Blockchain logging for process mining: a systematic review

Considerable progress was forcasted for collaborative business processes with the rise of blockchain programmable platforms. One of the saliant promises was auditable traces of business process execution, but practically that has posed challenges specially with regard to blockchain logs’ structure who turned out to be inadequate for process mining techniques. Approaches to answer this issue have started to emerge in the literature, some focusing on the creation process of event logs and others dealing with their retrieval from the blockchain. This work outlines the generic steps required to solve these challenges and analyzes findings in these approaches with a consideration for efficiency and future research directions

Towards a process-oriented analysis of blockchain data

Blockchains sequentially store the history of transactional information, in a virtually immutable and distributed way. Moreover, second-generation blockchains such as Ethereum are programmable environments, and every operation invocation towards the smart contracts corresponds to a transaction sequentially collated in the ledgers. They thus allow for the controlled enactment of multi-party processes as well as the immutable recording of their distributed execution. Despite the verification, tracking, and monitoring of such blockchain-enabled processes appears paramount, a formal and implemented framework encompassing those aspects is still a mostly unexplored research avenue. The talk revolves around the current state of the art, as well as the opportunities and challenges that arise when it comes to conducting a process-oriented analysis on data stemming from blockchains, from a representation and modelling perspective

Advancements and Challenges in Object-Centric Process Mining: A Systematic Literature Review

Recent years have seen the emergence of object-centric process mining techniques. Born as a response to the limitations of traditional process mining in analyzing event data from prevalent information systems like CRM and ERP, these techniques aim to tackle the deficiency, convergence, and divergence issues seen in traditional event logs. Despite the promise, the adoption in real-world process mining analyses remains limited. This paper embarks on a comprehensive literature review of object-centric process mining, providing insights into the current status of the discipline and its historical trajectory

Clinical Interactions in Electronic Medical Records Towards the Development of a Token-Economy Model

The use of electronic medical records (EMRs) plays a crucial role in the successful implementation of the Universal Healthcare Law which promises quality and affordable healthcare to all Filipinos. Consequently, the current adoption of EMRs should be studied from the perspective of the healthcare provider. As most studies look into use of EMRs by doctors or patients, there are very few that extend studies to look at possible interaction of doctor and patient in the same EMR environment. Understanding this interaction paves the way for possible incentives that will increase the use and adoption of the EMR. This study uses process mining to understand simulated doctor-patient interaction, with the goal of developing interaction features and a token economy framework to increase EMR adoption. Results from the process mining showed that current EMR interaction remains low, and highlighted the need for interaction features to promote preventive healthcare. Moreover, process mining from the simulated logs showed that consistency and time are important factors in encouraging usage. Activity category, relative frequency of activity, relative case frequency of activity and average time spent on activity are features that may serve as the foundation for a token economy framework for EMRs

Securing, Standardizing, and Simplifying Electronic Health Record Audit Logs Through Permissioned Blockchain Technology

Audit logs perform critical functions in electronic health record (EHR) systems. They provide a chronological record of all operations performed in an EHR, allowing health care organizations to track EHR usage, hold system users accountable for their interactions with patient records, detect anomalous and potentially malicious behavior in the system, protect patient privacy, and develop insight into workflows and interactions among system users. However, several problems exist with the way that current state-of-the-art EHR technology handles audit data. Specifically, current systems complicate the collection and analysis of audit logs because they lack an interoperable audit log structure, spread audit log data from different EHR applications across multiple data repositories, and often fail to record all useful information about events in the EHR. Permissioned blockchain technology offers two opportunities to mitigate these issues. First, smart contracts running on the blockchain can impose an interoperable structure on audit log data, both within single health care organizations and across all organizations participating in the network. Second, the blockchain ledger constitutes a consolidated repository for all audit log data at each organization, simplifying the collection of data for analysis. AuditChain, the prototype system I present in this thesis, leverages Hyperleger Fabric\u27s permissioned blockchain technology to address these issues of audit log interoperability, content, structure, and consolidation. Specifically, AuditChain uses the blockchain ledger and smart contracts to standardize audit log content, simplify access to audit log data, and ensure that audit logs contain all necessary and useful information

Anomali Data Mining Menggunakan Metode K-Means Dalam Penilaian Mahasiswa Terhadap Pelayanan Prodi

Cluster analysis is a data mining technique that aims to identify a group of objects that have the same characteristics. The number of groups that can be identified depends on the amount of data and the type of object, so that data problems arise when there is a change to a number of redundant data, but not all of it is changed where the data above is repeatedly made into one table with a different code as the primary key and there are anomalies Insertion, so K-means is one method of clustering data which is divided into the form of one or more clusters/groups that have the same characteristics. Student data clustering uses the k-means method, consisting of student assessments. This study uses student assessment data. Then it was concluded that the assessment group was based on reliability aspects: the ability of lecturers, education staff and administrators to provide services, responsiveness aspects: the willingness of lecturers, education staff and administrators to help students and provide services quickly, aspects of certainty ( assurance): the ability of lecturers, staff and administrators to give confidence to students that the services provided are in accordance with the provisions, aspects of empathy (empathy): the willingness/concern of lecturers, staff and managers to give attention to students, tangibles aspects: students' assessment of the adequacy , accessibility, quality of facilities and infrastructure from the grouping results based on reliability, responsiveness, assurance and empathy data

CEPchain: A graphical model-driven solution for integrating complex event processing and blockchain

Blockchain provides an immutable distributed ledger for storing transactions. One of the challenges of blockchain is the particular processing of dynamic queries due to accumulating costs. Complex Event Processing (CEP) provides efficient and effective support for this in a way, however, that is difficult to integrate with blockchain. This paper addresses the research challenges of integrating blockchain with CEP. More specifically, we envision an effective development environment in which (i) event-driven smart contracts are modeled in a graphical way, which are, in turn, (ii) automatically transformed into complementary code that is deployed in both a CEP engine and a blockchain network, and then (iii) executed on off-chain CEP applications which, connected to different data sources and sinks, automatically invoke smart contracts when event pattern conditions are met. We follow a classic systems engineering approach for defining the concepts of our system, called CEPchain, which addresses the described requirements. CEPchain was evaluated using a real-world case study for vaccine delivery, which requires an unbroken cold chain. The results demonstrate that our approach can be applied without requiring experts on event processing and smart contract languages. Our contribution simplifies the design of integrated CEP and blockchain functionality by hiding implementation details and supporting efficient deployment.This work was supported by the Spanish Ministry of Science and Innovation under the ‘‘Estancias de movilidad en el extranjero José Castillejo para jóvenes doctores’’ program [grant number CAS19/00241], and the Spanish Ministry of Science and Innovation and the European Regional Development Funds under project FAME [grant number RTI2018-093608-B-C33]. The authors would like to thank Orlenys López-Pintado for his help with the Caterpillar tool and his insightful comments. Juan Boubeta-Puig would also like to thank the Institute for Information Business for their hospitality when visiting them at the Vienna University of Economics and Business, Austria, where part of this work was developed