{"title":"Selected Topics on Information Management in Complex Systems: Editorial Introduction to Issue 24 of CSIMQ","authors":"Erika Nazaruka","doi":"10.7250/csimq.2020-24.00","DOIUrl":null,"url":null,"abstract":"Complex systems consist of multiple interacting parts; some of them (or even all of them) may also be systems. While performing their tasks, these parts operate with multiple data and information flows. Data are gathered, created, transferred, and analyzed. Information based on the analyzed data is assessed and taken into account during decision making. Different types of data and a large number of data flows can be considered as one of the sources of system complexity. Thus, information management, including data control, is an important aspect of complex systems development and management. According to ISO/IEC/IEEE 15288:2015, “the purpose of the Information Management Process is to generate, obtain, confirm, transform, retain, retrieve, disseminate and dispose of information, to designated stakeholders…”. Information management strategies consider the scope of information, constrains, security controls and information life cycle. This means that information management activities should be implemented starting from the level of primitive data gathering and ending with enterprise-level decision making. The articles, which have been recommended by reviewers for this issue of CSIMQ, present contributions in different aspects of information management in complex systems, namely, implementation of harmful environment monitoring and data transmitting by Internet-of-Things (IoT) systems, analysis of technological and organizational means for mitigating issues related to information security and users’ privacy that can lead to changes in corresponding systems’ processes, organization and infrastructure, as well as assessment of potential benefits that a controlled (i.e. based on the up-to-date information) change process can bring to an enterprise.","PeriodicalId":416219,"journal":{"name":"Complex Syst. Informatics Model. Q.","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Complex Syst. Informatics Model. Q.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7250/csimq.2020-24.00","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Complex systems consist of multiple interacting parts; some of them (or even all of them) may also be systems. While performing their tasks, these parts operate with multiple data and information flows. Data are gathered, created, transferred, and analyzed. Information based on the analyzed data is assessed and taken into account during decision making. Different types of data and a large number of data flows can be considered as one of the sources of system complexity. Thus, information management, including data control, is an important aspect of complex systems development and management. According to ISO/IEC/IEEE 15288:2015, “the purpose of the Information Management Process is to generate, obtain, confirm, transform, retain, retrieve, disseminate and dispose of information, to designated stakeholders…”. Information management strategies consider the scope of information, constrains, security controls and information life cycle. This means that information management activities should be implemented starting from the level of primitive data gathering and ending with enterprise-level decision making. The articles, which have been recommended by reviewers for this issue of CSIMQ, present contributions in different aspects of information management in complex systems, namely, implementation of harmful environment monitoring and data transmitting by Internet-of-Things (IoT) systems, analysis of technological and organizational means for mitigating issues related to information security and users’ privacy that can lead to changes in corresponding systems’ processes, organization and infrastructure, as well as assessment of potential benefits that a controlled (i.e. based on the up-to-date information) change process can bring to an enterprise.