http://repositorio.lnec.pt:8080/jspui/handle/123456789/1007759 2026-04-04T21:10:26Z 2026-04-04T21:10:26Z Antunes, G. J. Barateiro, J. Caetano, A. Borbinha, J. L. http://repositorio.lnec.pt:8080/jspui/handle/123456789/1009462 2017-08-08T14:24:25Z 2015-05-01T00:00:00Z

Analysis of federated enterprise architecture models Antunes, G. J.; Barateiro, J.; Caetano, A.; Borbinha, J. L. Enterprise architecture models support decision-making as they help organizations to understand, communicate and analyse how business processes are performed, the goals they achieve, the information they use, as well as the applications that realize the business, and the supporting technological infrastructure. The integrated analysis of these models is not straightforward because it cross-cuts different domains that are described using heterogeneous concepts. This paper explores the application of ontologies to analyse enterprise architecture models. Ontologies represent knowledge that can be analysed using computational inference. The contributions of this paper are (1) the specification of multiple enterprise architecture models as ontological schemas, (2) the integration of ontological schemas, and (3) the analysis of the integrated models. The solution artefact consists of a federated model specified as a set of ontological schemas described in OWL-DL that integrates multiple enterprise models and assists their analysis using computational inference. The paper demonstrates the application of the federated model to the ArchiMate language as a means to assess the compliance of business requirements in a civil engineering scenario.

2015-05-01T00:00:00Z Miksa, T. Pröll, S. Mayer, R. Strodl, S. Vieira, R. J. C. Barateiro, J. Rauber, A. http://repositorio.lnec.pt:8080/jspui/handle/123456789/1006727 2016-06-01T11:01:11Z 2013-09-01T00:00:00Z

Framework for Verification of Preserved and Redeployed Processes Miksa, T.; Pröll, S.; Mayer, R.; Strodl, S.; Vieira, R. J. C.; Barateiro, J.; Rauber, A. José Borbinha; Michael Nelson; Steve Knight Preserving processes requires not only the identification of all process components, but also the interception of all interactions of the process with the external influencers. In order to verify if the collected data is sufficient for the purpose of redeployment, as well as to verify that the redeployed process performs according to expectations, a framework for verification is needed. This paper presents a framework for verification of preserved and redeployed processes. We demonstrate the applicability of the framework on an use case from the eScience domain. The preservation and the redeployment of the eScience process is tested by migrating it to substantially different environments.

2013-09-01T00:00:00Z Barateiro, J. Burda, D. Simon, D. http://repositorio.lnec.pt:8080/jspui/handle/123456789/1006726 2016-06-01T10:50:45Z 2013-09-01T00:00:00Z

Leveraging DP in Commercial Contexts through ERM Barateiro, J.; Burda, D.; Simon, D. José Borbinha; Michael Nelson; Steve Knight Until now, digital preservation research has been mainly driven by public or publicly funded organizations. The justification of costs for the preservation is based on abstract risks such as the risk of losing cultural heritage information, or the risk of data deficiencies for current and future research in big sets of data. Typically, the benefits from digitally preserving the objects of interest is difficult or impossible to quantify in terms of return-on-invest. In fact, it is common that memory institutions are mandated to preserve specific digital objects, making digital preservation not an option, but a legal obligation. While in the case of cultural heritage and scientific research qualitative reasons for preservation suffice, enterprises have an additional obligation to quantify the expected benefits and expenses in order to determine the scope of information to be managed and take commercial decisions for or against digital preservation. To provide appropriate means for leveraging the benefits of digital preservation in a commercial context, we argue in this paper that enterprise risk managers are the established function to assess and support decisions about preservation in enterprises. We show that enterprise risk management can be linked to digital preservation and how intelligent enterprise risk management can be utilized to identify the need for digital preservation, determine the corresponding actions, and contribute to the overall commercial success of enterprises.

2013-09-01T00:00:00Z Bachmann, A. Neumann, M. Miri, H. Barateiro, J. Antunes, G. J. Caetano, A. http://repositorio.lnec.pt:8080/jspui/handle/123456789/1006725 2016-06-01T10:50:40Z 2013-09-01T00:00:00Z

Preservation and redeployment of sensor acquisition processes from a dam safety information system Bachmann, A.; Neumann, M.; Miri, H.; Barateiro, J.; Antunes, G. J.; Caetano, A. KDIR/KMIS There is a growing demand for digital preservation of, not only static objects and files, e.g. text documents and images, but also dynamic objects and whole processes, such as interactive media and entire business and scientific processes. This paper investigates the problem of digitally preserving monitoring processes of a dam safety information system. Monitoring processes are a crucial element in ensuring structural safety; the interpretation of the past data produced by such processes as well as the prediction of potential future behaviour facilitates an earlier detection of possible dam failure. After a successful preservation performance, relevant data can be used or re-produced without the need for the original system to still exist; merely by re-playing the preserved information and data. This enables several possibilities in the scope of a water dam system. The retracing of former situations and structural behaviour decades later is one of them. Furthermore, the interpretation of past data and subsequent prediction of future behaviour that could facilitate an earlier detection of a fault or possible dam failure. This work presents a methodology for preserving the obtained sensor data (readings, measurements, and meta-data) from a dam safety information system, whose involved processes include: data acquisition, the preservation process itself, and the re-playing and redeployment of the preserved data.

2013-09-01T00:00:00Z