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A SPACE ENVIRONMENT INFORMATION SYSTEM FOR MISSION CONTROL PURPOSES: SYSTEM ANALYSIS AND DATA INTEGRATION DESIGN 2 VOLUMES (VOL. I) MARTA BOTELHO PANTOQUILHO Lisbon March 2005 DEPARTAMENTO DE INFORMÁTICA A SPACE ENVIRONMENT INFORMATION SYSTEM FOR MISSION CONTROL PURPOSES: SYSTEM ANALYSIS AND DATA INTEGRATION DESIGN 2 VOLUMES (VOL. I) BY MARTA BOTELHO PANTOQUILHO Thesis submitted to Faculdade de Ciências e Tecnologias of the Universidade Nova de Lisboa, in partial fulfilment of the requirements for the degree of Master in Computer Science Monte da Caparica, Portugal March 2005 Coordinator: Prof. Doutor João Moura Pires Sumário Space Weather é o termo usado para denominar as condições no Sol e no espaço interplanetário. Estas condições podem influenciar o desempenho de sistemas tecnológicos (terrestres e espaciais) e afectar a vida humana. Esta influência é mais acentuada nos satélites, contribuindo para a redução do seu tempo de vida e causando largos períodos de indisponibilidade dos instrumentos. A função da equipa de controlo de voo de um satélite consiste na salvaguarda do satélite de condições de risco e maximização da sua produtividade. Actualmente estas equipas não beneficiam de um sistema que lhes forneça informação integrada de dados de telemetria do satélite com dados de space weather. O sistema de apoio à decisão Space Environment Information System for Mission Control Purposes - SEIS, em desenvolvimento para a Agência Espacial Europeia, aborda esta problemática e fornece uma solução de integração de dados provenientes de diversas fontes externas e a sua disponibilização em tempo real. O maior desafio do SEIS é a integração e acessibilidade aos dados. O módulo de integração de dados é responsável pelo armazenamento de mais de 1000 parâmetros de diversas naturezas e pela sua disponibilização para monitorização em tempo real e para análise e correlação histórica eficiente. A tese documentada por este relatório consiste na análise, desenho e desenvolvimento do módulo de integração de dados do sistema SEIS. Abstract Space weather refers to conditions regarding the sun and the interplanetary space. These conditions can influence the performance and reliability of space-borne and ground-based technological systems and affect human life and health. Such influence is particularly strong on spacecrafts by reducing the mission lifetime and causing long periods of instrument's unavailability. Keeping the spacecraft healthy and productive is the responsibility and the main concern of the spacecraft flight control team (FCT). Nowadays most FCTs are supported by different and non-integrated systems providing telemetry (spacecraft instrument status parameters) and space weather information which do not suffice their needs. The Space Environment Information System for Mission Control Purposes (SEIS) is a decision support system being developed for the FCTs at the European Space Agency (ESA). This system integrates huge data from space weather and spacecraft heterogeneous data sources, provides real-time data loading and visualization, and also generates added spacecraft knowledge based on real-time inference capabilities. SEIS major concerns and key features are data integration and availability. The Data Integration Module (DIM) is responsible for the integration of over 1000 space weather and spacecraft parameters and their availability both in real-time (for a fast and continuous data monitoring) and offline-time (for deep data analysis and cross-correlation). The thesis reported within this document consists in the design and development of SEIS Data Integration Module. - vii - Para ti, Marco. Por tudo, mas sobretudo por aquilo que somos juntos. - ix - Acknowledgements I want to thank my beloved parents Joaquina and António for their patience and understanding, and above all for their unconditional love. I want to thank my dear brother, Marco, for his support and incentive, and for his love. To Didier, I want to give warm thanks for his outstanding patience and support at all times and his unbalanced trust in me. But most of all, thank you for your love. To my very patient coordinator and friend João Moura-Pires: may we work together once again. Thank you for your support and trust, and for all of those priceless advices. Thank you also for making it possible to endure this project without going mad. Thank you to all my colleagues for their support and contribution for such a joyful, friendly workplace. Thank you for all the moments that you have shared with me. A special thanks to the SEIS team members, particularly to Nuno Viana: it is a great joy to see our little project become such a success after so many hard working hours and against so many things; to Ricardo Ferreira: thank you for your enthusiasm and positive thinking at all times, and thank you for accepting such a challenge; to Joaquim Neto: thank you for the reality check that sometimes was missing and for your friendly word at all times. To Ivan Dorotovic I want to thank his professional example and help with the scientific revision of volume II. To Luís Correia and Alfredo Pereira, thank you for trusting and inviting me to be a part of this marvellous research team and to Rita Ribeiro thank you for your trust and support on this project. Finally, a special thanks to my friends and family that had to accept my absence so many times, for their understanding, love and support. This thesis is supported by the Fundação para a Ciência e Tecnologia grant number: SFRH/BM/17092/ xi - List of Abbreviations Throughout this document are used abbreviations and acronyms in order to improve the document s readability. The complete list and their meaning are presented in the following table (in alphabetic order). Abbreviation 3M CME DW DIM DKE ENVISAT ESA ETL FCT FOP INTEGRAL MT NOAA ODS OLAP OOL RAT S/C SCD SEIS SEU TLE XMM-Newton Meaning Mission Modelling Module Coronal Mass Ejection Data Warehouse Data Integration Module Dynamics, Kinematics and Environment Environmental Satellite (Is an ESA s satellite) European Space Agency Extraction, Transformation and Loading Flight Control Team Flight Operation Plan INTErnational Gamma Ray Astrophysics Laboratory. (Is an ESA s satellite). Monitoring Tool National Oceanic and Atmospheric Administration Operational Data Store On-Line Analytical Processing Out-Of-Limit Reporting and Analysis Tool Spacecraft Slowly Changing Dimensions Space Environment Information System Single Event Upset Two-Line-Element X-ray Multi-Mirror Mission. (Is an ESA s satellite). - xiii - Table of Contents 1 Introduction Context And Motivation Space Environment Assuring the Spacecraft Health Space Environment Information System Focus and Goals of this Thesis Document s Structure 10 2 Background, Technology and Related Work Background and Technology Decision Support Systems Data Warehousing Dimensional Modelling Metadata Related Work Earth and Space Environment Systems SEIS siblings Conclusion 34 3 SEIS Architecture Architecture Overview Data Data Flow Server-Side Modules Metadata repository Data Processing Module Forecasting Module Data Integration Module Client Tools 48 - xv - 3.3.1 The Monitoring Tool The Reporting and Analysis Tool Hardware Solution Conclusion 53 4 Problem Analysis Spacecraft Spacecraft Instruments and Measurements Spacecraft Orbit, Revolution and Position Spacecraft Events and Alarms Space Weather Space Weather Measurements Space Weather Alarms and Events Solar Cycle Spacecraft and Space Weather Ontology Forecasted Data Sizing The Problem Metadata Contribution Conclusions 78 5 SEIS Data Integration Module Design Operational Data Store Conceptual Design Physical Design Data Warehouse Conceptual Design Physical Design OLAP Cubes Conclusion SEIS Data Integration Module Management Operational Data Store Management Staging Area Processes xvi - 6.1.3 Further Improvements Data Warehouse Management Staging AREA DW Builder DW Partitions Manager DW Loader Implementation Details Conclusions Conclusion Key Points Goals Achieved Further Improvements (Discussion and Pointers) Glossary Solar and Astronomical Terms Technical Terms Bibliography Annexes Annex Annex Annex Annex xvii - List of Figures Figure 1.1: The Numerous Effects of Space Weather [2]. 5 Figure 1.2: SEIS system architecture overview. 7 Figure 3.1: SEIS system detailed architecture. 40 Figure 3.2: Metadata Module context. 42 Figure 3.3: Data Processing Module context. 43 Figure 3.4: Forecasting Module context. 44 Figure 3.5: Data Integration Module context. 45 Figure 3.6: SEIS Staging Area detail. 46 Figure 3.7: Client Tools context. 48 Figure 3.8: Monitoring Tool Main Window. 49 Figure 3.9: SEIS UML deployment scenario. 52 Figure 4.1: The four elements of an orbit [58]. 58 Figure 4.2: Spacecraft position in state vector representation [59]. _ 59 Figure 4.3: The orbits of the planets sweep out equal areas in equal time [60]. 60 Figure 4.4: Simple alarm rule example. 61 Figure 4.5: Domain reduced ontology: spacecraft and space weather concepts. 69 Figure 4.6: The three types of time series. 70 Figure 4.7: Data points in updates may be desynchronized. 71 Figure 4.8: Relation between the Spacecraft Concept and its instances, depicted in a UML Class diagram. 75 Figure 4.9: Global ID and Local ID usage example. 75 Figure 5.1: ODS Conceptual Model. 82 Figure 5.2: Desired ODS partitioning management. 84 Figure 5.3: Date and Time Dimensions. 85 Figure 5.4: Date-time Interval specification. 86 Figure 5.5: Spacecraft hierarchy tables attributes. 90 Figure 5.6: Spacecraft Position Star Schema. 92 Figure 5.7: Short Term Orbital File Format. 93 Figure 5.8: Two Line Element (TLE) Set Format. 94 Figure 5.9: Spacecraft Orbital Representation Star Schema. 94 Figure 5.10: Spacecraft Events' star schema. 95 Figure 5.11: Spacecraft real time series' star schema. 97 Figure 5.12: Alarms star schema. 99 Figure 5.13: Real Complex Space Weather Time Series star schema.102 Figure 5.14: Simple Space Weather Time Series star schema. 102 Figure 5.15: Space Weather Events star schema. 104 Figure 5.16: Data Warehouse partitions, per fact table. 106 Figure 5.17: Data Warehouse partitions close up xix - Figure 6.1: DIM hardware breakdown. 114 Figure 6.2: DIM UML State Diagram. 115 Figure 6.3: Processed Data Buffer Model. 117 Figure 6.4: Non-duplicate treatment inside the Processed Data Buffer.118 Figure 6.5: Staging Area control tables. 118 Figure 6.6: ODS Loading Process UML activity diagram. 120 Figure 6.7: ODS Cleaner UML Activity Diagram. 121 Figure 6.8: Data Warehouse Staging Area decomposition. 123 Figure 6.9: Data Warehouse Staging Log model. 126 Figure 6.10: DW Builder Process UML activity diagram. 127 Figure 6.11: Data Warehouse (and OLAP Cubes) partitioning management. 129 Figure 6.12: DW Partition Manager UML Activity Diagram. 130 Figure 6.13: DW Loader Activity Diagram. 131 Figure 6.14: SW Events Loading DTS. 133 Figure 6.15: Main DTS that controls all DTS execution xx - List of Tables Table 2.1: Data Warehouses vs. Operational Data Stores 19 Table 3.1: SEIS hardware configuration summary. 50 Table 4.1: Most significant space weather parameters' features (excluding the Complex-Set type). 63 Table 4.2: Summary of the prediction's overwriting policies. 72 Table 4.3: Data division by source and type within the SEIS system. _ 73 Table 4.4: Data division by source and sampling rate within the SEIS system. 73 Table 4.5: Data flow volume into the Data Integration Module (DIM). 73 Table 4.6: Most significant S/C Parameters concepts fields. 76 Table 5.1: ODS tables record definition. 83 Table 5.2: ODS tables indexing strategy. 83 Table 5.3: S/C star schema dimensions. 88 Table 5.4: Spacecraft Model Bus Architecture. 91 Table 5.5: SW dimensions. 99 Table 5.6: Space Weather model bus architecture 100 Table 6.1: Summary of the DIM management processes, per database.112 Table 6.2: Data Processed Buffer and ODS Staging Area tables record definition. 119 Table 6.3: Data Warehouse Staging Operational/Ad-Hoc Area tables. 124 Table 6.4: Data Warehouse Staging Data Area tables. 124 Table 6.5: Data Warehouse Staging Control Area tables. 125 Table 10.1: SEIS domain ontology glossary. 152 Table 10.2: Complete list of ground bases and spacecrafts used as data sources in SEIS. 153 Table 10.3: Data Warehouse Architecture bus matrix. 155 Table 10.4: Data Warehouse size estimations, including indexes. 157 1 Introduction Contents 1 Introduction Context And Motivation Focus and Goals of this Thesis Document s Structure 10 Introduction This chapter introduces the context and motivation for this thesis as well as its main objectives. Later on the structure of this document is presented. Finally, the scientific revisers of its content are introduced. 1.1 CONTEXT AND MOTIVATION SPACE ENVIRONMENT Space weather is the combination of conditions regarding the sun and the solar wind, magnetosphere, ionosphere and thermosphere that can influence the performance, integrity and reliability of space-borne and ground-based technological systems and that can affect human life and health [1]. The main driver of space weather near the Earth is the sun. It accomplishes this through its solar storms and events such as solar wind, solar flares and coronal mass ejections (CME). These phenomena affect and are affected by the Earth magnetic field which usually manages to shield effectively the Earth from the hazardous space weather effects. Space weather conditions affect everything surrounding it; however the exact extents of its influence are not completely clear yet. It is not hard to imagine that with the average CME dumping about double the power generating capacity of the entire U.S. into the atmosphere, big changes that can wreak havoc on a world that depends on satellites, electrical power, and radio communication - all of which are affected by electric and magnetic forces [2]. Many types of industries may be impacted by space weather: The communication industry has many problems with solar events. Solar activity can disturb radio transmissions and completely damage the electronics on satellites and in antennas. The power industry has problems with solar events since their transformers can become overloaded. Almost any industry that uses electronics in space can be affected by extremely powerful (but rare) bursts [3]. The industry is not the only one to be affected by space weather events: animals are affected as well. The National Oceanic and Atmospheric Administration (NOAA) lists animal effects getting more pronounced as the geomagnetic field gets more disturbed. It is pretty well accepted that homing pigeons and honey-bees (and probably sharks and rays and various bacteria) react to the Earth's magnetic field and its variations [4]. Astronauts and commercial flights are also affected by space weather conditions. The Earth's atmosphere and magnetosphere protect people on the ground, and even astronauts in Low-Earth-Orbit (LEO) are reasonably protected by the Earth's magnetosphere, although they occasionally seek shelter in protected modules of the International Space Station. At cruising altitude for subsonic and supersonic aircrafts the Earth s protective layer is significantly reduced, therefore exposing aircrafts directly to radiation of secondary cosmic rays produced in the Earth s atmosphere itself by galactic cosmic rays. Route and time of flight can influence the rate of on-board electronics and the radiation dose received by aircrews [5, 6]. The most susceptible items affected and damaged by space weather events are satellites. Satellites, also known as spacecrafts (S/C), are by their nature more susceptible to space weather events than groundbased systems, since they do not benefit from Earth s protective magnetic field [5]. Furthermore S/Cs - 4 - Context And Motivation usually carry sensitive instruments and other components that can easily be damaged by electromagnetic events. Typical cases are single event upsets (SEU) that flip a bit in the on-board memory, corrosion of the solar arrays, degradation of sensors, S/C charging. All these effects favour the aging of the S/C and can lead to malfunctioning of components and data loss [7]. In extreme cases, complete unavailability of services up to mission loss can occur [5]. Figure 1.1 depicts the manifold effects of space weather. It is reasonable to state that space weather effects are widely distributed. Figure 1.1: The Numerous Effects of Space Weather [2] ASSURING THE SPACECRAFT HEALTH Keeping the spacecraft (S/C) healthy and productive is the responsibility and the main concern of the S/C flight control team (FCT). This is a demanding and complex task considering that it is hard to detect environmental conditions of a S/C to be safe or to be hazardous. The most widely used approach of a FCT to counteract these effects has been to play safe: Playing safe, i.e. triggering counter measures early enough and keeping them for a long enough period, is a measure to reduce the risk, but it is not an efficient one. The dynamics of space weather could lead to situations where the instruments are shielded hours before the conditions become really hazardous. On the other hand it might happen that the FCT assumes safe conditions long before they actually occur. Sometimes instruments might be shut down or shielded even if there is only a transient radiation peak or they might be turned on too early, when the radiation level is still high. Another drawback of this approach is also that usually a single threshold for the radiation level decides whether the environment is safe or hazardous, when other measures could jointly be used to improve the assessment of hazard level on the S/C [7]. It is clear that the S/C productivity i.e. the observation time is being affected by these worst-case scenario based approaches. The availability of accurate real-time information about the ongoing space weather conditions in addition to better predictions of radiation levels could greatly improve these operations. However, such services - 5 - Introduction are currently not available or only very scarce. Although a lot of space weather data can be found on the Internet, it has to be acquired from many different places in many different formats. It is therefore almost impossible for a FCT member to consider all these sources. Furthermore the available sources for space weather data provide their data offline or at best at near real-time. Another problem is also that a great part of these data should be adapted to the conditions relevant for the specific S/C (materials of the S/C, position relative to the event source, etc). In light of these facts, it is concluded that although space weather data are available, it is very difficult for the FCT to have access to it, interpret it (due to the disparity of formats) and cross it with its spacecraft readings (telemetry data) at real-time (when it can be of any use) because data are neither uniformly integrated nor ready to use. Therefore, a decision support system that addresses these issues was envisaged by a research team at UNINOVA, a Portuguese research institute, in 2003 and proposed for development to the European Space Agency (ESA). Entitled Space Environment Information System for Mission Control Purposes (SEIS) the system integrates a huge variety of space weather data from different sources as well as S/C telemetry and ancillary data from running missions and stores it in a complete data repository based on data warehousing techniques. The users of this system are the FCT members of three selected ESA missions: INTEGRAL, ENVISAT and XMM-Newton. This system is introduced in the next section SPACE ENVIRONMENT INFORMATION SYSTEM Space weather has grown on importance and has become a source of concerns to human society since the awareness that our society is becoming increasingly depen
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