The document discusses process discovery and conformance checking. It begins with an introduction to different roles of process models and examples of process discovery on real event logs. It then covers topics like replay, conformance checking, and analyzing models based on criteria like fitness and simplicity. Process discovery algorithms discussed include state-based regions and language-based regions approaches. The document explains how conformance checking involves replaying traces and calculating alignments between event logs and models.
Discovering Petri Nets: Evidence-Based Business Process ManagementWil van der Aalst
Invited Talk for the Carl Adam Petri Memorial Symposium, February 2010, Berlin, Germany
Carl Adam Petri was one of the most influential computer scientists of our time. This symposium commemorated the life and work of Petri. See http://www2.informatik.hu-berlin.de/top/lehre/petriweb/.
Process Mining: Understanding and Improving Desire Lines in Big DataWil van der Aalst
We are pleased to announce the lecture: “Process Mining: Understanding and Improving Desire Lines in Big Data”
in honour of doctor honoris causa Wil van der Aalst.
Wednesday May 30th - 10.00 a.m. - 12 a.m.,
Hasselt University, campus Diepenbeek (Agoralaan, building D) - auditorium H5
The Faculty of Business Economics of Hasselt University is pleased to invite you to the lecture
“Process Mining: Understanding and Improving Desire Lines in Big Data”.
This lecture is organised to honour prof. dr. Wil van der Aalst, on whom the degree of ‘doctor honoris causa’ will be conferred by Hasselt University, Faculty of Business Economics (promotor prof. Koen Vanhoof). Professor van der Aalst is a full professor of Information Systems at the Technische Universiteit Eindhoven (TU/e). Currently he is also an adjunct professor at Queensland University of Technology (QUT).His research interests include workflow management, process mining, Petri nets, business process management, process modeling, and process analysis. Many of his ideas have influenced researchers, software developers and standardization committees working on process support.
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Keynote at 18th International Conference on Cooperative Information Systems (...Wil van der Aalst
The Software as a Service (SaaS) paradigm is particularly interesting for situations where many organizations need to support similar processes. For example, municipalities, courts, rental agencies, etc. support highly similar processes. However, despite these similarities, there is also the need to allow for local variations in a controlled manner. Therefore, cloud infrastructures should provide configurable services such that products and processes can be customized while sharing commonalities. Configurable and executable process models are essential to realize such infrastructures. This will finally transform reference models from "paper tigers" (reference modeling a la SAP, ARIS, etc.) into an "executable reality". Moreover, "configurable services in the cloud" enable cross-organizational process mining. This way, organizations can learn from each other and improve their processes.
Discovering Petri Nets: Evidence-Based Business Process ManagementWil van der Aalst
Invited Talk for the Carl Adam Petri Memorial Symposium, February 2010, Berlin, Germany
Carl Adam Petri was one of the most influential computer scientists of our time. This symposium commemorated the life and work of Petri. See http://www2.informatik.hu-berlin.de/top/lehre/petriweb/.
Process Mining: Understanding and Improving Desire Lines in Big DataWil van der Aalst
We are pleased to announce the lecture: “Process Mining: Understanding and Improving Desire Lines in Big Data”
in honour of doctor honoris causa Wil van der Aalst.
Wednesday May 30th - 10.00 a.m. - 12 a.m.,
Hasselt University, campus Diepenbeek (Agoralaan, building D) - auditorium H5
The Faculty of Business Economics of Hasselt University is pleased to invite you to the lecture
“Process Mining: Understanding and Improving Desire Lines in Big Data”.
This lecture is organised to honour prof. dr. Wil van der Aalst, on whom the degree of ‘doctor honoris causa’ will be conferred by Hasselt University, Faculty of Business Economics (promotor prof. Koen Vanhoof). Professor van der Aalst is a full professor of Information Systems at the Technische Universiteit Eindhoven (TU/e). Currently he is also an adjunct professor at Queensland University of Technology (QUT).His research interests include workflow management, process mining, Petri nets, business process management, process modeling, and process analysis. Many of his ideas have influenced researchers, software developers and standardization committees working on process support.
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Keynote at 18th International Conference on Cooperative Information Systems (...Wil van der Aalst
The Software as a Service (SaaS) paradigm is particularly interesting for situations where many organizations need to support similar processes. For example, municipalities, courts, rental agencies, etc. support highly similar processes. However, despite these similarities, there is also the need to allow for local variations in a controlled manner. Therefore, cloud infrastructures should provide configurable services such that products and processes can be customized while sharing commonalities. Configurable and executable process models are essential to realize such infrastructures. This will finally transform reference models from "paper tigers" (reference modeling a la SAP, ARIS, etc.) into an "executable reality". Moreover, "configurable services in the cloud" enable cross-organizational process mining. This way, organizations can learn from each other and improve their processes.
Process Mining - Chapter 12 - Analyzing Spaghetti ProcessesWil van der Aalst
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Process Mining - Chapter 11 - Analyzing Lasagna ProcessesWil van der Aalst
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Process Mining - Chapter 2 - Process Modeling and AnalysisWil van der Aalst
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Process Mining - Chapter 6 - Advanced Process Discovery_techniquesWil van der Aalst
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Event Logs: What kind of data does process mining require?Wil van der Aalst
The starting point for process mining is an event log. How to get this data in a format suitable for process mining? This slide show will explain this.
Each event in such a log refers to an activity (i.e., a well-defined step in some process) and is related to a particular case (i.e., a process instance). The events belonging to a case are ordered and can be seen as one "run" of the process. Event logs may store additional information about events. In fact, whenever possible, process-mining techniques use extra information such as the resource (i.e., person or device) executing or initiating the activity, the timestamp of the event, or data elements recorded with the event (e.g., the size of an order).
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Process Mining - Chapter 13 - Cartography and NavigationWil van der Aalst
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
This Slide Deck was presented at the annual international conference of itSMF Slovensko on May, 6th. in Bratislava. It gives an introduction into Process Mining as a new useful approach to discover real life processes in IT Service Management end everywhere else where processes are driven by tools providing log file information.
Many thanks to Anne Rozinat http://fluxicon.com for the graphs and information she provided to itSMF Austria. Many thanks to Celonis for providing a demo application.
Please recognize the further links and recommendations at the end of the presentation.
Process Mining - Chapter 8 - Mining Additional PerspectivesWil van der Aalst
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Bringing Customers to You with Inbound MarketingLaunch Team Inc.
This presentation, originally presented at the Photonics West 2014 conference, shows marketing and product managers in the optics & photonics industry how to adapt their marketing tactics to engage new customers.
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
SOUTHEAST ASIA (SEA) DIGITAL IN 2015 - Q4 - WeAreSocials
Tổng quan bức tranh và số liệu online cho thị trường Đông Nam Á (SEA) 2015 Quý 4.
Bức tranh người dùng Mobile trong khu vực Đông Nam Á
ANTS quảng cáo trực tuyến Việt Nam
Các chỉ số thị trường quảng cáo Việt Nam
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Industrial Analytics and Predictive Maintenance 2017 - 2022Rising Media Ltd.
In this session we will present the results of two recent, international studies on the state of data analytics in industrial settings. You will get insights from an in-depth industry survey of 151 analytics professionals and decision-makers in industrial companies, providing a deep-dive into strategies, project types, cost structures and skill-demand in IoT-based analytics. In addition we will present a survey focusing on predictive analytics covering the market potential and expected development until 2022.
Process Mining: Data Science in Action - Wil van der Aalst, TU/e, DSC/e, HSEYandex
Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis. Process mining bridges the gap between traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques, such as machine learning and data mining. Process mining seeks to find a connection between event data (i.e., observed behavior) and process models (hand-made or discovered automatically). This technology has become available only recently, but it can be applied to any type of operational processes (organizations and systems). Example applications can include: analyzing treatment processes in hospitals, improving customer service processes in multinational companies, understanding browsing behavior of customers on a booking site, analyzing failures of a baggage handling system, or improving user interface of the X-ray machine. What all of these applications have in common is the need to relate dynamic behavior to process models. Not only does process mining provide a bridge between data mining and business process management, but it also helps to address the classical divide between "business" and "IT". Evidence-based business process management based on process mining helps to create a common ground for business process improvement and information systems development.
Process Mining: BPM on Steroids (CPOs@BPM&O 2019 Keynote)Wil van der Aalst
In seinem Vortrag am ersten Veranstaltungstags des CPOs@BPM&O wird Prof. van der Aalst von der RWTH Aachen vorschlagen, das Beste aus beiden Welten zu kombinieren: Hybridprozessmodelle zu entdecken, die formale und informelle Elemente enthalten. Die entdeckten Modelle erlauben formale Argumente, offenbaren aber auch Informationen, die nicht in gängigen formalen Modellen erfasst werden können. Die nächste Welle kommerzieller Process-Mining-Tools wird solche Hybridmodelle verwenden.
In seiner Keynote wird Prof. van der Aalst auch auf seine Zusammenarbeit mit der Industrie eingehen. Er führte Process Mining in über 150 Organisationen an, leitete die Entwicklung des Open-Source-Tools ProM und beeinflusste die über 20 verfügbaren kommerziellen Process Mining-Tools.
Everything You Always Wanted To Know About Petri Nets, But Were Afraid To AskWil van der Aalst
A short tutorial on Petri nets at BPM 2019 in Vienna. Business Process Management (BPM), Process Mining (PM), Workflow Management (WFM), and other approaches aimed at improving processes depend on process models. Business Process Model and Notation (BPMN), Event-driven Process Chains (EPCs), and UML activity diagrams all build on Petri nets and have semantics involving ‘playing the token game’. In addition, process analysis approaches ranging from verification and simulation to process discovery and compliance checking often depend on Petri net theory. For the casual user, there is no need to understand the underlying foundations. However, BPM/PM/WFM researchers and ‘process experts’ working in industry need to understand these foundational results. Unfortunately, the results of 50 years of Petri net research are not easy to digest. This tutorial paper provides, therefore, an entry point into the wonderful world of Petri nets.
Process Mining - Chapter 12 - Analyzing Spaghetti ProcessesWil van der Aalst
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Process Mining - Chapter 11 - Analyzing Lasagna ProcessesWil van der Aalst
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Process Mining - Chapter 2 - Process Modeling and AnalysisWil van der Aalst
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Process Mining - Chapter 6 - Advanced Process Discovery_techniquesWil van der Aalst
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Event Logs: What kind of data does process mining require?Wil van der Aalst
The starting point for process mining is an event log. How to get this data in a format suitable for process mining? This slide show will explain this.
Each event in such a log refers to an activity (i.e., a well-defined step in some process) and is related to a particular case (i.e., a process instance). The events belonging to a case are ordered and can be seen as one "run" of the process. Event logs may store additional information about events. In fact, whenever possible, process-mining techniques use extra information such as the resource (i.e., person or device) executing or initiating the activity, the timestamp of the event, or data elements recorded with the event (e.g., the size of an order).
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Process Mining - Chapter 13 - Cartography and NavigationWil van der Aalst
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
This Slide Deck was presented at the annual international conference of itSMF Slovensko on May, 6th. in Bratislava. It gives an introduction into Process Mining as a new useful approach to discover real life processes in IT Service Management end everywhere else where processes are driven by tools providing log file information.
Many thanks to Anne Rozinat http://fluxicon.com for the graphs and information she provided to itSMF Austria. Many thanks to Celonis for providing a demo application.
Please recognize the further links and recommendations at the end of the presentation.
Process Mining - Chapter 8 - Mining Additional PerspectivesWil van der Aalst
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Bringing Customers to You with Inbound MarketingLaunch Team Inc.
This presentation, originally presented at the Photonics West 2014 conference, shows marketing and product managers in the optics & photonics industry how to adapt their marketing tactics to engage new customers.
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
SOUTHEAST ASIA (SEA) DIGITAL IN 2015 - Q4 - WeAreSocials
Tổng quan bức tranh và số liệu online cho thị trường Đông Nam Á (SEA) 2015 Quý 4.
Bức tranh người dùng Mobile trong khu vực Đông Nam Á
ANTS quảng cáo trực tuyến Việt Nam
Các chỉ số thị trường quảng cáo Việt Nam
Slides supporting the book "Process Mining: Discovery, Conformance, and Enhancement of Business Processes" by Wil van der Aalst. See also http://springer.com/978-3-642-19344-6 (ISBN 978-3-642-19344-6) and the website http://www.processmining.org/book/start providing sample logs.
Industrial Analytics and Predictive Maintenance 2017 - 2022Rising Media Ltd.
In this session we will present the results of two recent, international studies on the state of data analytics in industrial settings. You will get insights from an in-depth industry survey of 151 analytics professionals and decision-makers in industrial companies, providing a deep-dive into strategies, project types, cost structures and skill-demand in IoT-based analytics. In addition we will present a survey focusing on predictive analytics covering the market potential and expected development until 2022.
Process Mining: Data Science in Action - Wil van der Aalst, TU/e, DSC/e, HSEYandex
Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis. Process mining bridges the gap between traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques, such as machine learning and data mining. Process mining seeks to find a connection between event data (i.e., observed behavior) and process models (hand-made or discovered automatically). This technology has become available only recently, but it can be applied to any type of operational processes (organizations and systems). Example applications can include: analyzing treatment processes in hospitals, improving customer service processes in multinational companies, understanding browsing behavior of customers on a booking site, analyzing failures of a baggage handling system, or improving user interface of the X-ray machine. What all of these applications have in common is the need to relate dynamic behavior to process models. Not only does process mining provide a bridge between data mining and business process management, but it also helps to address the classical divide between "business" and "IT". Evidence-based business process management based on process mining helps to create a common ground for business process improvement and information systems development.
Process Mining: BPM on Steroids (CPOs@BPM&O 2019 Keynote)Wil van der Aalst
In seinem Vortrag am ersten Veranstaltungstags des CPOs@BPM&O wird Prof. van der Aalst von der RWTH Aachen vorschlagen, das Beste aus beiden Welten zu kombinieren: Hybridprozessmodelle zu entdecken, die formale und informelle Elemente enthalten. Die entdeckten Modelle erlauben formale Argumente, offenbaren aber auch Informationen, die nicht in gängigen formalen Modellen erfasst werden können. Die nächste Welle kommerzieller Process-Mining-Tools wird solche Hybridmodelle verwenden.
In seiner Keynote wird Prof. van der Aalst auch auf seine Zusammenarbeit mit der Industrie eingehen. Er führte Process Mining in über 150 Organisationen an, leitete die Entwicklung des Open-Source-Tools ProM und beeinflusste die über 20 verfügbaren kommerziellen Process Mining-Tools.
Everything You Always Wanted To Know About Petri Nets, But Were Afraid To AskWil van der Aalst
A short tutorial on Petri nets at BPM 2019 in Vienna. Business Process Management (BPM), Process Mining (PM), Workflow Management (WFM), and other approaches aimed at improving processes depend on process models. Business Process Model and Notation (BPMN), Event-driven Process Chains (EPCs), and UML activity diagrams all build on Petri nets and have semantics involving ‘playing the token game’. In addition, process analysis approaches ranging from verification and simulation to process discovery and compliance checking often depend on Petri net theory. For the casual user, there is no need to understand the underlying foundations. However, BPM/PM/WFM researchers and ‘process experts’ working in industry need to understand these foundational results. Unfortunately, the results of 50 years of Petri net research are not easy to digest. This tutorial paper provides, therefore, an entry point into the wonderful world of Petri nets.
Process Mining In Today’s Platforms Economy: Opportunities and Challenges (WI...Wil van der Aalst
Process mining is rapidly becoming a standard way to analyze performance and compliance problems based on event data. Currently, there are more than 30 commercial process-mining tools based on the research by prof. Van der Aalst and his team. The primary enabler for process mining is the increasing digitization of society and business. Tech companies such as Uber, Airbnb, Amazon, Booking, and Alibaba and were able to grow extremely fast due to the digital platforms they provide. Smart homes, production facilities, and energy networks also build on platforms recording the actual behavior or people and machines. All digital platforms have in common that they record event data at an unprecedented level. This allows for all forms of process mining (process discovery, conformance checking, prediction, etc.). Particularly interesting are comparative process mining techniques, i.e., comparing variants of the same process for different groups of customers, periods, locations, etc. However, there are also challenges related to confidentiality and other aspects of responsible data science. In his talk, Wil van der Aalst (“the godfather of process mining”) reflects on the capabilities and limitations of today’s process mining tools and the opportunities and challenges provided by digital platforms.
A Decade of Business Process Management Conferences: Reflections on a Develop...Wil van der Aalst
The Business Process Management (BPM) conference series celebrates its tenth anniversary. This is a nice opportunity to reflect on a decade of BPM research. This talk will describe the history of the conference series through the prism of typical BPM use cases and six key BPM concerns: Process Modeling Languages, Process Enactment Infrastructures, Process Model Analysis, Process Mining, Process Flexibility, and Process Reuse. Although BPM has matured as a research discipline, there are still various important problems that remain open. Moreover, despite the broad interest in BPM, there is significant room for improvement when it comes to the the adoption of state-of-the-art results by software vendors, consultants, and end-users. The BPM discipline should not shy away from the key challenges and set clear targets for the next decade.
Keynote BPM 2012: http://bpm2012.ut.ee/
Prof.dr.ir. Wil van der Aalst is a full professor of Information Systems at the Technische Universiteit Eindhoven (TU/e). Currently he is also an adjunct professor at Queensland University of Technology (QUT) working within the BPM group there. His research interests include workflow management, process mining, Petri nets, business process management, process modeling, and process analysis. Wil van der Aalst has published more than 150 journal papers, 17 books (as author or editor), 300 refereed conference/workshop publications, and 50 book chapters. Many of his papers are highly cited (he has an H-index of more than 92 according to Google Scholar, making him the European computer scientist with the highest H-index) and his ideas have influenced researchers, software developers, and standardization committees working on process support. He has been a co-chair of many conferences including the Business Process Management conference, the International Conference on Cooperative Information Systems, the International conference on the Application and Theory of Petri Nets, and the IEEE International Conference on Services Computing. He is also editor/member of the editorial board of several journals, including the Distributed and Parallel Databases, the International Journal of Business Process Integration and Management, the International Journal on Enterprise Modelling and Information Systems Architectures, Computers in Industry, Business & Information Systems Engineering, IEEE Transactions on Services Computing, Lecture Notes in Business Information Processing, and Transactions on Petri Nets and Other Models of Concurrency. In 2012, he received the degree of doctor honoris causa from Hasselt University. He is also a member of the Royal Holland Society of Sciences and Humanities (Koninklijke Hollandsche Maatschappij der Wetenschappen) and the Academy of Europe (Academia Europaea).
Service Interaction: Patterns, Formalization, and AnalysisWil van der Aalst
Invited Lecture at the 9th International School on Formal Methods for the Design of Computer, Communication and Software Systems: Web Services (SFM-09:WS), Bertinoro, Italy, June 1-6, 2009.
Keynote Gartner Business Process Management Summit, February 2009, London Wil van der Aalst
Executive Keynote Gartner Business Process Management Summit
23 – 25 February 2009, London. Title "Process Mining: Beyond Business Intelligence" by Prof. dr. ir. Wil van der Aalst, Professor of Information Systems, Technische Universiteit Eindhoven.
This is something completely NEW, something people said wasn’t possible, that the data wasn’t there to allow systems that really could map out a process; they were wrong. Data is now everywhere; it is accessible, there is an abundance of data and it can provide you with insights you could never find just in interviews. The goal is to get away from workflow systems that are divorced from reality and from how people really work.
Today’s tools oversimplify reality when what you need is a view as close to the real world as possible. Since the 1990s such process tools have been a disappointment; they haven’t covered the true lifecycle. Process mining is a new step which involves seeing how processes are really being executed and using this as an input to allow the design and improvement of processes.
Keynote IEEE Symposium Series on Computational Intelligence (SSCI 2011)/IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2011), April 2011, Paris, France
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
18. “All of the world's
Big Data music can be stored
on a $600 disk drive.”
“Enterprises
globally stored
more than 7
exabytes
of new data on disk
drives in 2010,
while consumers
stored more
than 6 exabytes of
new data on “Indeed, we are
devices such as generating so much
PCs and data today that it is
notebooks.” physically impossible
to store it all. Health
care providers, for
instance, discard 90
percent of the data
that they generate.”
Source: “Big Data: The Next Frontier for Innovation, Competition,
and Productivity” McKinsey Global Institute, 2011.
PAGE 17
19. Hilbert and Lopez. The World's Technological Capacity to Store, Communicate,
and Compute Information. Science, 332(6025):60-65, 2011.
PAGE 18
25. Four Competing Quality Criteria
“able to replay event log” “Occam’s razor”
“not overfitting the log” “not underfitting the log”
PAGE 24
26. Example: one log four models
b
examine
thoroughly
g
pay
c compensation
a examine e
start register casually decide end
# trace
request
h 455 acdeh
d reject
check ticket request 191 abdeg
f reinitiate
request 177 adceh
N1 : fitness = +, precision = +, generalization = +, simplicity = +
144 abdeh
111 acdeg
a c d e h
82 adceg
start register examine check decide reject end
request casually ticket request
56 adbeh
N2 : fitness = -, precision = +, generalization = -, simplicity = +
47 acdefdbeh
“able to replay event log” “Occam’s razor”
38 adbeg
examine check
thoroughly b d ticket g 33 acdefbdeh
fitness simplicity pay
compensation
a 14 acdefbdeg
start register examine
c end 11 acdefdbeg
request casually
e f reinitiate h
process decide request reject
request
9 adcefcdeh
discovery N3 : fitness = +, precision = -, generalization = +, simplicity = + 8 adcefdbeh
5 adcefbdeg
a d c e g
3 acdefbdefdbeg
generalization precision register
request
check
ticket
examine
casually
decide pay
compensation
2 adcefdbeg
a c d e g 2 adcefbdefbdeg
“not overfitting the log” “not underfitting the log” register examine check decide pay
request casually ticket compensation 1 adcefdbefbdeh
a d c e h 1 adbefbdefdbeg
register check examine decide reject
request ticket casually request 1 adcefdbefcdefdbeg
a c d e h 1391
start end
register examine check decide reject
request casually ticket request
(all 21 variants seen in the log)
a b d e g
register examine check decide pay
request thoroughly ticket compensation
a d b e h
register check examine decide reject
request ticket thoroughly request
a b d e h
register examine check decide reject
request thoroughly ticket request PAGE 25
N4 : fitness = +, precision = +, generalization = -, simplicity = -
30. # trace
455 acdeh
Model N4 191 abdeg
177 adceh
144 abdeh
a d c e g 111 acdeg
register check examine decide pay
request ticket casually compensation 82 adceg
a c d e g 56 adbeh
register examine check decide pay
request casually ticket compensation 47 acdefdbeh
a d c e h 38 adbeg
register check examine decide reject
request ticket casually request 33 acdefbdeh
a c d e h 14 acdefbdeg
start end
register examine check decide reject
request casually ticket request 11 acdefdbeg
9 adcefcdeh
(all 21 variants seen in the log)
8 adcefdbeh
5 adcefbdeg
a b d e g
register examine check decide pay 3 acdefbdefdbeg
request thoroughly ticket compensation
2 adcefdbeg
a d b e h
register check examine decide reject 2 adcefbdefbdeg
request ticket thoroughly request
1 adcefdbefbdeh
a b d e h
register examine check decide reject 1 adbefbdefdbeg
request thoroughly ticket request
1 adcefdbefcdefdbeg
N4 : fitness = +, precision = +, generalization = -, simplicity = -
PAGE 29
1391
33. Petri net view:
Just discover the places …
Adding a place limits behavior:
• overfitting ≈ adding too many places
• underfitting ≈ adding too few places
PAGE 32
34. Example: Process Discovery Using
State-Based Regions
d
e
[a,e] [a,d,e]
[ a,b]
a b
[] [a] c
c
b d
[a,c] [a,b,c] [a,b,c,d]
b
a p1 e p3 d
start end
p2 c p4
PAGE 33
35. Example of Region
d
e
[a,e] [a,d,e]
[ a,b]
a b
[] [a] c
c
b d
[a,c] [a,b,c] [a,b,c,d]
enter: b,e
leave: d
do-not-cross: a,c
b
a p1 e p3 d
start end
p2 c p4
PAGE 34
36. Example: Process Discovery Using
Language-Based Regions
A place is feasible if it
can be added without
disabling any of the
traces in the event log.
R
PAGE 35
39. # trace
455 acdeh
Can be lifted to log level 191 abdeg
177 adceh
N1 b 144 abdeh
examine
thoroughly
g
111 acdeg
p1 pay
c p3
compensation
82 adceg
a examine e
start register casually decide p5 end 56 adbeh
request
h
p2 d p4 reject 47 acdefdbeh
check ticket request
f reinitiate 38 adbeg
request
33 acdefbdeh
14 acdefbdeg
11 acdefdbeg
9 adcefcdeh
8 adcefdbeh
5 adcefbdeg
3 acdefbdefdbeg
2 adcefdbeg
2 adcefbdefbdeg
1 adcefdbefbdeh
1 adbefbdefdbeg
1 adcefdbefcdefdbeg
PAGE 38
1391
40. From “playing the token game” to
optimal alignments …
observed trace: “abeg”
a b » e g
a b d e g
move in
model only
PAGE 39
41. Another alignment
observed trace: “abcdeg”
a b c d e g
a b » d e g
move in
log only
PAGE 40
42. Moves in an alignment
move in log
trace in
event log
a b » d e g
a » c d e g
possible run
of model
move in
model move in both
Optimal alignment describes modeled behavior
closest to observed behavior PAGE 41
43. Moves have costs
… a … … » …
… » … … a …
… a … … a …
… a … … b …
• Standard cost function:
− c(x,») = 1
− c(»,y) = 1
− c(x,y) = 0, if x=y
− c(x,y) = ∞, if x≠y PAGE 42
44. Non-fitting trace: abefdeg
abefdeg
a b » e f d » e g
2
a b d e f d b e g
a b e f d e g
2
a b » » d e g
PAGE 43
45. Any cost structure is possible
… send-letter(John,2 …
weeks, $400)
… send-email(Sue,3 …
weeks,$500)
• Similar activities (more similarity implies lower costs).
• Resource conformance (done by someone that does
not have the specified role).
• Data conformance (path is not possible for this
customer).
• Time conformance (missed the legal deadline)
PAGE 44
46. b
examine
thoroughly
g
pay
c compensation
Fitness
a e
1.0
examine
start register casually decide end
# trace
request
h 455 acdeh
d reject
check ticket request 191 abdeg
f reinitiate
request 177 adceh
N1 : fitness = +, precision = +, generalization = +, simplicity = +
144 abdeh
111 acdeg
a c d e h
82 adceg
Our A* algorithm 0.8 start register
request
examine
casually
check
ticket
N2 : fitness = -, precision = +, generalization = -, simplicity = +
decide reject
request
end
56 adbeh
exploits the Petri 47 acdefdbeh
38 adbeg
net marking examine
thoroughly b d check
ticket
pay
g 33 acdefbdeh
equation and uses a
compensation
14 acdefbdeg
other “tricks” to 1.0 start register
request
examine
casually c
decide e f reinitiate
request reject
request
h
end 11 acdefdbeg
9 adcefcdeh
prune the search N3 : fitness = +, precision = -, generalization = +, simplicity = + 8 adcefdbeh
5 adcefbdeg
space. a d c e g
3 acdefbdefdbeg
register check examine decide pay
request ticket casually compensation
2 adcefdbeg
a c d e g 2 adcefbdefbdeg
register examine check decide pay
request casually ticket compensation 1 adcefdbefbdeh
a d c e h 1 adbefbdefdbeg
register check examine decide reject
request ticket casually request 1 adcefdbefcdefdbeg
1.0 start
a
register
request
c
examine
casually
d
check
ticket
e
decide
h
reject
request
end
1391
(all 21 variants seen in the log)
a b d e g
register examine check decide pay
Aligned event log is request thoroughly ticket compensation
a d b e h
starting point for other register
request
check
ticket
examine
thoroughly
decide reject
request
types of analysis. a
register
b d
check
e
decide
h
reject
examine
request thoroughly ticket request
PAGE 45
N4 : fitness = +, precision = +, generalization = -, simplicity = -
49. What if? there are more
than 100.000.000
events? there are more than
1000 different
activities?
acefgijkl conformance add extra
acddefhkjil checking insurance
g
abdefjkgil c8
process c4
acdddefkhijl discovery
acefgijkl
abefgjikl h
skip extra
... b
insurance
skip extra
change c5 c9
insurance d
booking
i
a c select car
in book car c1 add extra c2 c6
insurance
e f j l
confirm c3 check driver’s c10 out
initiate supply
check-in license car
there are more k
than 1.000.000 c7
charge credit
c11
cases? card
PAGE 48
52. How to distribute conformance checking?
f
abcdeg
adcefbcfdeg
abdceg
abcdefbcdeg c
abdfcefdceg
acdefbdceg a b c2 c4 e g
abcdeg
abdceg in c1 d c6 out
abdcefbdcefbdceg
abcdeg c3 c5
abcdefbcdefbdceg
abcdefbdceg
acdefg
adcfeg
abdcefcdfeg
abcdeg
abcdeg
abdceg
abcdefbcdeg f occurs
abcdeg too often
abdceg
abdcefbdcefbdceg f
abcdeg
abcdefbcdefbdceg
abcdefbdceg
abcdeg c
a b c2 c4 e g
in c1 d c6 out
c3 c5
adcefbcfdeg
abdfcefdceg b is often
acdefbdceg skipped
acdefg
adcfeg PAGE 51
abdcefcdfeg
53. Classification based on partitioning of
event log: vertical and horizontal
sets of
cases
sets of
activities
PAGE 52
54. Replication: Same event log on all
computing nodes
Only makes sense if random elements,
e.g., genetic process mining.
PAGE 53
69. So What?
• Any process model can be partitioned in minimal
passages.
• Discovery and conformance checking can be done
per passage!
clouds may contain
a d
f
h
arbitrary subprocesses not
k n
explicitly recorded in the
event log (invisible activities
o
or small networks used for
routing, e.g. XOR/AND/OR-
b e i
split/joins)
l
i g p o
c j
m
PAGE 68
70. Example result for Petri nets
f
a d h k n
“The event log fits all o
passages if and only if
b e i
the event log fits the i g
l
p o
whole model.” c j
m
Key insight: interface transitions controlled by event log PAGE 69
71. Discovery example
a g
in out
f f
b e
a g
c c
causal structure obtained using
b e
heuristics & domain knowledge
d d
f
c
a b c2 c4 e g
in c1 d c6 out
c3 c5
PAGE 70
72. Conformance checking
acefl add extra
acddefl insurance
g
abdefl c4 c8
acdddefl
acefl h
skip extra
abefl b
insurance
... skip extra
change c5 c9
insurance d
booking
i
a c select car
in book car c1 add extra c2 c6
insurance
e f j l
confirm c3 check driver’s c10 out
initiate supply
check-in license car
k
c7 c11
charge credit
card
PAGE 71