Data & Knowledge Engineering最新文献

Goal modelling in aeronautics: Practical applications for aircraft and manufacturing designs 航空目标建模：飞机和制造设计的实际应用

IF 2.7 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Data & Knowledge Engineering

Pub Date : 2024-11-05 DOI: 10.1016/j.datak.2024.102375

Anouck Chan , Anthony Fernandes Pires , Thomas Polacsek , Stéphanie Roussel , François Bouissière , Claude Cuiller , Pierre-Eric Dereux

Traditional aircraft development follows a sequential approach: the aircraft is designed first, followed by the industrial system. This approach limits the industrial system’s performance due to constraints imposed by the pre-defined aircraft design. Collaborative approaches, however, advocate for simultaneous design of different products to create new opportunities. Within a project focused on co-designing aircraft and their industrial systems, we put goal modelling into practice to gain a comprehensive understanding of the objectives driving each system’s design and their interdependencies. The intention was to develop an approach for actively involving domain experts, even those lacking prior knowledge of Goal-Oriented Requirements Engineering (GORE).

This paper provides a detailed account of the iterative process employed to develop and refine our approach. For each iteration, we describe the organisation of modelling sessions with experts, the resulting models, and the collected feedback. We also report on the overall approach’s reception from both industry experts and academic participants. Furthermore, we highlight recommendations and research challenges that emerged from the encountered difficulties during the iterative process, suggesting avenues for further investigation and improvement.

传统的飞机研发采用顺序式方法：首先设计飞机，然后设计工业系统。由于预先确定的飞机设计所带来的限制，这种方法限制了工业系统的性能。而协作式方法则主张同时设计不同的产品，以创造新的机遇。在一个专注于飞机及其工业系统协同设计的项目中，我们将目标建模付诸实践，以全面了解驱动每个系统设计的目标及其相互依存关系。本文详细介绍了开发和完善我们的方法所采用的迭代过程。对于每一次迭代，我们都描述了与专家一起组织建模会议的情况、所产生的模型以及收集到的反馈。我们还报告了行业专家和学术参与者对整个方法的接受程度。此外，我们还强调了在迭代过程中遇到的困难所带来的建议和研究挑战，提出了进一步调查和改进的途径。

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引用次数: 0

Ethical reasoning methods for ICT: What they are and when to use them 信息和传播技术的伦理推理方法：它们是什么以及何时使用

IF 2.7 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Data & Knowledge Engineering

Pub Date : 2024-11-04 DOI: 10.1016/j.datak.2024.102373

Sergio España , Chris van der Maaten , Jens Gulden , Óscar Pastor

Information and communication technology (ICT) brings about numerous advantages across various domains of our lives. However, alongside these benefits, there is a growing awareness of its potential negative ethical, social, and environmental impacts. Consequently, stakeholders ranging from conceptual modellers to policy makers often find themselves grappling with ethical considerations stemming from ICT engineering and usage. This paper presents a review of 10 ethical reasoning methods suitable for the ICT domain. We have employed a method engineering technique to author metamodels for the methods, which were subsequently subjected to validation by experts proficient in the respective methods. Following a situational method engineering approach, we have also characterised each ethical reasoning method and validated the characterisation with the experts. This has allowed us to develop a tool that helps select the method that is most suitable for a given ethical reasoning situation. Furthermore, we deliberate on the practical application of ethical reasoning methods within conceptual modelling contexts. We are confident that we have laid the groundwork for further research into ethical reasoning of ICT, with a specific emphasis on its role during conceptual modelling.

信息与传播技术（ICT）为我们生活的各个领域带来了诸多好处。然而，在带来这些好处的同时，人们也越来越意识到它可能对伦理、社会和环境造成负面影响。因此，从概念模型设计者到政策制定者等利益相关者经常会发现自己正在努力解决信息与传播技术工程和使用过程中产生的伦理问题。本文综述了 10 种适合 ICT 领域的伦理推理方法。我们采用方法工程技术为这些方法创建元模型，随后由精通相关方法的专家对这些元模型进行验证。按照情境方法工程方法，我们还对每种伦理推理方法进行了特征描述，并与专家一起对特征描述进行了验证。这使我们能够开发一种工具，帮助选择最适合特定伦理推理情境的方法。此外，我们还讨论了伦理推理方法在概念建模中的实际应用。我们相信，我们已经为进一步研究信息与传播技术的伦理推理奠定了基础，并特别强调了伦理推理在概念建模过程中的作用。

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引用次数: 0

SSQTKG: A Subgraph-based Semantic Query Approach for Temporal Knowledge Graph SSQTKG：基于子图的时态知识图谱语义查询方法

IF 2.7 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Data & Knowledge Engineering

Pub Date : 2024-11-02 DOI: 10.1016/j.datak.2024.102372

Lin Zhu, Xinyi Duan, Luyi Bai

Real-world knowledge graphs are growing in size with the explosion of data and rapid expansion of knowledge. There are some studies on knowledge graph query, but temporal knowledge graph (TKG) query is still a relatively unexplored field. A temporal knowledge graph is a knowledge graph that contains temporal information and contains knowledge that is likely to change over time. It introduces a temporal dimension that can characterize the changes and evolution of entities and relationships at different points in time. However, in the existing temporal knowledge graph query, the entity labels are one-sided, which cannot accurately reflect the semantic relationships of temporal knowledge graphs, resulting in incomplete query results. For the processing of temporal information in temporal knowledge graphs, we propose a temporal frame filtering approach and measure the acceptability of temporal frames by the new definition sim_time based on the proposed three temporal frames and nine rules. For measuring the semantic relationship of predicates between entities, we vectorize the semantic similarity between predicates, i.e., edges, using the knowledge embedding model, and propose the new definition sim_pre to measure the semantic similarity of predicates. Based on these, we propose a new semantic temporal knowledge graph query method

{SSQ}_{TKG}

, and perform pruning operations to optimize the query efficiency of the algorithm based on connectivity. Extensive experiments show that

{SSQ}_{TKG}

can return more accurate and complete results that meet the query conditions in the semantic query and can improve the performance of the querying on the temporal knowledge graph.

随着数据的爆炸和知识的迅速扩展，现实世界中的知识图谱规模越来越大。目前已有一些关于知识图谱查询的研究，但时态知识图谱（TKG）查询仍是一个相对尚未开发的领域。时态知识图谱是一种包含时态信息的知识图谱，其中的知识可能会随着时间的推移而发生变化。它引入了一个时间维度，可以描述实体和关系在不同时间点上的变化和演化。然而，在现有的时态知识图谱查询中，实体标签是片面的，不能准确反映时态知识图谱的语义关系，导致查询结果不完整。针对时态知识图谱中时态信息的处理，我们提出了一种时态框架过滤方法，并根据提出的三个时态框架和九条规则，通过新定义 simtime 来衡量时态框架的可接受性。为了度量实体间谓词的语义关系，我们利用知识嵌入模型将谓词间的语义相似度（即边）矢量化，并提出了度量谓词语义相似度的新定义 simpre。在此基础上，我们提出了一种新的语义时态知识图谱查询方法 SSQTKG，并根据连接性进行剪枝操作以优化算法的查询效率。大量实验表明，SSQTKG 能返回更准确、更完整的符合语义查询条件的查询结果，并能提高时态知识图谱的查询性能。

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引用次数: 0

VarClaMM: A reference meta-model to understand DNA variant classification VarClaMM：了解 DNA 变异分类的参考元模型

IF 2.7 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Data & Knowledge Engineering

Pub Date : 2024-11-01 DOI: 10.1016/j.datak.2024.102370

Mireia Costa , Alberto García S. , Ana León , Anna Bernasconi , Oscar Pastor

Determining the significance of a DNA variant in patients’ health status – a complex process known as variant classification – is highly critical for precision medicine applications. However, there is still debate on how to combine and weigh diverse available evidence to achieve proper and consistent conclusions. Indeed, currently, there are more than 200 different variant classification guidelines available to the scientific community, aiming to establish a framework for standardizing the classification process. Yet, these guidelines are qualitative and vague by nature, hindering their practical application and potential automation. Consequently, more precise definitions are needed.

In this work, we discuss our efforts to create VarClaMM, a UML meta-model that aims to provide a clear specification of the key concepts involved in variant classification, serving as a common framework for the process. Through this accurate characterization of the domain, we were able to find contradictions or inconsistencies that might have an effect on the classification results. VarClaMM’s conceptualization efforts will lay the ground for the operationalization of variant classification, enabling any potential automation to be based on precise definitions.

确定 DNA 变异在患者健康状况中的重要性（这是一个复杂的过程，被称为变异分类）对于精准医疗的应用至关重要。然而，对于如何结合和权衡现有的各种证据以得出正确一致的结论，目前仍存在争议。事实上，目前科学界有 200 多份不同的变异体分类指南，旨在建立一个规范分类过程的框架。然而，这些指南在本质上是定性和模糊的，妨碍了它们的实际应用和潜在的自动化。在这项工作中，我们讨论了我们为创建 VarClaMM 所做的努力，VarClaMM 是一个 UML 元模型，旨在为变异体分类所涉及的关键概念提供清晰的规范，作为该过程的通用框架。通过对这一领域的准确描述，我们能够发现可能对分类结果产生影响的矛盾或不一致之处。VarClaMM 的概念化工作将为变体分类的操作化奠定基础，使任何潜在的自动化都能建立在精确定义的基础上。

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引用次数: 0

NoSQL document data migration strategy in the context of schema evolution 模式演进背景下的 NoSQL 文档数据迁移策略

IF 2.7 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Data & Knowledge Engineering

Pub Date : 2024-11-01 DOI: 10.1016/j.datak.2024.102369

Solomiia Fedushko , Roman Malyi , Yuriy Syerov , Pavlo Serdyuk

In Agile development, one approach cannot be chosen and used all the time. Constant updates and strategy changes are necessary. We want to show that combining several migration strategies is better than choosing only one. Also, we emphasize the need to consider the type of schema change. This paper introduces a novel approach designed to optimize the migration process for NoSQL databases. The approach represents a significant advancement in migration strategy planning, providing a quantitative framework to guide decision-making. By incorporating critical factors such as schema changes, database size, the necessity of data in search functionalities, and potential latency issues, the approach comprehensively evaluates the migration feasibility and identifies the optimal migration path. Unlike existing methodologies, this approach adapts to the dynamic nature of NoSQL databases, offering a scalable and flexible approach to migration planning.

在敏捷开发中，不可能一直选择和使用一种方法。不断更新和改变策略是必要的。我们希望证明，结合几种迁移策略比只选择一种迁移策略更好。此外，我们还强调需要考虑模式变更的类型。本文介绍了一种旨在优化 NoSQL 数据库迁移过程的新方法。该方法为指导决策提供了一个量化框架，是迁移策略规划领域的一大进步。通过纳入模式变更、数据库大小、搜索功能中数据的必要性和潜在延迟问题等关键因素，该方法全面评估了迁移的可行性，并确定了最佳迁移路径。与现有方法不同的是，这种方法适应 NoSQL 数据库的动态特性，为迁移规划提供了一种可扩展的灵活方法。

引用次数: 0

Change pattern relationships in event logs 事件日志中的更改模式关系

IF 2.7 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Data & Knowledge Engineering

Pub Date : 2024-10-15 DOI: 10.1016/j.datak.2024.102368

Jonas Cremerius, Hendrik Patzlaff, Mathias Weske

Process mining utilises process execution data to discover and analyse business processes. Event logs represent process executions, providing information about the activities executed. In addition to generic event attributes like activity name and timestamp, events might contain domain-specific attributes, such as a blood sugar measurement in a healthcare environment. Many of these values change during a typical process quite frequently. We refer to those as dynamic event attributes. Change patterns can be derived from dynamic event attributes, describing if the attribute values change from one activity to another. So far, change patterns can only be identified in an isolated manner, neglecting the chance of finding co-occuring change patterns. This paper provides an approach to identifying relationships between change patterns by utilising correlation methods from statistics. We applied the proposed technique on two event logs derived from the MIMIC-IV real-world dataset on hospitalisations in the US and evaluated the results with a medical expert. It turns out that relationships between change patterns can be detected within the same directly or eventually follows relation and even beyond that. Further, we identify unexpected relationships that are occurring only at certain parts of the process. Thus, the process perspective reveals novel insights on how dynamic event attributes change together during process execution. The approach is implemented in Python using the PM4Py framework.

流程挖掘利用流程执行数据来发现和分析业务流程。事件日志代表流程执行情况，提供有关所执行活动的信息。除了活动名称和时间戳等通用事件属性外，事件还可能包含特定领域的属性，如医疗环境中的血糖测量。在一个典型的流程中，其中许多值会频繁变化。我们将这些属性称为动态事件属性。变化模式可以从动态事件属性中推导出来，描述属性值是否从一个活动变化到另一个活动。迄今为止，变化模式只能以孤立的方式识别，忽略了发现共同发生的变化模式的机会。本文提供了一种利用统计学中的相关方法来识别变化模式之间关系的方法。我们将所提出的技术应用于从美国 MIMIC-IV 真实世界住院数据集中提取的两个事件日志，并与医学专家一起对结果进行了评估。结果表明，变化模式之间的关系可以在相同的直接或最终跟随关系中检测到，甚至可以超越这种关系。此外，我们还发现了一些意想不到的关系，这些关系只发生在流程的某些部分。因此，流程视角揭示了流程执行过程中动态事件属性如何共同变化的新见解。该方法使用 PM4Py 框架在 Python 中实现。

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引用次数: 0

Strategic redesign of business processes in the digital age: A framework 数字时代业务流程的战略再设计：一个框架

IF 2.7 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Data & Knowledge Engineering

Pub Date : 2024-10-05 DOI: 10.1016/j.datak.2024.102367

Fredrik Milani, Kateryna Kubrak, Juuli Nava

Organizations constantly seek ways to improve their business processes by using digital technologies as enablers. However, simply substituting an existing technology with a new one has limited value compared to using the capabilities of digital technologies to redesign business processes. Therefore, process analysts try to understand how the capabilities of digital technologies can enable the redesign of business processes. In this paper, we conduct a systematic literature review and examine 40 case studies where digital technologies were used to redesign business processes. We identified that, within the context of business process improvement, capabilities of digitalization, communication, analytics, digital representation, and connectivity can enable business process redesign. Furthermore, we note that these capabilities enable applying nine redesign heuristics. Based on our review, we map how each capability can facilitate the implementation of specific redesign heuristics. Finally, we illustrate how such a capability-driven approach can be applied to Metaverse as an example of a digital technology. Our mapping and classification framework can aid analysts in identifying candidate redesigns that capitalize on the capabilities of digital technologies.

各组织都在不断寻求利用数字技术改进业务流程的方法。然而，与利用数字技术的功能重新设计业务流程相比，简单地用新技术取代现有技术的价值有限。因此，流程分析师试图了解数字技术的功能如何能够促进业务流程的重新设计。在本文中，我们进行了系统的文献回顾，并研究了 40 个利用数字技术重新设计业务流程的案例。我们发现，在业务流程改进的背景下，数字化、通信、分析、数字表示和连接等能力可以促进业务流程的重新设计。此外，我们还注意到，这些能力有助于应用九种重新设计启发式方法。在回顾的基础上，我们描绘了每种能力如何促进特定再设计启发式方法的实施。最后，我们举例说明了如何将这种以能力为导向的方法应用于 Metaverse 这种数字技术。我们的映射和分类框架可以帮助分析人员确定可利用数字技术能力的候选再设计方案。

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引用次数: 0

Timed alignments with mixed moves 混合动作的定时排列

IF 2.7 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Data & Knowledge Engineering

Pub Date : 2024-09-28 DOI: 10.1016/j.datak.2024.102366

Neha Rino , Thomas Chatain

We study conformance checking for timed models, that is, process models that consider both the sequence of events that occur, as well as the timestamps at which each event is recorded. Time-aware process mining is a growing subfield of research, and as tools that seek to discover timing-related properties in processes develop, so does the need for conformance-checking techniques that can tackle time constraints and provide insightful quality measures for time-aware process models. One of the most useful conformance artefacts is the alignment, that is, finding the minimal changes necessary to correct a new observation to conform to a process model. In this paper, we extend the notion of timed distance from a previous work where an edit on an event’s timestamp came in two types, depending on whether or not it would propagate to its successors. Here, these different types of edits have a weighted cost each, and the ratio of their costs is denoted by

α

. We then solve the purely timed alignment problem in this setting for a large class of these weighted distances (corresponding to

α \in {1} \cup [2, \infty)

). For these distances, we provide linear time algorithms for both distance computation and alignment on models with sequential causal processes.

我们研究的是定时模型的一致性检查，即同时考虑事件发生顺序和记录每个事件的时间戳的流程模型。时间感知流程挖掘是一个不断发展的研究子领域，随着试图发现流程中与时间相关属性的工具的发展，人们对能够解决时间限制并为时间感知流程模型提供有洞察力的质量度量的一致性检查技术的需求也在不断增长。最有用的一致性工件之一是对齐，也就是找到修正新观察结果所需的最小变化，使其符合流程模型。在本文中，我们扩展了以前工作中的定时距离概念，在以前的工作中，对事件时间戳的编辑分为两种类型，这取决于编辑是否会传播给后继者。在这里，这些不同类型的编辑各有一个加权成本，它们的成本比用 α 表示。然后，我们在这种情况下求解了一大类加权距离（对应于 α∈{1}∪[2,∞)）的纯定时对齐问题。对于这些距离，我们提供了在具有连续因果过程的模型上进行距离计算和配准的线性时间算法。

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引用次数: 0

State-transition-aware anomaly detection under concept drifts 概念漂移下的状态转换感知异常检测

IF 2.7 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Data & Knowledge Engineering

Pub Date : 2024-09-28 DOI: 10.1016/j.datak.2024.102365

Bin Li, Shubham Gupta, Emmanuel Müller

Detecting temporal abnormal patterns over streaming data is challenging due to volatile data properties and the lack of real-time labels. The abnormal patterns are usually hidden in the temporal context, which cannot be detected by evaluating single points. Furthermore, the normal state evolves over time due to concept drifts. A single model does not fit all data over time. Autoencoders have recently been applied for unsupervised anomaly detection. However, they are trained on a single normal state and usually become invalid after distributional drifts in the data stream. This paper uses an Autoencoder-based approach STAD for anomaly detection under concept drifts. In particular, we propose a state-transition-aware model to map different data distributions in each period of the data stream into states, thereby addressing the model adaptation problem in an interpretable way. In addition, we analyzed statistical tests to detect the drift by examining the sensitivity and powers. Furthermore, we present considerable ways to estimate the probability density function for comparing the distributional similarity for state transitions. Our experiments evaluate the proposed method on synthetic and real-world datasets. While delivering comparable anomaly detection performance as the state-of-the-art approaches, STAD works more efficiently and provides extra interpretability. We also provide insightful analysis of optimal hyperparameters for efficient model training and adaptation.

由于数据的不稳定性和缺乏实时标签，在流数据中检测时间异常模式具有挑战性。异常模式通常隐藏在时间上下文中，无法通过评估单个点来检测。此外，由于概念漂移，正常状态会随时间发生变化。单一模型并不适合随时间变化的所有数据。自动编码器最近被应用于无监督异常检测。然而，它们是在单一正常状态下训练的，通常在数据流的分布漂移后就会失效。本文将基于自动编码器的 STAD 方法用于概念漂移下的异常检测。特别是，我们提出了一种状态转换感知模型，将数据流每个周期的不同数据分布映射为状态，从而以可解释的方式解决了模型适应问题。此外，我们还分析了统计检验，通过检验灵敏度和幂来检测漂移。此外，我们还提出了大量估算概率密度函数的方法，用于比较状态转换的分布相似性。我们的实验在合成数据集和真实数据集上对所提出的方法进行了评估。在提供与最先进方法相当的异常检测性能的同时，STAD 的工作效率更高，并提供了额外的可解释性。我们还对高效模型训练和适应的最佳超参数进行了深入分析。

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引用次数: 0

Reasoning on responsibilities for optimal process alignment computation 最佳流程对齐计算的责任推理

IF 2.7 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Data & Knowledge Engineering

Pub Date : 2024-09-19 DOI: 10.1016/j.datak.2024.102353

Matteo Baldoni, Cristina Baroglio, Elisa Marengo, Roberto Micalizio

Process alignment aims at establishing a matching between a process model run and a log trace. To improve such a matching, process alignment techniques often exploit contextual conditions to enable computations that are more informed than the simple edit distance between model runs and log traces. The paper introduces a novel approach to process alignment which relies on contextual information expressed as responsibilities. The notion of responsibility is fundamental in business and organization models, but it is often overlooked. We show the computation of optimal alignments can take advantage of responsibilities. We leverage on them in two ways. First, responsibilities may sometimes justify deviations. In these cases, we consider them as correct behaviors rather than errors. Second, responsibilities can either be met or neglected in the execution of a trace. Thus, we prefer alignments where neglected responsibilities are minimized.

The paper proposes a formal framework for responsibilities in a process model, including the definition of cost functions for computing optimal alignments. We also propose a branch-and-bound algorithm for optimal alignment computation and exemplify its usage by way of two event logs from real executions.

流程对齐的目的是在流程模型运行和日志跟踪之间建立匹配。为了改进这种匹配，流程对齐技术通常会利用上下文条件来进行计算，这种计算比模型运行和日志跟踪之间的简单编辑距离更有依据。本文介绍了一种新颖的流程对齐方法，它依赖于以责任表示的上下文信息。责任概念是业务和组织模型的基本要素，但却经常被忽视。我们表明，最优对齐的计算可以利用责任。我们通过两种方式利用责任。首先，责任有时会证明偏离是合理的。在这种情况下，我们将其视为正确的行为而不是错误。其次，在跟踪执行过程中，责任既可能被履行，也可能被忽略。本文提出了流程模型中责任的正式框架，包括计算最优排列的成本函数定义。我们还提出了最优排列计算的分支和边界算法，并通过两个实际执行的事件日志来举例说明其用法。

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引用次数: 0