In this episode we talk with Claudio Di Ciccio about declarative process modelling, and adjacent topics in process mining.

Claudio Di Ciccio is an assistant professor with the Institute for Information Business at Wirtschaftsuniversität Wien, Austria. His research interests include process mining, declarative process modelling, blockchains, and service oriented computing.

In 2015, his paper entitled “Ensuring Model Consistency in Declarative Process Discovery” has received the best paper award of the 13th conference on Business Process Management. In August 2018, he was Researcher of the Month of the Vienna University of Economics and Business.

Recommended PhD theses:

Maja Pešić: “Constraint-based workflow management systems: shifting control to users”

https://doi.org/10.6100/IR638413

Johannes De Smedt: “Studies on Declarative Process Modeling and Its Relation to Procedural Techniques”

https://lirias.kuleuven.be/1834742

Online resources about MINERful

MINERful website: https://github.com/cdc08x/MINERful

MINERful wiki: https://github.com/cdc08x/MINERful/wiki

Slides:

Introductory slides on declarative process specifications: https://www.slideshare.net/cdc08x/introduction-to-the-declarative-specification-of-processes

Slides on declarative process discovery: https://www.slideshare.net/cdc08x/automated-discovery-of-declarative-process-models

Slides on declarative process discovery and reasoning: https://www.slideshare.net/cdc08x/declarative-specification-of-processes-discovery-and-reasoning

Claudio's website:

http://diciccio.net

Papers mentioned during the interview:

The one about activity-events matching (it’s open access!): https://doi.org/10.1007/s10270-017-0603-z

The one about process drift: https://arxiv.org/abs/1907.06386

Find A SIDE OF DATA on twitter: https://twitter.com/ASideOFData

And on the web: asideofdata.com

SEND us an email with suggestions: [email protected]

Today at A Side Of Data, Anton interviews Leo Zhicheng Liu - an information visualization and visual analytics researcher, who is currently working in the Creative Intelligence Lab at Adobe Research. 

 

We talk about visualizing event sequence data. Today there is a lot of interest in this data type for clickstream data, customer journey mapping, medical domain, and process mining. Through his experience of working on many projects including Matrix Wave, SellTrend, CoreFlow, MAQUI(МАРКІ), and Patterns & Sequences, Leo discusses the principles, motivations, and guidelines of creating better visual representations of the data at hand.

 

Contact Leo via his web page: http://www.zcliu.org/

Leo's twitter: https://twitter.com/zcliu

Leo's projects:

Data Illustrator: https://twitter.com/dataillustrator

CoreFlow: http://www.zcliu.org/coreflow/

 

Find A SIDE OF DATA on twitter: https://twitter.com/ASideOFData

And on the web: asideofdata.com

SEND us an email with suggestions: [email protected]

In this episode of A Side Of Data, we interview lecturer and assistant professor at the the Queensland University of Technology, creator of Inductive miner Sander Leemans. We discuss how the main algorithm of process mining that is process discovery works, we talk about power and deficiencies of those algorithms, and we also touch upon the process mining tools, and how to improve them. We touch upon process model representations, such as directly follows relations, declare, procedural models. The guest based on his experience advises the creators of the commercial process mining products.

Find more about Sander: http://leemans.ch/leemansCH/quickvisualiser/

On LinkedIn: https://www.linkedin.com/in/sander-leemans-8347b8aa

Find out show on twitter: https://twitter.com/ASideOFData

And on the web: asideofdata.com

Email: [email protected]

In this episode, my cohost Saimir Bala and me (Anton Yeshchenko) talk about sequential time-oriented event data, which is the basis of the Process Mining as a science about of understanding processes from data. Our discussion covers what are limitations of data mining, and how process mining helps overcome them. We also talk about the main challenges of process mining.

Find us on twitter: twitter.com/ASideOFData

Saimir: twitter.com/saimirbala

Anton: twitter.com/antonyeshchenko

Please rate us on podcasting platforms, and send an email with suggestions for future shows to [email protected]

In this episode of Aside of data Henderik Proper and Stijn Hoppenbrouwers discuss about conceptual modeling, and how that relates to big data, process mining, BPM. Is conceptual modeling becoming obsolete? Or does it have an impact in the world of machine learning and AI? Why metadata is important? How do organizations benefit from building conceptual models? Reach Henderik at twitter @erikproper and Stijn @SHoppenbrouwers. Tweet to the show @ASideOfData

In this episode, I interview Moe Wynn, from the Queensland University of Technology in Australia about her experience of helping private companies and hospitals with Process mining. She explains a few practical use cases of how data methods helped actual organizations to find problems in their processes. Additionally, we discuss data quality issues that basically every process mining project encounters and talk about recommendations on what to think about when setting up the ERP system to enable better data analysis afterward.

This is the introductory episode of A Side Of Data podcast that aims to introduce the listener to the soul of the later episodes. This podcast is all about using data to bring real value and insights through data science, process mining, data visualization algorithms, and going beyond data, to make more sense by the conceptual modeling, BPM, etc. Welcome to the podcast!

Thank you Danial Foroughi for creating an amazing podcast intro