<pre>IEEE EDOC 2014 is the eighteenth conference in a series that provides the key forum for researchers and practitioners in the field of enterprise computing. EDOC conferences address the full range of models, methodologies, and engineering technologies contributing to intra– and inter–enterprise application systems. Since 1997, EDOC has brought together leading computer scientists, IT decision makers, enterprise architects, solution designers, and practitioners to discuss enterprise computing challenges, models and solutions from the perspectives of academia, industry, and government. The IEEE EDOC conference series emphasizes a holistic view on enterprise applications engineering and management, fostering integrated approaches that address and relate business processes, people and technology. EDOC′14 welcomes high quality scientific submissions as well as experience papers on enterprise computing from industry. The main theme of EDOC′14 is "Utilizing Big Data for Enterprise of the Future" and addresses the four V′s of Big Data in the context of enterprise computing [<a href="http://www.ibmbigdatahub.com/infographic/four–vs–… 1. new ways to utilize and manage the large *volume* of data in enterprises, 2. efficient techniques for handling the *velocity* of data where large amount of data are captured in a short time frame, 3. bringing together a large *variety* of different forms of data within and across enterprises, and 4. dealing with *veracity* or uncertainty of data leading to quality and trust in collected data. Expert panel discussions and keynotes will address current topics and issues in this domain. Topics The IEEE EDOC conference seeks high–quality contributions addressing the domains, life–cycle issues, and realization technologies involved in building, deploying and operating enterprise computing systems. Suggested areas include, but are not limited to: – Enterprise Architecture and Enterprise Application Architecture * Enterprise architecture frameworks * Enterprise architecture analysis, assessment and prediction * Cloud computing and the evolution of enterprise architectures * Enterprise ontologies – Model–based Approaches * Model–driven architectures and model–driven software development * Modeling based on domain specific languages (DSL) * Approaches based on reference architectures * Collaborative development and cooperative engineering issues – Service–oriented Architectures (SOA) and Enterprise Service Architectures (ESA) * Service engineering and evolution of related specifications * Semantics–based service engineering * Service composition, orchestration and choreography * Enterprise service bus * Complex event processing and event–driven architectures – Governance in Service–oriented Architectures * Service policies, contract definition and enforcement * Security/privacy policy definition and description languages * Security/privacy policy interoperability – Business process management (BPM) * Business process modeling, verification, configuration and implementation * Process–aware information systems (PAIS), Human–centric PAIS, Social BPM * Managing business process variability, adaptation and evolution in PAIS * Process mining and its application in business analytics * Distributed and cross–organizational business processes * Data–intensive processes * Cloud impact on BPM, business processes in the cloud * Emerging BPM paradigms (e.g., adaptive case management, data–driven processes) – Business analytics * Modeling and predictive analytics for enterprise computing * Data–driven enterprise strategy * Collaboration enterprise analytic platforms * Business process intelligence (e.g., process performance management) * Continuous, online analytics for big data in the enterprise – Business rules * Business rule languages and engines * Relation between business rules and business processes * Business rules and service computing * Business rules and compliance management, business process compliance – Information integration and interoperability * Business object modeling methodologies and approaches * Taxonomies, ontologies and business knowledge integration * Master data management, data mining and (real–time) data warehousing * Flexible information models and systems (e.g., object–driven processes) * Data quality and trustworthiness – Networked Enterprise Solutions * Enterprise interoperability, collaboration and its architecture * Virtual organizations, including multi–agent system support * Cross–enterprise collaboration in a world of cloud, social and big data * Digital ecosystems * Trust management – Enterprise applications deployment and governance * Performance and operational risk prediction and measurement * Quality of service (QoS) and cost of service (CoS) * Management and maintenance of enterprise computing systems * Information assurance * Human and social organizational factors in enterprise computing – Emerging trends in distributed enterprise applications * Social information and innovation networks, social media impact on the enterprise * People–centric collaboration systems, people–centric services * Private and public cloud computing Infrastructures * Idea management and crowdsourcing * Enterprise 2.0, Web 2.0 and beyond * Mobile enterprise services * Industry specific solutions (e.g. for aerospace, automotive, finance, logistics, medicine and telecommunications) * Research and public sector collaboration (e.g. in e–health, e–government, e–science) </pre>
Abbrevation
EDOC
City
Ulm
Country
Germany
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