50,106 research outputs found
Coordinating Knowledge Work in Multi-Team Programs: Findings from a Large-Scale Agile Development Program
Software development projects have undergone remarkable changes with the
arrival of agile development methods. While intended for small, self-managing
teams, these methods are increasingly used also for large development programs.
A major challenge in programs is to coordinate the work of many teams, due to
high uncertainty in tasks, a high degree of interdependence between tasks and
because of the large number of people involved. This revelatory case study
focuses on how knowledge work is coordinated in large-scale agile development
programs by providing a rich description of the coordination practices used and
how these practices change over time in a four year development program with 12
development teams. The main findings highlight the role of coordination modes
based on feedback, the use of a number of mechanisms far beyond what is
described in practitioner advice, and finally how coordination practices change
over time. The findings are important to improve the outcome of large
knowledge-based development programs by tailoring coordination practices to
needs and ensuring adjustment over time.Comment: To appear in Project Management Journa
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Skills and Knowledge for Data-Intensive Environmental Research.
The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap
Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure
Big data research has attracted great attention in science, technology,
industry and society. It is developing with the evolving scientific paradigm,
the fourth industrial revolution, and the transformational innovation of
technologies. However, its nature and fundamental challenge have not been
recognized, and its own methodology has not been formed. This paper explores
and answers the following questions: What is big data? What are the basic
methods for representing, managing and analyzing big data? What is the
relationship between big data and knowledge? Can we find a mapping from big
data into knowledge space? What kind of infrastructure is required to support
not only big data management and analysis but also knowledge discovery, sharing
and management? What is the relationship between big data and science paradigm?
What is the nature and fundamental challenge of big data computing? A
multi-dimensional perspective is presented toward a methodology of big data
computing.Comment: 59 page
Multi-agent systems for power engineering applications - part 1 : Concepts, approaches and technical challenges
This is the first part of a 2-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part 1 of the paper examines the potential value of MAS technology to the power industry. In terms of contribution, it describes fundamental concepts and approaches within the field of multi-agent systems that are appropriate to power engineering applications. As well as presenting a comprehensive review of the meaningful power engineering applications for which MAS are being investigated, it also defines the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part 2 of the paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented
Over-the-air software updates in the internet of things : an overview of key principles
Due to the fast pace at which IoT is evolving, there is an increasing need to support over-theair software updates for security updates, bug fixes, and software extensions. To this end, multiple over-the-air techniques have been proposed, each covering a specific aspect of the update process, such as (partial) code updates, data dissemination, and security. However, each technique introduces overhead, especially in terms of energy consumption, thereby impacting the operational lifetime of the battery constrained devices. Until now, a comprehensive overview describing the different update steps and quantifying the impact of each step is missing in the scientific literature, making it hard to assess the overall feasibility of an over-the-air update. To remedy this, our article analyzes which parts of an IoT operating system are most updated after device deployment, proposes a step-by-step approach to integrate software updates in IoT solutions, and quantifies the energy cost of each of the involved steps. The results show that besides the obvious dissemination cost, other phases such as security also introduce a significant overhead. For instance, a typical firmware update requires 135.026 mJ, of which the main portions are data dissemination (63.11 percent) and encryption (5.29 percent). However, when modular updates are used instead, the energy cost (e.g., for a MAC update) is reduced to 26.743 mJ (48.69 percent for data dissemination and 26.47 percent for encryption)
Report on the Third Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE3)
This report records and discusses the Third Workshop on Sustainable Software
for Science: Practice and Experiences (WSSSPE3). The report includes a
description of the keynote presentation of the workshop, which served as an
overview of sustainable scientific software. It also summarizes a set of
lightning talks in which speakers highlighted to-the-point lessons and
challenges pertaining to sustaining scientific software. The final and main
contribution of the report is a summary of the discussions, future steps, and
future organization for a set of self-organized working groups on topics
including developing pathways to funding scientific software; constructing
useful common metrics for crediting software stakeholders; identifying
principles for sustainable software engineering design; reaching out to
research software organizations around the world; and building communities for
software sustainability. For each group, we include a point of contact and a
landing page that can be used by those who want to join that group's future
activities. The main challenge left by the workshop is to see if the groups
will execute these activities that they have scheduled, and how the WSSSPE
community can encourage this to happen
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