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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.

Enterprise knowledge graphs (EKG) in resource description framework (RDF) consolidate and semantically integrate heterogeneous data sources into a comprehensive dataspace. However, to make an external relational data source accessible through an EKG, an RDF view of the underlying relational database, called an RDB2RDF view, must be created. The RDB2RDF view should be materialized in situations where live access to the data source is not possible, or the data source imposes restrictions on the type of query forms and the number of results. In this case, a mechanism for maintaining the materialized view data up-to-date is also required. The purpose of this paper is to address the problem of the efficient maintenance of externally materialized RDB2RDF views.

This paper proposes a formal framework for the incremental maintenance of externally materialized RDB2RDF views, in which the server computes and publishes changesets, indicating the difference between the two states of the view. The EKG system can then download the changesets and synchronize the externally materialized view. The changesets are computed based solely on the update and the source database state and require no access to the content of the view.

The central result of this paper shows that changesets computed according to the formal framework correctly maintain the externally materialized RDB2RDF view. The experiments indicate that the proposed strategy supports live synchronization of large RDB2RDF views and that the time taken to compute the changesets with the proposed approach was almost three orders of magnitude smaller than partial rematerialization and three orders of magnitude smaller than full rematerialization.

The main idea that differentiates the proposed approach from previous work on incremental view maintenance is to explore the object-preserving property of typical RDB2RDF views so that the solution can deal with views with duplicates. The algorithms for the incremental maintenance of relational views with duplicates published in the literature require querying the materialized view data to precisely compute the changesets. By contrast, the approach proposed in this paper requires no access to view data. This is important when the view is maintained externally, because accessing a remote data source may be too slow.

Semantic retrieval and discovery of datasets published as open data remains a challenging task. The datasets inherently originate in the globally distributed web jungle, lacking the luxury of centralized database administration, database schemes, shared attributes, vocabulary, structure and semantics. The existing dataset catalogs provide basic search functionality relying on keyword search in brief, incomplete or misleading textual metadata attached to the datasets. The search results are thus often insufficient. However, there exist many ways of improving the dataset discovery by employing content-based retrieval, machine learning tools, third-party (external) knowledge bases, countless feature extraction methods and description models and so forth.

In this paper, the authors propose a modular framework for rapid experimentation with methods for similarity-based dataset discovery. The framework consists of an extensible catalog of components prepared to form custom pipelines for dataset representation and discovery.

The study proposes several proof-of-concept pipelines including experimental evaluation, which showcase the usage of the framework.

To the best of authors’ knowledge, there is no similar formal framework for experimentation with various similarity methods in the context of dataset discovery. The framework has the ambition to establish a platform for reproducible and comparable research in the area of dataset discovery. The prototype implementation of the framework is available on GitHub.

In this paper we present a roadmap for the elicitation of business rules based on different stakeholders' perspectives, in order to facilitate the processes of structuring, organizing and expressing business tactic and policy in a way that it is close to the business milieu and stakeholders' viewpoints.

This paper has derived from a combined research practice. Initially, the development of a roadmap for understanding different stakeholders' perspectives and for identifying their views on business tactics and policies was based on well‐grounded work on enterprise goal modelling, combined with a theoretical study of business rule – related concepts. The outcome of this work was tested against a real business case dealing with the development of an electronic procurement system in the pre‐fabricated construction sector.

As a conclusion, the paper put forward a comprehensive methodological framework for dealing with rule‐intensive projects. The proposed roadmap can help IT practitioners in collecting and organizing business rule statements that apply within a particular organization, either towards the implementation of change on a business level, or in the context of specifying the (existing or future) functionality of supporting information systems (IS).

The rule roadmap presented here has been coupled with a modelling approach for expressing rules in a structured, consistent manner and for organizing them in a rule repository. Future work includes the extension of this approach to cover design and implementation as part of rule‐centric information systems engineering.

Therefore, the overall contribution of this work relates to the provision of guidance for identifying business policy and tactics at an intentional level (through the investigation of the rationale behind them) and for transforming relevant models to the operational level, where business rules are linked to business processes, information and systems.

Although the business rule concept has been examined from different points of view over the past years, the paper attempts to bridge the gap between approaches that see rules as extensions of business goals, other approaches that consider rules as limitations on the way business activities are performed, and finally, approaches according to which rules constrain the creation, modification and deletion of information entities.

This paper investigates whether and how G2G collaboration for policy and decision‐making can be effectively supported by an appropriately developed information system.

The research method adopted in this paper follows the “Design Science Paradigm”, which has been extensively used in information systems research.

As resulted from the case study described in this paper, the proposed system has significant potential for supporting G2G collaboration for policy and decision‐making. It can support the collaborative understanding of social problems and needs, and the development of alternative actions or solutions for them. In addition, it can support the collaborative development of detailed action plans for the selected alternative(s). During the implementation of these actions, the system can be used for the collaborative monitoring of them, the identification of implementation problems and issues, and the development of alternatives for managing them. Finally, it can be also used for the collaborative evaluation of these actions by the involved public organizations, as well as the citizens and groups who are their recipients.

Enhanced public policy and decision‐making through the use of the proposed web‐based system.

The main contribution of this paper lies in the development of a web‐based system for supporting the G2G collaboration required for public policy and decision‐making in the public administration, as well as the creation, leveraging and utilization of the relevant knowledge. The proposed system allows for distributed, synchronous or asynchronous, G2G collaboration and aims at aiding the involved public organizations by providing them a series of argumentation, decision‐making and knowledge management features.

Knowledge sharing is an important way to improve the knowledge system of industrial construction, and the supervision mechanism is an important way to improve the efficiency of knowledge sharing. However, some research works and practices indicate that the effects of applying the supervision mechanism are not obvious. Therefore, the purpose of this paper is to propose an incentive method of knowledge sharing based on the supervision mechanism for promoting knowledge sharing among member enterprises in the industrial construction supply chain.

A basic incentive model and an optimization model of knowledge sharing in the industrial construction supply chain based on the supervision mechanism were developed via the principal–agent theory. Weighted coefficients of explicit and implicit knowledge sharing were introduced into the basic model, while the supervision reward was added into the basic model of the optimization model. The effect of these two models was compared and analyzed via numerical simulation.

The optimal incentive coefficient and effort level of knowledge sharing can be obtained by solving the two aforementioned models. The results of the comparison between the two models indicate that the introduction of a supervisory reward improved the effort level and expected earnings produced by knowledge sharing, but reduced the confirmed equal earnings of member enterprises in the industrial construction supply chain.

Mutual transformation between tacit and explicit knowledge was not considered, and supervisory costs were also not considered, in the estimation of the output of knowledge sharing.

The new models proposed by this study provide theoretical guidance for the design of knowledge sharing incentive measures in the industrial construction supply chain based on the supervision mechanism. The findings suggest that member enterprises should pay attention to the costs of knowledge sharing, in order to obtain more benefits.

This study introduced the weight coefficients of explicit and implicit knowledge sharing into a previous incentive model, proposed an incentive optimization model of knowledge sharing in the industrial construction supply chain based on a supervisory mechanism, and revealed the change rules of related variables that affect the model with the change in weight coefficients. The findings verify the effectiveness of introducing supervisory reward measures and extend the range of theoretical application.

An enterprise social network (ESN) is part of the landscape of information reform by enterprises, using Web 2.0. In terms of the marketing targets of typical Web 2.0 techniques, enterprise knowledge sharing in Web 2.0 can be classified into different types (individual interaction type, group interaction type, social interaction type, real‐time interaction type and delay interaction type). The purpose of this paper is to summarize the features and modes of different enterprises' knowledge sharing and study enterprise knowledge sharing quantitatively from an ESN perspective by selecting real‐time interaction type as the case.

Because of the area of research, the authors supplemented social network analysis (SNA) with a mathematical modeling method and additional in‐depth interviews.

The Web 2.0 era provides the opportunity to quantify knowledge sharing. Also, SNA can quantitatively and visually diagnose the knowledge sharing status of the enterprise and guide the enterprise's knowledge‐sharing process.

Only a case study regarding real‐time interaction type is presented; other types of interaction are not studied empirically.

SNA, combined with a mathematical modeling method and additional in‐depth interviews with team leaders or key managers in organizations, can diagnose quantitatively, visually and comprehensively the knowledge‐sharing status of the enterprise.

This paper systematically summarizes the features and modes of Web 2.0 enterprise knowledge sharing, and the multiple‐method research design represents a sound approach to targeting enterprise knowledge sharing.

In this research, collaboration attributes related to the firm's intrinsic and extrinsic facets at pertinent levels (i.e. enterprise, strategic, operational, and tactical levels) for construction equipment OEMs (original equipment manufacturers) operating in India have been quantified and modeled.

For modeling the intra-firm collaboration at respective organizational levels, relevant attributes have been populated employing literature review followed by subsequent validation from pertinent focus groups. The focus groups comprising professionals working in the construction and mining equipment industry in India aided us in estimating the extent of interdependencies and influences within/amongst collaboration attributes. The collaboration attributes and respective interdependencies/influences are modeled employing the concept of graph theory wherein the individual attributes are represented using vertices and influences/interdependencies are represented using edges. The collaboration indices resulting from the variable permanent matrix have been derived as well.

Scenario and subsequent sensitivity analysis are performed. This research discusses the significance and aspects related to various collaborative attributes and the interrelations amongst them. Further, the research also evolves quantitative measures of collaboration indices at enterprise, strategic, tactical and operational levels by employing a graph-theoretic approach (GTA). The authors have also extricated and discussed a number of meaningful implications from both the perspectives of interorganizational relationships (IORs) and the normative theory of organizations using a cross-case analysis of five firms having operations in India.

The research would aid organizations (particularly those belonging to the construction equipment sector) measure the efficacy of collaboration in respective value-chains at strategic, tactical and operational levels. From the theoretical perspective, the integration of the IORs and normative theory of organizations enables looking at the intra-firm collaboration problem from a multi-dimensional standpoint involving activities, performance measures, action initiation, communication, shades of top management, level of activity, etc.

This paper aims to offer a comprehensive examination of the various solutions currently accessible for addressing the challenge of semantic interoperability in cyber physical systems (CPS). CPS is a new generation of systems composed of physical assets with computation capabilities, connected with software systems in a network, exchanging data collected from the physical asset, models (physics-based, data-driven, . . .) and services (reconfiguration, monitoring, . . .). The physical asset and its software system are connected, and they exchange data to be interpreted in a certain context. The heterogeneous nature of the collected data together with different types of models rise interoperability problems. Modeling the digital space of the CPS and integrating information models that support cyber physical interoperability together are required.

This paper aims to identify the most relevant points in the development of semantic models and machine learning solutions to the interoperability problem, and how these solutions are implemented in CPS. The research analyzes recent papers related to the topic of semantic interoperability in Industry 4.0 (I4.0) systems.

Semantic models are key enabler technologies that provide a common understanding of data, and they can be used to solve interoperability problems in Industry by using a common vocabulary when defining these models.

This paper provides an overview of the different available solutions to the semantic interoperability problem in CPS.