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Massive amounts of data, manifesting in various forms, are being produced on the Web every minute and becoming the new standard. Exploring these information sources distributed in different Web segments in a unified way is becoming a core task for a variety of users’ and companies’ scenarios. However, knowledge creation and exploration from distributed Web data sources is a challenging task. Several data integration conflicts need to be resolved and the knowledge needs to be visualized in an intuitive manner. The purpose of this paper is to extend the authors’ previous integration works to address semantic knowledge exploration of enterprise data combined with heterogeneous social and linked Web data sources.

The authors synthesize information in the form of a knowledge graph to resolve interoperability conflicts at integration time. They begin by describing KGMap, a mapping model for leveraging knowledge graphs to bridge heterogeneous relational, social and linked web data sources. The mapping model relies on semantic similarity measures to connect the knowledge graph schema with the sources' metadata elements. Then, based on KGMap, this paper proposes KeyFSI, a keyword-based semantic search engine. KeyFSI provides a responsive faceted navigating Web user interface designed to facilitate the exploration and visualization of embedded data behind the knowledge graph. The authors implemented their approach for a business enterprise data exploration scenario where inputs are retrieved on the fly from a local customer relationship management database combined with the DBpedia endpoint and the Facebook Web application programming interface (API).

The authors conducted an empirical study to test the effectiveness of their approach using different similarity measures. The observed results showed better efficiency when using a semantic similarity measure. In addition, a usability evaluation was conducted to compare KeyFSI features with recent knowledge exploration systems. The obtained results demonstrate the added value and usability of the contributed approach.

Most state-of-the-art interfaces allow users to browse one Web segment at a time. The originality of this paper lies in proposing a cost-effective virtual on-demand knowledge creation approach, a method that enables organizations to explore valuable knowledge across multiple Web segments simultaneously. In addition, the responsive components implemented in KeyFSI allow the interface to adequately handle the uncertainty imposed by the nature of Web information, thereby providing a better user experience.

The requirements engineering (RE) process constitutes the earliest phase of the information system development life cycle. Requirements elicitation is considered as one of the most critical activities of this phase. Moreover, requirements elicitation is still a challenge, especially in the distributed environment of so‐called inter‐company cooperative information systems (ICISs). The purpose of this paper is to propose a methodology to elicit requirements for an ICIS.

An analytical research approach was conducted. The current RE approaches, which are based either on goal, scenario or viewpoint were evaluated. Then the role of the elicitation technique selection step within the requirements elicitation process was examined. Finally the factors that affect this step in a distributed environment were studied. An example from the textile industry is used to illustrate the applicability of the proposed methodology.

Though existing requirements elicitation approaches based either on goal, scenario or viewpoint are effective techniques, they do not fit exactly to a cooperative distributed environment: more issues are created by inadequate communication, time difference between sites, cultural, language and characteristics diversity of stakeholders which affect the elicitation technique selection step and thus the requirements elicitation process. In order to tackle these issues, this paper presents a methodology called MAMIE (from Macro‐ to Micro‐level requirements Elicitation) to elicit requirements for an ICIS. A prototype tool has been developed to support the operation of the methodology.

The major limitation of the paper is that has not yet been tested in an existing organization.

To provide the analyst with well‐defined steps in order to elicit requirements of an ICIS. To understand the role of the elicitation technique selection step within the requirements elicitation process and identifying the factors which have an impact on this step. To select an appropriate elicitation technique according to these factors.

MAMIE integrates the three notions of goal, scenario and viewpoint to elicit requirements for an ICIS. The paper argues that these concepts may be used simultaneously and in a complementary way to improve the requirements elicitation process. Moreover, in order to increase the quality of the elicited requirements and thus the quality of the system‐to‐be, selecting an elicitation technique in MAMIE is not based on personal preferences but on situation assessment.

Many problems in science and engineering fields involve decision making. Usually these decision‐making processes are based on several criteria that represent various experts' knowledge. Stakeholder prioritization is useful for assisting in decision‐making situations where various stakeholders have competing interests, resources are limited, and stakeholder requirements must be appropriately balanced. When these conflicts arise it is important to the success of the organization that it has prioritized each stakeholder according to the situation. To date, few researchers tried to resolve this question, mostly are based on intuitive and very simple reasoning methods which are error prone. The purpose of this paper is to propose a multi‐criteria decision analysis process to help decision makers when evaluating and prioritizing stakeholders.

In this process, Mitchell et al.'s model is used for identifying criteria on which stakeholders will be evaluated and the fuzzy Choquet integral as an aggregation operator. This research also tested and discussed the proposal using a case study from Toulouse city subway.

The results show the applicability of this process and the effectiveness of using the fuzzy Choquet integral than a traditional multi‐criteria evaluation method for human subjective evaluation, or when criteria are not mutually independent.

The highly subjective nature of criteria weights and rapid elicitation can lead to questions of validity. Also, results are not always widely accepted.

The paper is original in considering the stakeholder prioritization problem as a multi‐criteria decision analysis problem; using a simple and well‐known model to classify stakeholders, i.e Mitchell et al.'s model; and in using Choquet integral as an aggregation operator which allows considering interaction between criteria.