Program on Earth Observation Data Management Systems (EODMS)

An assessment was made of the needs of a group of potential users of satellite remotely sensed data (state, regional, and local agencies) involved in natural resources management in five states, and alternative data management systems to satisfy these needs are outlined. Tasks described include: (1) a comprehensive data needs analysis of state and local users; (2) the design of remote sensing-derivable information products that serve priority state and local data needs; (3) a cost and performance analysis of alternative processing centers for producing these products; (4) an assessment of the impacts of policy, regulation and government structure on implementing large-scale use of remote sensing technology in this community of users; and (5) the elaboration of alternative institutional arrangements for operational Earth Observation Data Management Systems (EODMS). It is concluded that an operational EODMS will be of most use to state, regional, and local agencies if it provides a full range of information services -- from raw data acquisition to interpretation and dissemination of final information products

Manned Mars mission communication and data management systems

A manned Mars mission will involve a small crew and many complex tasks. The productivity of the crew and the entire mission will depend significantly on effective automation of these tasks and the ease with which the crew can interface with them. The technology to support a manned Mars mission is available today; however, evolving software and electronic technology are enabling many interesting possibilities for increasing productivity and safety while reducing life cycle cost. Some of these advanced technologies are identified

Program on Earth Observation Data Management Systems (EODMS), appendixes

The needs of state, regional, and local agencies involved in natural resources management in Illinois, Iowa, Minnesota, Missouri, and Wisconsin are investigated to determine the design of satellite remotely sensed derivable information products. It is concluded that an operational Earth Observation Data Management System (EODMS) will be most beneficial if it provides a full range of services - from raw data acquisition to interpretation and dissemination of final information products. Included is a cost and performance analysis of alternative processing centers, and an assessment of the impacts of policy, regulation, and government structure on implementing large scale use of remote sensing technology in this community of users

Assess program: Interactive data management systems for airborne research

Two data systems were developed for use in airborne research. Both have distributed intelligence and are programmed for interactive support among computers and with human operators. The C-141 system (ADAMS) performs flight planning and telescope control functions in addition to its primary role of data acquisition; the CV-990 system (ADDAS) performs data management functions in support of many research experiments operating concurrently. Each system is arranged for maximum reliability in the first priority function, precision data acquisition

Profit Maximization with Data Management Systems

Data, a core component of information systems, has long been recognized as a critical resource to firms. Data is the backbone of business processes; it enables efficient operations, supports managerial decision-making, and generates revenues as a commodity. This study identifies a significant gap between the technical and the business perspectives of data management. While functionality and technical efficiency are well addressed, the consideration of economic perspectives, such as value-contribution and profitability, is not evident. This study suggests that introducing economic perspectives can better inform the design and the administration of data management systems by accounting for the interplay between business benefits and implementation costs. To address the identified gap, the paper proposes a quantitative microeconomic framework for data management that links value and cost to the impartial/technological characteristics of data and the related information system. Such a mapping allows cost/benefit assessment and determination of optimal configuration of system and data characteristics to maximize value and profits. The framework is demonstrated through development of a model for tabular datasets, and the optimal design of dataset characteristics (such as time- span, desired quality-level, and the set of attributes to be included). The application of the model is illustrated using numerical examples

Advanced software techniques for space shuttle data management systems Final report

Airborne/spaceborn computer design and techniques for space shuttle data management system

Security problems of universal data management systems

Стаття присвячена розгляду проблеми безпеки універсальних систем управління даними. Зроблено аналіз та класифікація сучасних систем управління даними за різними критеріями. На основі аналізу літератури та використання досвіду створення корпоративних систем, визначені два підходи до організації універсальних платформ управління даними: використання мультимодельних систем та інтегрованих платформ управління даними. На підставі проведеного аналізу загроз та засобів захисту даних для SQL, NoSQL, NewSQL систем управління базами даних, сховищ даних (Data WareHouse), озер даних (Data Lake) та хмар даних визначені основні підходи до захисту даних кожної категорії продуктів. Визначені сучасні тенденції розвитку технологій управління даними та засобів захисту даних. Саме стрімкий розвиток NoSQL, NewSQL систем і обмін функціональністю між ними призвів до появи систем, що мають функції багатьох класів. Визначено проблеми захисту даних для мультимодельних СУБД та інтегрованих платформ даних та запропоновано шляхи їх подолання. Адже для універсальної платформи управління даними недостатньо простої інтеграції засобів безпеки різних типів систем управління даними, необхідні нові підходи. Для інтегрованих середовищ особливої актуальності набуває підхід Data Centric Security, який орієнтовано на захист критичних даних на всіх етапах їх обробки – від збору і передачі до аналізу і розміщення в сховищах даних. Організація доступу до даних через логічні вітрини даних з використанням семантичних технологій, онтологічних моделей даних забезпечує перетворення набору розрізнених даних в єдиний масив шляхом «віртуалізації даних». Обґрунтовано актуальність та доцільність застосування когнітивних технологій та штучного інтелекту в області інформаційної безпеки, що відкрило нові можливості для створення автоматизованих, «розумних» засобів безпеки систем управління даними. Таким системам притаманна здатність до самоаналізу і конфігурування. Застосування технології машинного навчання дозволяє виявляти слабкі місця в системі безпеки СУБД. Поєднання інтелектуальних рішень безпеки та управління з технологіями баз даних дозволить швидко реагувати на нові виклики в сфері захисту сховищ та озер даних різного типуThe article deals with the security of universal data management systems. The analysis and classification of modern data management systems by different criteria has been made. Based on the analysis of the literature and the experience of creating corporate systems, two approaches to the organization of universal data management systems have been identified: the use of multimodel systems and integrated data management platforms. Based on the analysis of threats and data protection tools for database management systems SQL, NoSQL, NewSQL, Data Warehouse, Data Lake and data clouds, the main approaches to data protection of each product category have been identified. The current trends in the development of data management technologies and data security have been identified. The development of NoSQL, NewSQL systems and the exchange of functionalities between them has led to the development of systems, which have functions of many classes. The problems of data protection for multimodel database management systems and for integrated data platforms have been identified and ways to overcome the identified problems have been suggested. For a universal data management platform, it is not enough to combine security features of different types of DBMS but new approaches are needed. The Data Centric Security approach is suitable for integrated environments; it is focused on protecting critical data at all stages of their processing - from collection and transmission to analysis and deployment in data warehouses. The organization of access to data through logical data marts using semantic technologies, ontological data models provides the transformation of a set of different types of data into a single array by "data virtualization". The article has substantiated the relevance and feasibility of the use of cognitive technologies and artificial intelligence in the field of information security, which opened new opportunities for the creation of automated, "smart" security tools for data management systems. Such systems have the ability to self-analyse and configure. The use of machine learning technology allows to identify weaknesses in the database security system. The combination of intelligent security and management solutions with database technologies will allow developers to respond quickly to new challenges in the protection of integrated data management systems of various type