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Data Science is an emerging field of science, which requires a multi-disciplinary approach and is based on the Big Data and data intensive technologies that both provide a basis for effective use of the data driven research and economy models. Modern data driven research and industry require new types of specialists that are capable to support all stages of the data lifecycle from data production...
This paper presents the Data Science Model Curriculum (MC-DS) that is based on the Data Science Competence Framework and Data Science Body of Knowledge defined in EDISON Data Science Framework (EDSF). MC-DS follows a competence-based curriculum design approach grounded in the Data Science competences (CD-DS) defined in EDSF and correspondingly defined Learning Outcomes (LO). The DSBoK provides a basis...
DevOps teams have to consider many technology and platform aspects when developing, deploying and operating cloud based applications: application deployments need to work everywhere on different cloud platforms, identities need to come from anywhere, and networks need to connect to anyone. The CYCLONE middleware is a holistic middleware stack that allows deploying and managing cloud based applications...
This paper presents results of the ongoing development of the Intercloud Security Framework (ICSF), that is a part of the Intercloud Architecture Framework (ICAF), and provides an architectural basis for building security infrastructure services for multi-cloud applications. The paper refers to general use case of the data intensive applications that indicate need for multi-cloud applications platforms...
Nowadays, governmental and non-governmental health organisations and insurance companies invest in integrating an individual's genetic information to their daily practices. In this paper, we focus on an emerging area of genome analysis, called Disease Susceptibility (DS), from which an individual's susceptibility to a disease is calculated by using her genetic information. Recent work by Danezis et...
Data Science is becoming a field connecting multi-year development in areas such as Big Data and Data Analytics, and also applied domains like Bioengineering. Data Science education programs are rapidly being created on all levels. Usually it happens through reuse or renaming and can result in curricula that lack proper balance of competences, which balance is necessary for future data scientists...
This paper presents results of the ongoing development of CYCLONE as a platform for scientific applications in heterogeneous multi-cloud/multi-provider environment. In particular, we focus on QoS management of the multi-cloud applications within CYCLONE. A challenging factor for application deployment and exploitation within the CYCLONE infrastructure is its highly dynamic nature, which raises the...
Data Science is an emerging field of science, which requires a multi-disciplinary approach and should be built with a strong link to emerging Big Data and data driven technologies, and consequently needs re-thinking and re-design of both traditional educational models and existing courses. The education and training of Data Scientists currently lacks a commonly accepted, harmonized instructional model...
eXtensible Access Control Markup Language (XACML) allows for flexible management of authorisations and is particularly useful in settings where permissions change dynamically. However, it has been shown that policy evaluation in XACML may have scalability problems when policies become large and sophisticated in content. Among several proposals for designing efficient policy decision points for XACML...
This paper describes the general architecture and functional components of the cloud based Big Data Infrastructure (BDI). The proposed BDI architecture is based on the analysis of the emerging Big Data and data intensive technologies and supported by the definition of the Big Data Architecture Framework (BDAF) that defines the following components of the Big Data technologies: Big Data definition,...
Encryption is often viewed as a major drawback which hinders the performance of processing systems. This perception is not wrong; encrypted storage, memory and communications usually perform much slower than systems which process data in the clear. Big Data applications is no exception to the rule: it was designed with Volume and Velocity requirements in mind, and security (i.e. encryption) was initially...
Over the years, the Internet has become a central tool for society. The extent of its growth and usage raises critical issues associated with its design principles that need to be addressed before it reaches its limits. Many emerging applications have increasing requirements in terms of bandwidth, QoS and manageability. Moreover, applications such as Cloud computing and 3D-video streaming require...
The paper presents proposed Security Architecture for Open Collaborative Environment (OCE) being developed in the framework of the Collaboratory.nl (CNL) project with the intent to build a flexible, customer-driven security infrastructure for open collaborative applications. The architecture is based on extended use of emerging Web Services and Grid security technologies combined with concepts from...
This paper presents results of the ongoing development of the Cloud Services Delivery Infrastructure (CSDI) that provides a basis for infrastructure centric cloud services provisioning, operation and management in multi-cloud multi-provider environment defined as a Zero Touch Provisioning, Operation and Management (ZTP/ZTPOM) model. The presented work refers to use cases from data intensive research...
This paper presents results of the ongoing development of the CYCLONE as a platform for scientific applications in heterogeneous multi-cloud/multi-provider environment. The paper explains the general use case that provides a general motivation for the CYCLONE architecture and provides detailed analysis of the bioinformatics use cases that define specific requirements to the CYCLONE infrastructure...
Cloud Computing is developed as a new wave of ICT technologies, offering a common approach to on-demand provisioning of computation, storage and network resources that are generally referred to as infrastructure services. Most of currently available commercial cloud services are built and organized reflecting simple relations between single provider and customers with the simple security and trust...
Modern research and education networks need to solve two major tasks: (1) providing seamless access to their users, and (2) support new scientific and collaborative applications that are becoming increasingly complex and dynamic in their scale, use of distributed resources, and required advanced networking services. Rapid deployment and automation of new network services provisioning is becoming difficult...
This paper introduces XMPP and suggests how this technology might be used to help implement Intercloud communication. It gives an introduction to XMPP and how the architecture fits together as well as a discussion of the services it provides 'out of the box'. It then discusses secondary benefits of the protocol and highlights how XMPP could be an appropriate base protocol for implementing the Intercloud...
Various Cloud layers have to work in concert in order to manage and deploy complex multi-cloud applications, executing sophisticated workflows for Cloud resource deployment, activation, adjustment, interaction, and monitoring. While there are ample solutions for managing individual Cloud aspects (e.g. network controllers, deployment tools, and application security software), there are no well-integrated...
Grids provide collaborative environments for integration of the distributed heterogeneous resources and services running on different operating systems (OSs), e.g., Unix, Linux, Windows, embedded systems; Platforms, e.g., J2EE, .NET; and Devices, e.g., computers, instruments, sensors, databases, networks. Such environments need platform-independent technologies for services to communicate across various...
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