representing and visualizing mined artful processes in mailofmine

Representing and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio, Massimo Mecella, Tiziana CatarciHCI-KDD @ USAB 2011: Information Quality in e-Health Graz, 2011, November the 24th

Representing and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)

Motivation (1)Artful processes [HillEtAl06]informal processes typically carried out by those people whose work is mental rather than physical (managers, professors, researchers, engineers, etc.)knowledge workers [ACTIVE09]Knowledge workers create artful processes on the flyThough artful processes are frequently repeated, they are not exactly reproducible, even by their originators, nor can they be easily shared.Artful processes and knowledge workersRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


Motivation (2)In collaborative contexts, knowledge workers share their information and outcomes with other knowledge workersE.g., a software development mgr.Typically, by means of several e-mail conversationsE-mail conversations are actual traces of running processes that knowledge workers adhere toE-mail conversationsRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


Motivation (3)From the collection of e-mail messages, you can extract the processes that lay behindRelated e-mail conversations are traces of their runsValuable advantages for usersAutomated discovery of formal representationswith no effort for knowledge workersTidy organization for nave best practices kept only in mindOpportunity to share and compare the knowledge on methodologiesAutomated discovery of bottlenecks, delays, structural defectsfrom the analysis of previous runsE-mail conversations are a kind of semi-structured textthis approach is not tailored to the electronic mailit can be extended to the analysis of other semi-structured textsProcesses from e-mail conversationsRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


Motivation (4)Personal information management (PIM)how to organize ones own activities, contacts, etc. through the usage of software [CatarciEtAl07, ACTIVE09]Information warfarein supporting anti-crime intelligence agenciesEnterprise engineeringfor knowledge-heavy industries, where preserving documents making up product data is not enough [SmVortex, Heutelbeck11]eHealthfor the automatic discovery of medical treatment procedures on top of patient health records

Some areas of applicabilityRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


The approachRepresentationDeclarative workflows [vanDerAalstEtAl09] for representing artful processesRegular grammars to express declarative workflows constraintsMiningObject Matching [ZardettoEtAl10] forclustering e-mail conversationsfinding the matching between activity and tasks instancesRegular expression mining [GarofalakisEtAl99] for inferring constraintsSupervised learning to group activities into processesText mining information extraction to determine tasks out of e-mail messages [CohenEtAl04, SakuraiEtAl05]How to represent and infer artful processesRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


Algorithm (1)From the e-mail archive to key partsMail archiveMail DatabaseConversationsKey PartsMulti-format mail storageplug-in based crawlers[ZardettoEtAl10]-basedclustering algorithm[CarvalhoEtAl04]-based filterRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


Algorithm (2)From key parts to the activitiesActivity indiciumTasksKey PartsConcatenation[ZardettoEtAl10]-basedActivities[GarofalakisEtAl99]-based pattern miner[CohenEtAl04, SakuraiEtAl05]-based task extractorRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


Algorithm (3)From activities to the processes[GarofalakisEtAl99]-based pattern minerSupervised learningProcess indiciumProcessRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


On the visualization of processesRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *The imperative modelRepresents the whole process at onceThe most used notation is based on a subclass of Petri Nets (namely, the Workflow Nets)


On the visualization of processesRather than using a procedural language for expressing the allowed sequence of activities, it is based on the description of workflows through the usage of constraintsthe idea is that every task can be performed, except the ones which do not respect such constraintsRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *The declarative modelIf A is performed,B must be perfomed,no matterbefore or afterwards(responded existence)Whenever B is performed,C must be performedafterwardsand B can not be repeateduntil C is done(alternate response)The notation here is based on [VanDerAalstEtAl06] (DecSerFlow)


On the visualization of processesRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *Imperative vS declarativeImperativeDeclarativeDeclarative models work better in presence of a partial specification of the process scheme


Representation of artful processesAn example of expected outcomeExistenceconstraintsRelationconstraintsTasksNotation based on [VanDerAalstEtAl06] (DecSerFlow)Representing and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


On the visualization of processesAn example of DecSerFlow [VanDerAalstEtAl06] notationNo, it is not the initialactionYou could even start from hereYou might want to run a legal trace like this: a3, a3, a3, a2, a2, a3, a4, a5, a6, a7, a6, a5 What we want to state here is that such a notation is probably not quite intuitiveRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


On the visualization of processesOur proposalWe do not consider a static graph-based global representation alone the best suitable solution.A graphical representation, easy to understand at a first glimpse, must be used.Idea:when presenting the process schema (static view):a local view on tasks/activities, showing related constraints only;a global view on the process, either: basic (less information, less symbols), or extended (more information, more symbols, extending (a));(2) can work as a kind of navigation map for (1)when presenting the running instance (dynamic view):a dynamic interactive trace representation diagram, based on the local static view notation.Representing and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


On the visualization of processesIntroducing the new local view: the rationaleRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


On the visualization of constraintsThe static local view: some examplesRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


On the representation of processesThe static global viewBasicExtendedRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


A GUI sketchLocal and global views togetherRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


On the representation of constraintsDynamic viewRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


References[BranderEtAl11] Brander, S., Hinkelmann, K., Hu, B., Martin, A., Riss, U. V., Thnssen, B., Witschel, H. F.. Refining process models through the analysis of informal work practice. In BPM, Lecture Notes in Computer Science (6896), 116131. Springer (2011).[HillEtAl06] Hill, C., Yates, R., Jones, C., Kogan, S.L.: Beyond predictable workflows: Enhancing productivity in artful business processes. IBM Systems Journal 45(4), 663682 (2006)[ACTIVE09] Warren, P., Kings, N., et al.: Improving knowledge worker productivity - the active integrated approach. BT Technology Journal 26(2), 165176 (2009)[CatarciEtAl07] Catarci, T., Dix, A., Katifori, A., Lepouras, G., Poggi, A.: Task-centred information management. Proc. DELOS Conference, LNCS 4877 (2007)[SmVortex] Smart vortex management and analysis of massive data streams to support large-scale collaborative engineering projects. FP7 IP Project: http://www.smartvortex.eu/[Heutelbeck11] Heutelbeck, D.: Preservation of enterprise engineering processes by social collaboration software (2011), personal communication, to appear in Proc. COLLIN2011 - 2nd Symposium on Collective Intelligence[vanDerAalstEtAl09] van der Aalst, W.M.P., Pesic, M., Schonenberg, H.: Declarative workflows: Balancing between flexibility and support. Computer Science - R&D 23(2), 99113 (2009)[ZardettoEtAl10] Zardetto, D., Scannapieco, M., Catarci, T.: Effective automated object matching. Proc. ICDE 2010[CohenEtAl04] Cohen, W.W., Carvalho, V.R., Mitchell, T.M.: Learning to classify email into speech acts. Proc. EMNLP 2004[SakuraiEtAl05] Sakurai, S., Suyama, A.: An e-mail analysis method based on text mining techniques. Appl. Soft Comput. 6(1), 6271 (2005)[CarvalhoEtAl04] Carvalho, V.R., Cohen, W.W.: Learning to extract signature and reply lines from email. Proc. CEAS 2004[GarofalakisEtAl99] Garofalakis, M.N., Rastogi, R., Shim, K.: Spirit: Sequential pattern mining with regular expression constraints. Proc. VLDB 1999[vanDerAalstEtAl06] van der Aalst, W.M.P., Pesic, M.: Decserflow: Towards a truly declarative service flow language. Proc. WS-FM 2006[Pnueli77] Pnueli, A.: The Temporal Logic of Programs. Proc. 18th Annual Symposium on Foundations of Software Technology and Theoretical Computer Science, 1977Cited articles and resources, in order of appearanceRepresenting and Visualizing Mined Artful Processes in MailOfMineClaudio Di Ciccio (DIS, SAPIENZA Universit di Roma)P. *


**Artful processes have goals and methods that change quickly over time, making them difficult to codify in an enterprise application.We denote these kinds of processes artful in the sense that there is an art to their execution.In some processes, it is primarily the content in each process instance rather than the process itself that determines the outcome; for example, a request for proposal (RFP) process.Most important, many highly specialized processes are developed or refined locally at the individual or small-team level such that the process cannot easily be separated from the specific people who perform it; for example, managine client relationships in professional services firms.While the framing process may be stable at an abstract level, the key details are not. They depend on the skills, experience, and judgment of the primary actors.********initial(a) implies a to be the first task (activity) for the containing activity (orprocess);f inal(a) implies a to be the last task (activity) for the containing activity (orprocess);response(a, b) implies b to appear in the activity (or process) execution after a is performed, if a is performed;respondedExistence(a, b) implies b to appear in the activity (or process) execution if a is performed, no matter when;succession(a, b) implies b to appear in the activity (or process) after a is performed, and no b can be executed before a is done;coExistence(a, b) implies b to appear in the activity (or process) if a is per-formed, no matter when, and viceversa (a must be performed if b is done).********

representing and visualizing mined artful processes in mailofmine

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