needs of information to each OSS. To provide the mechanisms to create a federated view of all the SID-based ontologies. To create a P2P distributed network of OSS-attached agents which are able to: translate relational information into semantic information through SPARQL queries. insert or update the relational data with information from the SPARQL query results. To provide the mechanisms to support the needs from real systems: subscriptions to data changes, on demand queries, massive loads or validation of data integrity. The system must be as less intrusive as possible with the existing legacy OSS's.

8 02 Today’s approach P2P Network OSS 1 OSS 2 SPIDERS Operation:
Variables SPARQL Queries Assignments 1 3 SPARQL Query P2P Network SPIDERS Agent 6 Local Ontology 2 SPIDERS Agent SPARQL Query Federated Ontology SPARQL ResultSet to DB (assignment) 7 4 5 D2R Mapping 8 Relational BD Relational BD

9 Based on Protègè and OntoSphere plugin
02 UI Screenshot (I) Based on Protègè and OntoSphere plugin

10 02 UI Screenshot (II)

11 02 UI Screenshot (&III)

12 03 Requirements (I) SPARQL based access Local SPARQL endpoint
Efficient access. The data will remain relational. Local SPARQL endpoint To offer a common SPARQL endpoint for multiple distributed data sources and to enable the resolution of queries joining results from all of them. OSS 3 OSS 2 P2P Network Query Who answers? OSS 1

13 03 Requirements (II) Bidirectional translation
It is required to insert, update or delete data in the relational schemas from RDF data or SPARQL results, based on an semantic to relational mapping. The same mapping approach for both directions would be desirable. Complex problems: generation/work out of primary and foreign keys, identifying properties, data types compatibilities, fulfillment of constraints, data formats, etc. OSS 3 Ontology Relational Data to RDF / SPARQL results OWL Schema Mapping RDF / SPARQL results to Relational Data Relational BD

14 03 Requirements (&III) Support for morphologic transformations
Origin and destiny data must follow coherent formats (i.e., capital letters). It must be provided mechanisms to define and transform morphologic properties. Propagation of data changes Data is dynamic. There are different interaction mechanisms: push, poll, subscription… From the semantic condition to the relational database trigger. Security There must be a control over which systems access every piece of data, and under which conditions.

15 Conclusions and future work
04 Conclusions and future work The objectives of the project have created great expectation on Telefonica’s OSS domain. But there is a long road to go: Bidirectional mapping. Standardization of mappings. Federated data model based on ontologies alignment/merging. At the end, we will be enabled to: Automate data acquisition processes. Automate network management processes based on stored information.

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