Sustaining Grass-roots Organizational Memories: Methods and Effects of Applying Managed Forgetting in Administrative Corporate Scenarios

维持基层组织记忆:在企业行政场景中应用管理遗忘的方法和效果

基本信息

  • 批准号:
    318396700
  • 负责人:
  • 金额:
    --
  • 依托单位:
  • 依托单位国家:
    德国
  • 项目类别:
    Priority Programmes
  • 财政年份:
    2016
  • 资助国家:
    德国
  • 起止时间:
    2015-12-31 至 2023-12-31
  • 项目状态:
    已结题

项目摘要

Introducing ‘forgetting’ into organizational knowledge management methods and practices promises to help overcoming information overload and to ease focusing on and refinding the really important things. Based on the results of the first phase, in this project, we will further investigate the concept of managed forgetting and its adequate framing, when applied in a corporate context. ‘Managed’ forgetting - an evidence-based routine of intentional forgetting that does not require conscious will - aims to translate cognitive mechanisms especially the focusing power of forgetting into the digital world, while at the same time complementing human remembering and forgetting. This is done by automatically collecting a variety of evidences for predicting the importance of information items and by combining the inferred information value - the ‘memory buoyancy’ - with a flexible set of forgetting actions. The further development of the concept Managed Forgetting requires comprehensive interdisciplinary research of its foundations and effects, of intelligent methods for its implementation as well as of its embedding into knowledge management and corporate processes. For achieving the objectives experts from three different domains – cognitive science, information analysis and retrieval and knowledge management – will closely work together in this project. Cognitive science experiments will deepen the understanding of relevant cognitive processes and investigate the effects of employing cognitive principles in organizational memories. Considering different temporal frames and the relationship between resources, we will develop multifaceted methods for information value assessment, which help in understanding the current item’s importance. The learned memory buoyancy will be used to develop advanced ‘forgetful’ information access methods for a grass-roots organizational memory, which meet the needs of administrative knowledge work processes. Finally, we will investigate the effects on the user, which incorporates empirical testing, validation in a real company context, and investigating the interactions between human and digital forgetting. Evaluation and experiments will play a crucial role in the project. Therefore, the Semantic Desktop is providing an ideal crystallization point for our interdisciplinary research: (a) It supports the typical activities of a knowledge worker, e.g. in administration; (b) it already maps the conceptual organization of the human cognitive system into a grass-roots organizational memory system via an personal ontology and (c) it provides a testbed for technical, cognitive and interdisciplinary research and experimentation. Based on the results for two research areas, namely ‘Arbeitsfeld 1’ and ‘Arbeitsfeld 2’ from the first phase of the project, we will further refine those results in the second phase, while focusing on ‘Arbeitsfeld 4’, i.e., exploring forgetful methods for the application area “Administration”.
将“遗忘”引入组织知识管理方法和实践,有望帮助克服信息过载,并减轻对真正重要的事情的关注和提炼。基于第一阶段的结果,在这个项目中,我们将进一步研究管理遗忘的概念和它的适当框架,当应用于企业环境。 “管理”遗忘-一种基于证据的故意遗忘程序,不需要有意识的意志-旨在将认知机制,特别是遗忘的聚焦能力转化为数字世界,同时补充人类的记忆和遗忘。这是通过自动收集各种证据来预测信息项的重要性,并将推断出的信息值(“记忆浮力”)与一组灵活的遗忘动作相结合来实现的。管理遗忘概念的进一步发展需要对其基础和影响进行全面的跨学科研究,实施智能方法以及将其嵌入知识管理和企业流程。为了实现这一目标,来自三个不同领域的专家-认知科学、信息分析和检索以及知识管理-将在这一项目中密切合作。认知科学实验将加深对相关认知过程的理解,并研究在组织记忆中采用认知原则的效果。考虑到不同的时间框架和资源之间的关系,我们将开发多方面的信息价值评估方法,这有助于理解当前项目的重要性。习得记忆浮力将用于开发先进的基层组织记忆“健忘”信息获取方法,满足行政知识工作流程的需求。最后,我们将研究对用户的影响,其中包括实证测试,在真实的公司背景下的验证,并研究人类和数字遗忘之间的相互作用。评估和实验将在项目中发挥关键作用。因此,语义桌面为我们的跨学科研究提供了一个理想的结晶点:(a)它支持知识工作者的典型活动,例如行政管理;(B)它已经通过个人本体将人类认知系统的概念组织映射到基层组织记忆系统中,以及(c)它提供了技术,认知和跨学科的研究和实验。基于第一阶段的“Arbeitsfeld 1”和“Arbeitsfeld 2”两个研究领域的结果,我们将在第二阶段进一步完善这些结果,同时关注“Arbeitsfeld 4”,即,探索“行政管理”应用领域的遗忘方法。

项目成果

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Professor Dr. Andreas Dengel其他文献

Professor Dr. Andreas Dengel的其他文献

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{{ truncateString('Professor Dr. Andreas Dengel', 18)}}的其他基金

metis II - Artificial intelligence methods for auto-completion of designs based on semantic building information (BIM) for supporting architects in early design phases.
metis II - 基于语义建筑信息 (BIM) 自动完成设计的人工智能方法,用于在早期设计阶段为建筑师提供支持。
  • 批准号:
    419390235
  • 财政年份:
    2019
  • 资助金额:
    --
  • 项目类别:
    Research Grants
"Scalable Methods of Text and Structure Recognition for the Full-Text Digitization of Historical Prints" Part 2: Layout Analysis
“历史印刷品全文数字化的文本和结构识别的可扩展方法”第 2 部分:布局分析
  • 批准号:
    394346204
  • 财政年份:
    2018
  • 资助金额:
    --
  • 项目类别:
    Research data and software (Scientific Library Services and Information Systems)
"Scalable Methods of Text and Structure Recognition for the Full-Text Digitization of Historical Prints" Part 1.B: Image Optimization
“用于历史印刷品全文数字化的文本和结构识别的可扩展方法”第 1.B 部分:图像优化
  • 批准号:
    394343055
  • 财政年份:
    2018
  • 资助金额:
    --
  • 项目类别:
    Research data and software (Scientific Library Services and Information Systems)
Linked Open Citation Database (LOC-DB) - Development of a Linked Open Data database for the indexing of citations of electronic and print media
链接开放引文数据库 (LOC-DB) - 开发链接开放数据数据库,用于电子和印刷媒体引文索引
  • 批准号:
    311018540
  • 财政年份:
    2016
  • 资助金额:
    --
  • 项目类别:
    Research data and software (Scientific Library Services and Information Systems)
metis - Knowledge-based search and query methods for accessing information of semantic models (BIM) to support searching in early design stages.
metis - 基于知识的搜索和查询方法,用于访问语义模型(BIM)信息以支持早期设计阶段的搜索。
  • 批准号:
    235841221
  • 财政年份:
    2013
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Neuronale Netze zur Beschreibung von Nachbarnetzen
用于描述邻近网络的神经网络
  • 批准号:
    5110362
  • 财政年份:
    1998
  • 资助金额:
    --
  • 项目类别:
    Priority Programmes
learning Cyclotron
学习回旋加速器
  • 批准号:
    442581111
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Research Grants

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非洲社会心理残疾人的全球草根运动
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深入了解黑草控制的根源:麦索罗看麦穗作物与杂草的化感相互作用。
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