Summary In the context of Internet of Things, thingsourcing is poised to promote the collective behavior that should prevail among things despite their independent nature being confined into silos. By analogy with crowdsourcing where crowds of (sometimes anonymous) people are contacted for their expertise, thingsourcing abstracts crowds of things and provides the necessary mechanisms for composing things together so they collectively satisfy users' demands. However, to ensure successful discovery of things according to these demands' requirements, an ontology‐based semantic description of things is deemed necessary. This article presents an approach for enriching things' descriptions semantically in preparation for their composition with respect to specific scripts that define who will do what, when, and where. A system demonstrating semantic thingsourcing along with a case study about dairy supply‐chain is presented in this article as well.

International audience

Social business processes support enterprises tap into the opportunities of Web 2.0. To ensure an efficient support, this paper presents an approach for identifying an enterprise’s business processes that could be converted into social. Indeed, not all processes are eligible for this conversion. The approach is built upon the concept of enterprise architecture that sheds the light on the necessary contextual elements for guiding the socialization of business processes. Due to the fuzzy nature of socialization, two multi-criteria decision making techniques, fuzzy logic and fuzzy-decision tree, enhance this guidance. A set of experiments for evaluating the proposed approach are presented in the paper, as well.

Like any software product, the quality of Business Process (BP) models is an important issue that must be addressed. Indeed, a poor-quality BP model can disturb its implementation and execution as well as its performance. In the literature, different studies focused on the evaluation of BP model's quality using quality metrics. The common challenge highlighted by these studies is the lack of a consensus on the thresholds of the used quality metrics and the difficulty of interpreting the values of these metrics. In this paper, we propose an approach that uses existing quality metrics to evaluate the quality of BP models in terms of comprehensibility and modifiability. Besides, we determine the thresholds of the different quality metrics through decision tree technique. Decision tree also produces a set of decision rules that are useful to determine the quality level of BP model. The approach is validated through a tool named BP-Quality that calculates the values of the quality metrics and deduces the comprehensibility and modifiability levels based on calculated values and the aforementioned thresholds.

A Social Business Process (SBP) is the result of blending social computing (a.k.a. Web 2.0) with business process (BP). Despite the benefits of SBP to enterprises, several limitations continue to undermine them. In this paper, we address two specific limitations, namely the difficulty of capturing SBP's requirements and the lack of a definition for SBP. Thus, meta-modeling is used to capture requirements from organizational, technological, and management perspectives. In addition, we introduce a definition for SBP by enriching an existing BP meta-model with social concepts. To annotate the SBP model with its requirements, a BPMN extension is proposed. The proposed meta-models are evaluated in terms of completeness and clarity using the Bunge-Wand-Weber ontology.