Workflow management systems (WFMS) are enjoying increasing popular ity due to their ability to coordinate and streamline complex organizational processes within organizations of all sizes. Organizational processes are de scriptions of an organization's activities engineered to fulfill its mission such as completing a business contract or satisfying a specific customer request. Gaining control of these processes allows an organization to reengineer and improve each process or adapt them to changing requirements. The goal of WFMSs is to manage these organizational processes and coordinate their execution. was demonstrated in the first half The high degree of interest in WFMSs of the 1990s by a significant increase in the number of commercial products (once estimated to about 250) and the estimated market size (in combined $2 billion in 1996. Ensuing maturity product sales and services) of about is demonstrated by consolidations during the last year. Ranging from mere e-mail based calendar tools and flow charting tools to very sophisticated inte grated development environments for distributed enterprise-wide applications and systems to support programming in the large, these products are finding an eager market and opening up important research and development op portunities. In spite of their early success in the market place, however, the current generation of systems can benefit from further research and develop ment, especially for increasingly complex and mission-critical applications.

This book constitutes the refereed proceedings of the 28th International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2016, held in Ershovo, Moscow, Russia, in October 2016. The 16 revised full papers presented together with one invited talk and two keynote papers were carefully reviewed and selected from 57 submissions. The papers are organized in topical sections on semantic modeling in data intensive domains; knowledge and learning management; text mining; data infrastructures in astrophysics; data analysis; research infrastructures; position paper.

Workflow management systems (WFMS) are enjoying increasing popular ity due to their ability to coordinate and streamline complex organizational processes within organizations of all sizes. Organizational processes are de scriptions of an organization's activities engineered to fulfill its mission such as completing a business contract or satisfying a specific customer request. Gaining control of these processes allows an organization to reengineer and improve each process or adapt them to changing requirements. The goal of WFMSs is to manage these organizational processes and coordinate their execution. was demonstrated in the first half The high degree of interest in WFMSs of the 1990s by a significant increase in the number of commercial products (once estimated to about 250) and the estimated market size (in combined $2 billion in 1996. Ensuing maturity product sales and services) of about is demonstrated by consolidations during the last year. Ranging from mere e-mail based calendar tools and flow charting tools to very sophisticated inte grated development environments for distributed enterprise-wide applications and systems to support programming in the large, these products are finding an eager market and opening up important research and development op portunities. In spite of their early success in the market place, however, the current generation of systems can benefit from further research and develop ment, especially for increasingly complex and mission-critical applications."

This book constitutes the refereed proceedings of the 19th International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2017, held in Moscow, Russia, in October 2017.The 16 revised full papers presented together with three invited papers were carefully reviewed and selected from 75 submissions. The papers are organized in the following topical sections: data analytics; next generation genomic sequencing: challenges and solutions; novel approaches to analyzing and classifying of various astronomical entities and events; ontology population in data intensive domains; heterogeneous data integration issues; data curation and data provenance support; and temporal summaries generation.