In the study of fine art, provenance refers to the documented history of some art object. Given that documented history, the object attains an authority that allows scholars to appreciate its importance with respect to other works, whereas, in the absence of such history, the object may be treated with some skepticism. Our IT landscape is evolving as illustrated by applications that are open, composed dynamically, and that discover results and services on the fly. Against this challenging background, it is crucial for users to be able to have confidence in the results produced by such applications. If the provenance of data produced by computer systems could be determined as it can for some works of art, then users, in their daily applications, would be able to interpret and judge the quality of data better. We introduce a provenance lifecycle and advocate an open approach based on two key principles to support a notion of provenance in computer systems: documentation of execution and user-tailored provenance queries.
A self-organising system functions without central control, and through contextual local interactions. Components achieve a simple task individually, but a complex collective behaviour emerges from their mutual interactions. Such a system modifies its structure and functionality to adapt to changes to requirements and to the environment based on previous experience. Nature provides examples of self-organisation, such as ants food foraging, molecules formation, or antibodies detection. Similarly, current software applications are driven by social interactions (negotiations, transactions), based on autonomous entities or agents, and run in highly dynamic environments. The issue of engineering applications, based on the principles of self-organisation to achieve robustness and adaptability, is gaining increasing interest in the software research community. The aim of this paper is to survey natural and artificial complex systems exhibiting emergent behaviour, and to outline the mechanisms enabling such behaviours
The evaluation of a conceptual model, which is an outcome of a qualitative research, is an arduous task due to the lack of a rigorous basis for evaluation. Overcoming this challenge, the paper at hand presents a detailed example of a multifaceted evaluation of a Reference Model of Information Assurance & Security (RMIAS), which summarises the knowledge acquired by the Information Assurance & Security community to date in one all-encompassing model. A combination of analytical and empirical evaluation methods is exploited to evaluate the RMIAS in a sustained way overcoming the limitations of separate methods. The RMIAS is analytically evaluated regarding the quality criteria of conceptual models and compared with existing models. Twenty-six semistructured interviews with IAS experts are conducted to test the merit of the RMIAS. Three workshops and a case study are carried out to verify the practical value of the model. The paper discusses the evaluation methodology and evaluation results.
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