Towards Continuous Data Collection from In-service Products: Exploring the Relation Between Data Dimensions and Collection Challenges

Anas Dakkak, Hongyi Zhang, D. I. Mattos, Jan Bosch, H. H. Olsson
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引用次数: 5

Abstract

Data collected from in-service products play an important role in enabling software-intensive embedded systems suppliers to embrace data-driven practices. Data can be used in many different ways such as to continuously learn and improve the product, enhance post-deployment services, reduce operational cost or create a better user experience. While there is no shortage of possible use cases leveraging data from in-service products, software-intensive embedded systems companies struggle to continuously collect data from their in-service products. Often, data collection is done in an ad-hoc way and targeting specific use cases or needs. Besides, few studies have investigated data collection challenges in relation to the data dimensions, which are the minimum set of quantifiable data aspects that can define software-intensive embedded product data from a collection point of view. To help address data collection challenges, and to provide companies with guidance on how to improve this process, we conducted a case study at a large multinational telecommunications supplier focusing on data characteristics and collection challenges from the Radio Access Networks (RAN) products. We further investigated the relations of these challenges to the data dimensions to increase our understanding of how data dominions contribute to the challenges.
面向在役产品的连续数据收集:探索数据维度与收集挑战之间的关系
从现役产品中收集的数据在使软件密集型嵌入式系统供应商接受数据驱动实践方面发挥着重要作用。数据可以以许多不同的方式使用,例如持续学习和改进产品,增强部署后服务,降低运营成本或创造更好的用户体验。虽然不乏利用在役产品数据的可能用例,但软件密集型嵌入式系统公司仍在努力从其在役产品中持续收集数据。通常,数据收集以特别的方式完成,并针对特定的用例或需求。此外,很少有研究调查与数据维度相关的数据收集挑战,数据维度是可以从收集的角度定义软件密集型嵌入式产品数据的可量化数据方面的最小集合。为了帮助解决数据收集挑战,并为公司提供如何改进这一过程的指导,我们对一家大型跨国电信供应商进行了案例研究,重点关注无线接入网络(RAN)产品的数据特征和收集挑战。我们进一步研究了这些挑战与数据维度之间的关系,以加深我们对数据领域如何促成这些挑战的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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