VIVACE: A Framework for the Systematic Evaluation of Variability Support in Process-Aware Information Systems

CONTEXT The increasing adoption of process-aware information systems (PAISs) such as workflow management systems, enterprise resource planning systems, or case management systems, together with the high variability in business processes (e.g., sales processes may vary depending on the respective products and countries), has resulted in large industrial process model repositories. To cope with this business process variability, the proper management of process variants along the entire process lifecycle becomes crucial. OBJECTIVE The goal of this paper is to develop a fundamental understanding of business process variability. In particular, the paper will provide a framework for assessing and comparing process variability approaches and the support they provide for the different phases of the business process lifecycle (i.e., process analysis and design, configuration, enactment, diagnosis, and evolution). METHOD We conducted a systematic literature review (SLR) in order to discover how process variability is supported by existing approaches. RESULTS The SLR resulted in 63 primary studies which were deeply analyzed. Based on this analysis, we derived the VIVACE framework. VIVACE allows assessing the expressiveness of a process modeling language regarding the explicit specification of process variability. Furthermore, the support provided by a process-aware information system to properly deal with process model variants can be assessed with VIVACE as well. CONCLUSIONS VIVACE provides an empirically-grounded framework for process engineers that enables them to evaluate existing process variability approaches as well as to select that variability approach meeting their requirements best. Finally, it helps process engineers in implementing PAISs supporting process variability along the entire process lifecycle

VIVACE: A framework for the systematic evaluation of variability support in process-aware information systems

Context: The increasing adoption of process-aware information systems (PAISs) such as workflow management systems, enterprise resource planning systems, or case management systems, together with the high variability in business processes (e.g., sales processes may vary depending on the respective products and countries), has resulted in large industrial process model repositories. To cope with this business process variability, the proper management of process variants along the entire process lifecycle becomes crucial. Objective: The goal of this paper is to develop a fundamental understand-ing of business process variability. In particular, the paper will provide a framework for assessing and comparing process variability approaches and the support they provide for the different phases of the business process life

VIVACE: A framework for the systematic evaluation of variability support in process-aware information systems

Context: The increasing adoption of process-aware information systems (PAISs) such as workflow management systems, enterprise resource planning systems, or case management systems, together with the high variability in business processes (e.g., sales processes may vary depending on the respective products and countries), has resulted in large industrial process model repositories. To cope with this business process variability, the proper management of process variants along the entire process lifecycle becomes crucial. Objective: The goal of this paper is to develop a fundamental understanding of business process variability. In particular, the paper will provide a framework for assessing and comparing process variability approaches and the support they provide for the different phases of the business process lifecycle (i.e., process analysis and design, configuration, enactment, diagnosis, and evolution). Method: We conducted a systematic literature review (SLR) in order to discover how process variability is supported by existing approaches. Results: The SLR resulted in 63 primary studies which were deeply analyzed. Based on this analysis, we derived the VIVACE framework. VIVACE allows assessing the expressiveness of a process modeling language regarding the explicit specification of process variability. Furthermore, the support provided by a process-aware information system to properly deal with process model variants can be assessed with VIVACE as well. Conclusions: VIVACE provides an empirically-grounded framework for process engineers that enables them to evaluate existing process variability approaches as well as to select that variability approach meeting their requirements best. Finally, it helps process engineers in implementing PAISs supporting process variability along the entire process lifecycle. (C) 2014 Elsevier B.V. All rights reserved.This work has been developed with the support of MICINN under the project EVERYWARE TIN2010-18011.Ayora Esteras, C.; Torres Bosch, MV.; Weber, B.; Reichert, M.; Pelechano Ferragud, V. (2015). VIVACE: A framework for the systematic evaluation of variability support in process-aware information systems. Information and Software Technology. 57:248-276. https://doi.org/10.1016/j.infsof.2014.05.009S2482765

A new MDA-SOA based framework for intercloud interoperability

Cloud computing has been one of the most important topics in Information Technology which aims to assure scalable and reliable on-demand services over the Internet. The expansion of the application scope of cloud services would require cooperation between clouds from different providers that have heterogeneous functionalities. This collaboration between different cloud vendors can provide better Quality of Services (QoS) at the lower price. However, current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability to enable collaboration between cloud service providers. Hence, the PhD work is motivated to address interoperability issue between cloud providers as a challenging research objective. This thesis proposes a new framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Analysing different methodologies that have been applied to resolve various problem scenarios related to interoperability lead us to exploit Model Driven Architecture (MDA) and Service Oriented Architecture (SOA) methods as appropriate approaches for our inter-cloud framework. Moreover, since distributing the operations in a cloud-based environment is a nondeterministic polynomial time (NP-complete) problem, a Genetic Algorithm (GA) based job scheduler proposed as a part of interoperability framework, offering workload migration with the best performance at the least cost. A new Agent Based Simulation (ABS) approach is proposed to model the inter-cloud environment with three types of agents: Cloud Subscriber agent, Cloud Provider agent, and Job agent. The ABS model is proposed to evaluate the proposed framework.Fundação para a Ciência e a Tecnologia (FCT) - (Referencia da bolsa: SFRH SFRH / BD / 33965 / 2009) and EC 7th Framework Programme under grant agreement n° FITMAN 604674 (http://www.fitman-fi.eu

Cybersecurity Awareness and Capacities of SMEs

Small and Medium Enterprises (SMEs) are increasingly exposed to cyber risks. Some of the main reasons include budget constraints, the employees’ lack of cybersecurity awareness, cross-sectoral cyber risks, lack of security practices at organizational level, and so on. To equip SMEs with appropriate tools and guidelines that help mitigate their exposure to cyber risk, we must better understand the SMEs’ context and their needs. Thus, the contribution of this paper is a survey based on responses collected from 141 SMEs based in the UK, where the objective is to obtain information to better understand their level of cybersecurity awareness and practices they apply to protect against cyber risks. Our results indicate that although SMEs do apply some basic cybersecurity measures to mitigate cyber risks, there is a general lack of cybersecurity awareness and lack of processes and tools to improve cybersecurity practices. Our findings provide to the cybersecurity community a better understanding of the SME context in terms of cybersecurity awareness and cybersecurity practices, and may be used as a foundation to further develop appropriate tools and processes to strengthen the cybersecurity of SMEs.publishedVersio

IT-palvelun tietotöiden automatisointi: Koneoppimismalli ohjelmistorobotille

Aging population, legacy systems and pressure on cost savings are all growing problems for modern-day companies. One relief for these problems is to automate business processes and IT-service desk tasks with software robots. The aim of the automation is to reduce employees' growing workload so that they have time to work with the more valuable tasks. One of the most limitating factors of using software robots are that the automated processes must be strictly rule-based and the input data must be highly structured. In business there has been a lot of talk about using machine learning and other AI-techniques for achieving more generic solutions, but the actual results have not yet been publicly recognised. In this thesis it is intended to examine the suitability of machine learning for software robotics by automating company's internal IT-services. The goal is to build a working solution and find a machine learning platform for the company that provides software robotic solutions as a service. The end result is a viable automation solution which uses machine learning model for probability-based decision making. Based on this research it is possible say that there exist synergy benefits between the two technologies, as long as there is a suitable application for them.Ikääntyvä väestö, vanhat järjestelmät ja paine kustannussäästöille ovat nykypäivän yritysten kasvavia ongelmia. Yksi helpotus näihin ongelmiin on liiketoimintaprosessien ja IT-palveluiden automatisointi ohjelmistorobottien avulla. Automatisoinnin pyrkimyksenä on vähentää työntekijöiden kasvavaa työtaakkaa, jotta heillä jää enemmän aikaa liiketoiminnalle tärkeämpien tehtävien hoitoon. Yksi suurimmista ohjelmistorobotiikan käyttöä rajoittavista tekijöistä on se, että automatisoitavien prosessien tulee olla tarkasti sääntöihin perustuvia, sekä hyödynnettävän tiedon tarkkaan jäsenneltyä. Alalla on ollut paljon puhetta koneoppimisen ja tekoälyn hyödyntämisestä geneerisempien ratkaisujen saavuttamiseen, mutta tuloksia näiden projektien onnistumisesta ei ole kantautunut suuren yleisön tietoisuuteen. Tässä työssä on tarkoitus tutkia koneoppimisen soveltuvuutta ohjelmistorobotiikkaan automatisoimalla yrityksen sisäisiä IT-palveluja. Päämääränä on rakentaa toimiva prototyyppi ja löytää koneoppimismalleja hyödyntävä alusta, jota prosessien automatisointia tarjoava yritys voisi alkaa käyttämään osana ratkaisukokonaisuuttaan. Lopputuloksena saatiin toimiva ratkaisu, joka höydyntää koneoppimista todennäköisyyksiin perustuvassa päätöksenteossa. Tutkimuksen avulla voidaan sanoa, että kahden tekniikan välillä on synergiahyötyjä, kunhan niille löydetään sopiva käyttökohde

A capability-based context modelling method to enhance digital service flexibility

The thesis argues that the enterprises need to understand their application context to be able to offer flexible digital services. Furthermore, after analysing the state of research in Services Science, it concludes that different roles with varying backgrounds participate to design and implementation of digital services, which adds the need for alignment between those as a further challenge for flexibility. To fulfil this, the thesis designs a context modelling method and evaluates it by means of Design Science Research (DSR).Digitalisierung in der Dienstleistungökonomie erfordert, die Auswirkungen von veränderten Anwendungskontexten an die zu erbringenden Services genau zu verstehen. Es wird nach der Analyse des Standes der Technik in Services Science festgestellt, dass unterschiedliche Rollen in der Gestaltung und Umsetzung von Digital Services beteiligt sind, was die Notwendigkeit der Abstimmung zwischen diesen Rollen als eine wichtige Herausforderung an die Flexibilität stellt. Um ein solches Alignment zu erreichen, entwickelt dieser Beitrag eine Kontextmodellierungsmethode und evaluiert diese mittels DSR

Baggage dissociation for sustainable air travel: Design study of ground baggage distribution networks

Dissociation of passenger travel from baggage delivery has been proposed as one of the radical innovations in future air travel. This concept is still relatively new and largely unexplored, so there are many issues that need to be resolved. For instance, a complete end-to-end baggage dissociation will require the ground distribution networks to deliver passenger luggage to and from the departing and arriving airports. This paper proposes to design such networks as the existing parcel delivery networks. In particular, baggage sorting centers (BSCs) can serve as local hubs for creasing a scalable, multi-level topology of the delivery network in order to manage baggage flows in a given geographical area around the selected airports. Assuming the population density as a proxy for estimating the baggage delivery service demands, the optimum locations of BSCs are determined by formulating and solving the standard p-median and the maximal covering location problems. The numerical results were obtained for Greater London, and also for the whole UK assuming all its major civilian airports. The Greater London area could be served by 36 BSCs to achieve a full service coverage. The 90% service coverage of the whole UK can be achieved by about the same number of BSCs, provided that the coverage distance is increased. In practice, the actual number of required BSCs crucially depends on the operational and capital costs, and the maximum processing capacity of each BSC. These findings have direct implications on the long-term planning and innovations in future air transport