Patterns for emerging application integration scenarios: A survey

Ritter, Daniel; May, Norman; Rinderle-Ma, Stefanie

doi:10.1016/j.is.2017.03.003

Cited by 39 publications

(75 citation statements)

References 18 publications

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“…• Product catalogues: In business-to-business applications, online portals and shopping sites store information about their products in electronic catalogues [23,24,25]. However, the ontology used to describe products is often designed differently among sellers.…”

Section: Matching Of Data Modelsmentioning

confidence: 99%

Handling probabilistic integrity constraints in pay-as-you-go reconciliation of data models

Hùng

Weidlich

Tâm

et al. 2019

Information Systems

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Data models capture the structure and characteristic properties of data entities, e.g., in terms of a database schema or an ontology. They are the backbone of diverse applications, reaching from information integration, through peer-to-peer systems and electronic commerce to social networking. Many of these applications involve models of diverse data sources. Effective utilisation and evolution of data models, therefore, calls for matching techniques that generate correspondences between their elements. Various such matching tools have been developed in the past. Yet, their results are often incomplete or erroneous, and thus need to be reconciled, i.e., validated by an expert. This paper analyses the reconciliation process in the presence of large collections of data models, where the network induced by generated correspondences shall meet consistency expectations in terms of integrity constraints. We specifically focus on how to handle data models that show some internal structure and potentially differ in terms of their assumed level of abstraction. We argue that such a setting calls for a probabilistic model of integrity constraints, for which satisfaction is preferred, but not required. In this work, we present a model for probabilistic constraints that enables reasoning on the correctness of individual correspondences within a network of data models, in order to guide an expert in the validation process. To support pay-as-you-go reconciliation, we also show how to construct a set of high-quality correspondences, even if an expert validates only a subset of all generated correspondences. We demonstrate the efficiency of our techniques for real-world datasets comprising database schemas and ontologies from various application domains.

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Section: Matching Of Data Modelsmentioning

confidence: 99%

Handling probabilistic integrity constraints in pay-as-you-go reconciliation of data models

Hùng

Weidlich

Tâm

et al. 2019

Information Systems

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“…6,7 In recent years, several open-source message-based integration frameworks have emerged, which represent a new generation of application integration tools. 8,9 These frameworks follow the architectural style of pipes-and-filters 10 and are strongly influenced by the integration patterns documented by Hohpe and Woolf. 11 In the workflow of an integration solution, pipes represent message channels and filters represent atomic tasks that implement a concrete integration pattern to process encapsulated data in messages.…”

Section: Introductionmentioning

confidence: 97%

“…Given that, in the pipes-and-filters architectural style, a message must be completely stored in a channel before being processed by the next task in the workflow, it is not adequate when the data are large or have to be processed in streaming. Increasingly integration frameworks are required to deal with unstructured and large volumes of data, 16 making the EAI research field interesting from a practical point of view, 5,8,9,[17][18][19] whereas effort is required to adapt the integration frameworks for them to work with unstructured and large volumes of data. 17,20 A typical situation happens in contexts such as problems associated with natural language analysis, image analysis, video analysis, video-to-text, and extraction of text data in natural language, in which it is required to work with unstructured data that usually require a streaming pipeline.…”

Section: Introductionmentioning

confidence: 99%

Ranking open source application integration frameworks based on maintainability metrics: A review of five‐year evolution

Frantz¹,

Rehbein²,

Berlezi³

et al. 2019

Softw Pract Exp

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Integration frameworks are specialized software tools built and adapted to facilitate the design and implementation of integration solutions. An integration solution allows for the reuse of applications from the software ecosystem of companies to support their business processes. There are several open-source integration frameworks available on the market designed to operate in a business context to manipulate structured data; however, increasingly, they are required to deal with unstructured and large volumes of data, thus requiring effort to adapt these frameworks to work with unstructured and large volume of data.Choosing the framework, which is the easiest to be adapted, is not a trivial task.In this article, we review the newest stable versions of four open-source integration frameworks by analyzing how they have evolved regarding their adaptive maintainability over five years. We rank them according to their maintainability degree and compare past and current versions of each framework. To encourage and enable researchers and developers to replicate our experiments, with the aim of verifying our findings, and to experiment with new versions of the integration frameworks analyzed, we detail the experimental protocol used while also having made all the required software involved available on the Web.

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“…Enterprise application integration (EAI) is a research eld that concerns with the development of methodologies, techniques and tools to make di erent applications, which were not developed with the purpose of working together, to collaborate (Hohpe and Woolf;). An integration solution orchestrates a group of applications, without the perception that they are being integrated, and without causing dependency in the applications with the solution, allowing data and functionality reuse (Ritter et al;.…”

Section: Introductionmentioning

confidence: 99%

Towards optimisation of the number of threads in the integration platform engines using simulation models based on queueing theory

Haugg¹,

Frantz²,

Roos‐Frantz³

et al. 2019

RBCA

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The use of applications is important to support the business processes of companies. However, most of these applications are not designed to function collaboratively. An integration solution orchestrates a group of applications, allowing data and functionality reuse. The performance of an integration solution depends on the optimum configuration of the number of threads in the runtime engine provided by the integration platforms. It is common that this configuration relies on the empirical knowledge of the software engineers, and it has a direct impact on the performance of integration solutions. The optimum number of threads may be found by means of simulation models. This article presents a methodology and a tool to assist with the generation of simulation models based on queuing theory, in order to find the optimum number of threads to execute an integration solution focusing on performance improvement. We introduce a case of study to demonstrate and experiments to evaluate our proposal.

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Patterns for emerging application integration scenarios: A survey

Cited by 39 publications

References 18 publications

Handling probabilistic integrity constraints in pay-as-you-go reconciliation of data models

Handling probabilistic integrity constraints in pay-as-you-go reconciliation of data models

Ranking open source application integration frameworks based on maintainability metrics: A review of five‐year evolution

Towards optimisation of the number of threads in the integration platform engines using simulation models based on queueing theory

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