Bridging the demand and the offer in data science

During the last several years, we have observed an exponential increase in the demand for Data Scientists in the job market. As a result, a number of trainings, courses, books, and university educational programs (both at undergraduate, graduate and postgraduate levels) have been labeled as “Big data” or “Data Science”; the fil‐rouge of each of them is the aim at forming people with the right competencies and skills to satisfy the business sector needs. In this paper, we report on some of the exercises done in analyzing current Data Science education offer and matching with the needs of the job markets to propose a scalable matching service, ie, COmpetencies ClassificatiOn (E‐CO‐2), based on Data Science techniques. The E‐CO‐2 service can help to extract relevant information from Data Science–related documents (course descriptions, job Ads, blogs, or papers), which enable the comparison of the demand and offer in the field of Data Science Education and HR management, ultimately helping to establish the profession of Data Scientist.publishedVersio

A Demo of Application Lifecycle Management for IoT Collaborative Neighborhood in the Fog

International audienceRegarding latency, privacy, resiliency and network scarcity management, only distributed approaches such as proposed by Fog Computing architecture can efficiently address the fantastic growth of the Internet of Things (IoT). IoT applications could be deployed and run hierarchically at different levels in an infrastructure ranging from centralized datacenters to the connected things themselves. Consequently, software entities composing IoT applications could be executed in many different configurations. The heterogeneity of the equipment and devices of the target infrastructure opens opportunities in the placement of the software entities, taking into account their requirements in terms of hardware, cyber-physical interactions and software dependencies. Once the most appropriate place has been found, software entities have to be deployed and run. Container-based virtualization has been considered to overpass the complexity of packaging, deploying and running software entities in a heterogeneous distributed infrastructure at the vicinity of the connected devices. This paper reports a practical experiment presented as a live demo that showcases a " Smart Bell in a Collaborative Neighborhood " IoT application in the Fog. Application Lifecycle Management (ALM) has been put in place based on Docker technologies to deploy and run micro-services in the context of Smart Homes operated by Orange

A Decision Support System for Planning and Operation of Maintenance and Customer Services in Electric Power Distribution Systems

This chapter aims to present the design and development of a decision support system (DSS) for the analysis, simulation, planning, and operation of maintenance and customer services in electric power distribution system (EPDS). The main objective of the DSS is to improve the decision‐making processes through visualization tools and simulation of real cases in the EPDS, in order to allow better planning in the short, medium, and long term. Therefore, the DSS helps managers and decision‐makers to reduce maintenance and operational costs, to improve system reliability, and to analyze new scenarios and conditions for system expansion planning. First, we introduce the key challenges faced by the decision‐makers in the planning and operation of maintenance and customer services in EPDS. Next, we discuss the benefits and the requirements for the DSS design and development, including use cases modeling and the software architecture. Afterwards, we present the capabilities of the DSS and discuss important decisions made during the implementation phases. We conclude the chapter with a discussion about the obtained results, pointing out the possible enhancements of the DSS, future extensions, and new use cases that may be addressed

A Distributed Sensor Data Search Platform for Internet of Things Environments

Recently, the number of devices has grown increasingly and it is hoped that, between 2015 and 2016, 20 billion devices will be connected to the Internet and this market will move around 91.5 billion dollars. The Internet of Things (IoT) is composed of small sensors and actuators embedded in objects with Internet access and will play a key role in solving many challenges faced in today's society. However, the real capacity of IoT concepts is constrained as the current sensor networks usually do not exchange information with other sources. In this paper, we propose the Visual Search for Internet of Things (ViSIoT) platform to help technical and non-technical users to discover and use sensors as a service for different application purposes. As a proof of concept, a real case study is used to generate weather condition reports to support rheumatism patients. This case study was executed in a working prototype and a performance evaluation is presented.Comment: International Journal of Services Computing (ISSN 2330-4472) Vol. 4, No.1, January - March, 201

PaaSword: A Data Privacy and Context-aware Security Framework for Developing Secure Cloud Applications - Technical and Scientific Contributions

Most industries worldwide have entered a period of reaping the benefits and opportunities cloud offers. At the same time, many efforts are made to address engineering challenges for the secure development of cloud systems and software.With the majority of software engineering projects today relying on the cloud, the task to structure end-to-end secure-by-design cloud systems becomes challenging but at the same time mandatory. The PaaSword project has been commissioned to address security and data privacy in a holistic way by proposing a context-aware security-by-design framework to support software developers in constructing secure applications for the cloud. This chapter presents an overview of the PaaSword project results, including the scientific achievements as well as the description of the technical solution. The benefits offered by the framework are validated through two pilot implementations and conclusions are drawn based on the future research challenges which are discussed in a research agenda

Informationstechnologische Unterstützung der Archivierung biographischer Interviews und Erinnerungszeugnisse

Traditionelle Gedächtnisinstitutionen - Archive, Bibliotheken und Museen - stehen vor der Herausforderung der digitalen Transformation. Insbesondere, da Inhalte aus unterschiedlichen Gründen nur zum Teil online verfügbar sind, während die externe Nachfrage nach der Nutzung der vorhandenen Archivinhalte ständig steigt. Der Beitrag befasst sich daher mit Ansatzpunkten und Zielen eines künftigen Arbeitsprogramms, das die genannten Herausforderungen adressiert

Evaluation of EDISON\u27s Data Science Competency Framework Through a Comparative Literature Analysis

During the emergence of Data Science as a distinct discipline, discussions of what exactly constitutes Data Science have been a source of contention, with no clear resolution. These disagreements have been exacerbated by the lack of a clear single disciplinary \u27parent.\u27 Many early efforts at defining curricula and courses exist, with the EDISON Project\u27s Data Science Framework (EDISON-DSF) from the European Union being the most complete. The EDISON-DSF includes both a Data Science Body of Knowledge (DS-BoK) and Competency Framework (CF-DS). This paper takes a critical look at how EDISON\u27s CF-DS compares to recent work and other published curricular or course materials. We identify areas of strong agreement and disagreement with the framework. Results from the literature analysis provide strong insights into what topics the broader community see as belonging in (or not in) Data Science, both at curricular and course levels. This analysis can provide important guidance for groups working to formalize the discipline and any college or university looking to build their own undergraduate Data Science degree or programs