论文标题

部分可观测时空混沌系统的无模型预测

Editorial: Special Issue on Collaborative Aspects of Open Data in Software EngineeringJohan

论文作者

Linåker, Johan, Runeson, Per, Zuiderwijk, Anneke, Brock, Amanda

论文摘要

高质量的数据对于软件工程师设计和实施当今的软件,作为机器学习算法以及基于可视化和基于分析的功能的输入变得越来越重要。开放数据 - 即,在许可证下共享的数据,该数据使用户有权学习,处理和分配数据并出于任何目的 - 提供了一种解决此需求的机制。数据可能来自多种来源,无论是政府机构的人群,共享还是在商业实体之间共享,并且无疑是当今公共部门,商业和行业的所有业务和收入模型所固有的。在此访客社论中,有关软件工程中开放数据的协作方面的特刊,我们探讨了软件工程中开放数据的协作方面。我们强调了这些方面如何使组织受益,可能存在哪些挑战以及如何根据当前实践来解决这些挑战,并介绍本期特刊中包含的四篇论文。

High-quality data has become increasingly important to software engineers in designing and implementing today's software, for example, as an input to machine-learning algorithms and visualisation- and analytics-based features. Open data - i.e., data shared under a licence that gives users the right to study, process, and distribute the data to anyone and for any purpose - offers a mechanism to address this need. Data may originate from multiple sources, whether crowdsourced, shared by government agencies, or shared between commercial entities, and is undoubtedly inherent to all business and revenue models across the public sector, business and industry today. In this guest editorial for the Special Issue on Collaborative Aspects of Open Data in Software Engineering, we explore the collaborative aspects of open data in software engineering. We highlight how these aspects can benefit organisations, what challenges may exist and how these may be addressed based on current practice, and introduce the four papers included in this special issue.

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