On the Move to Meaningful Internet Systems. OTM 2017 Workshops

Highly customized products with shorter life cycles characterize the market today: the smart manufacturing paradigm can answer these needs. In this latter production system context, the interaction between production resources (PRs) can be swiftly adapted to meet both the variety of customers’ needs and the optimization goals. In the scientific literature, several architectural configurations have been devised so far to this aim, namely: hierarchical, heterarchical or hybrid. Whether the hierarchical and heterarchical architectures provide respectively low reactivity and a reduced vision of the optimization opportunities at production system level, the hybrid architectures can mitigate the limit of both the previous architectures. However, no hybrid architecture can ensure all PRs are aware of how orienting their behavior to achieve the optimization goal of the manufacturing system with a minimal computational effort. In this paper, a new “hybrid architecture” is proposed to meet this goal. At each order entry, this architecture allows the PRs to be dynamically grouped. Each group has a supervisor, i.e. the optimizer, that has the responsibility: (1) to monitor the tasks on all the resources, (2) to compute the optimal manufacturing parameters and (3) to provide the optimization results to the resources of the group. A software prototype was developed to test the new architecture design in a simulated flow-shop and in a simplified job shop production.

Many of the current manufacturing systems are still implemented as sequential inflexible production lines. This creates difficulties to fulfil the customer request for customized products. The production of customized products is accompanied by major changes in the production infrastructure. To support more flexible production, the sequential production lines nowadays start to change to workshop production. In that case all production systems will be grouped by their tasks, e.g. all drilling machines are located in the same place. A manufacturing system stands for the different involved hardware and software components at the manufacturing process. Each manufacturing system is connected with the help of the shop-floor IT. The term shop-floor indicates the productive area of a factory and includes the operative work. Shop-floor IT includes the information processes and IT solutions that control, secure and record product activities. Therefore the shop-floor IT supports directly the execution on field level. The model based view of a production process simplifies the understanding of the product lifecycle and planning. To optimize and speed up building and changing of product processes, the modular shop-floor IT has been developed by technologies derived from cyber physical systems and internet of things. However, interoperability issues such as different implementation of controls and process variations are a major challenge.

In Sensing, Smart, and Sustainable (S^3) Enterprises information is not only gathered from an internet of production things supporting smart decision making, but this information also allows execute processes automatically. These processes need to be interoperable for sustainable operation while enabling dynamic adaptation. In this paper we present a development framework successfully tested in a European project demonstrating key features of subject-orientation for production process support across the IEC 62264 control hierarchy layers. It aligns business planning and logistics with manufacturing operations and production management, utilizing a communication protocol choreography, message passing and data exchange between production-relevant behavior encapsulations. The overall system is modular and adaptive, where interoperability is supported through process models.

With the increased globalization of the economy, the competitiveness has become ubiquitous and enterprises need to be reactive and to collaborate with different stakeholders to survive in its environment. Within this context, the choice of suitable collaborators and partners with whom collaboration may happen without problems is a key factor of success. In this paper, an ontology-based approach to support interoperability and help enterprises to solve interoperability problems before they occur is proposed.

Enterprise Architecture (EA) and Enterprise Modelling (EM) are systems engineering tools to understand, design, develop, implement and integrate complex enterprise and information systems. ISO 15704, 19439 and 19440 define fundamental concepts and principles of EAs and EMs, which are emphasized as the top standards of smart manufacturing by NIST’s smart manufacturing ecosystem and relative standardization roadmap. Since the three international standards will soon be subject to revision, this paper rethinks the basic principles of EAs and EMs, and presents a General Enterprise Modelling (GEM) framework and a relative EA (GEM-EA). GEM-EA provides tools and methodology of model-based systems engineering (MBSE) to enterprise and automation systems integration. GEM involves a set of models and methods to describes different aspects of a system and covers its lifecycle. GEM and GEM-EA can greatly facilitate the process of enterprise diagnosis, business process reengineering and information system implementation.

A manufacturing information system is targeted for use anywhere production is taking place. Modern manufacturing information systems are generally computerized and are designed to collect and present the data which production operators need in order to plan and direct operations within the production. The application of mobile and wearable devices can support operators’ tasks without distracting them from their core duties. In this paper, we present an approach towards a wearable manufacturing information system that is able to implement decentralized production monitoring and control and supports users in their core tasks. Building upon acquired and digitally stored production data, these devices provide different user-specific information and services when required. A practical example from corrugation industry highlights advantages of mobile devices compared to conventional centralized systems in the field of manufacturing.

When recognizing the need of involving stakeholders for mapping role-specific requirements to system behavior, semantic interoperability is becoming a crucial issue in development. Elicitation, analysis, and specification need to go beyond a purely functional perspective on system development and integrate interactions relevant for stakeholders. We discuss a behavior perspective to mutually adjust role-specific elements, and in this way design organization-relevant support systems. Since interacting role element specifications can be automatically executed, designs can be evaluated interactively, and digital support systems can be developed incrementally.

Interoperability is of high focus for the manufacturing industry that is currently undergoing a transformation into the fourth industrial revolution. Factories are adopting smart technologies and implementing decentralized and human-centered manufacturing systems. To use ICT for cognitive automation and information sharing is becoming more common and increasingly important for factory workers. To implement these ICT solutions, it is important to consider their interoperability with the entire manufacturing system. This study suggests a framework that combines the context of human-centered manufacturing with areas of concerns in enterprise systems. The framework is presented and discussed regarding its usefulness to assess and/or improve system interoperability.

Big data play a central role in eHealth and have been crucial for designing and implementing clinical decisions support systems. Those applications can avail on data analysis and response capabilities, often empowered by Machine Learning algorithms, which can help clinician in diagnostic as well as therapeutic decisions. On the other hand, in the context of eSociety, eCommunities can be essential actors for managing and structuring medical data. In fact, they can support in gathering, providing and labeling data. This last task is highly relevant for medical Big Data, as it is a key point for supervised Machine Learning algorithms, which need an extensive data annotation process. This improves prediction and analysis capabilities of the algorithms on large datasets. Our approach on the medical Big Data labeling problem is the design and prototyping of a crowdsourcing collaborative Web Application, used for the annotation of medical images, that we named Medical Monkeys. Under the principles of mutual advantage and collaboration researchers, online gamers, medical students and patients will be involved, within this platform, in a virtual and mutually beneficial cooperation for improving Machine Learning algorithms. Using our application on large scale data analysis, algorithms for image segmentation will become useful for clinical decisions support systems. Our application is the result of a collaboration of several universities and research institutes and has, as principal aim, the integration, in form of gaming tasks, of eCommunities for the implementation of a more accurate analysis and diagnostic on MRI or CT images.

The purpose of this paper is to realize a comparative analysis of relational and non-relational database management systems. Both conceptual and technical characteristics are introduced, presenting the benefits and disadvantages of each model, using a hybrid application. The application, named SuperstoreSalesReporting, generates comparative reports which describe the technical characteristics of both SQL and NoSQL databases based on the executed operations. The application constitutes the contribution of this study, together with the creation of the SQL Server internal processes for migrating data from a flat file into a star schema.

Product classification standards like eCl@ss and UNSPSC define tens of thousands of product categories, and some standards additionally provide specific product property definitions and enumerated values. Many organizations hold respective meta-data for their products readily available in back-end databases. While many approaches have been presented for using such standards for more granular product information on the Web of Data, none has so far received mainstream adoption. This can be partly explained by legal, technical, and administrative barriers for adoption. In this paper, we describe a novel approach for using product classification standards in Web data markup in Microdata and JSON-LD syntax that does not require the availability of proper Web ontology variants of the underlying standards. We can show that the approach can provide the very same effect for the consumption and interpretation of the resulting mark-up in a Linked Data and Semantic Web context. Our proposal has already been integrated into the official version of schema.org and can be readily used for research and business applications.

The paper proposes an ongoing application and its corresponding use cases for managing user preferences and resource consumption (electric energy, gas, water) in a smart home. The application brings innovation both at front end and back end levels, via intuitive computer-human interaction and ontology-based user modeling, aiming to (1) provide an easy to use graphical user interface in order to assist residential users in managing their resources in a smart home setting; (2) collect resource consumption data and perform analysis on these data for prediction of future consumption rates and costs; (3) make recommendations for the resource management in a smart home; and (4) provide statistics regarding resource consumption management. The concept will be validated with families of residential users from the city of Cluj-Napoca.

The widespread usage of semantic resources such as SPARQL endpoints and RDF data dumps by an ever growing number of users requires steps to be made in order to ensure the correctness of the provided data. DBpedia, a major node of the LOD cloud is a contributor of both types with its content deriving from Wikipedia. This paper presents our effort towards creating alternative links for the DBpedia’s bibliographic references motivated by the “DBpedia citations & references challenge”. We present the procedure of the link creation by utilizing a Java library that we have developed, called BibLinkCreator, which extracts data from the DBpedia’s references RDF data dump provided during the competition, and other RDF data dumps (available for download or collected via APIs) relevant to bibliographic records, based on unique identifiers such as ISBN, and links citation URIs after matching identifiers and ensuring the similarity of other properties.

In this paper we discuss the introduction of a course on fact-based modeling in the first year of the bachelor program Knowledge Engineering at Maastricht University. We will discuss the course built-up and the course assessment.

This paper is concerned with the concept of grounding enterprise models in terms of an underlying fact-based model, as a way to add more meaning to these enterprise models. We motivate the need for doing so in terms of a fundamental understanding of conceptual modelling, and enterprise modelling in particular. We also clarify why, next to e.g. adding more meaning by using formal semantics, or mapping the model to a foundational ontology, it remains important to ground enterprise models on fact-based models that capture the natural way in which people converse about/in their domain. The presented concepts are illustrated by means of a running example, while also reflecting on, and summarising, the results of earlier experiments in grounding different enterprise models.

With the ever-changing dynamic Information and Communications Technology environment and the new shared deployment options for computing, a paradigm shift has occurred, which enables ubiquitous and convenient computing on a pay-as-you-go basis. Access on demand has become available to networks of scalable, elastic, self-serviceable, configurable physical and virtual resources. This paper updates the previous paper that addressed early ISO Committee Draft (CD) work on Cloud Computing by ISO ISO/IEC JTC1 SC38 (in collaboration with ITU-T SG13/WP6 for Cloud Computing), and models the full and expanded ISO Cloud Computing Reference Architecture and Service Level Agreement (SLA) using Fact Based Modeling (FBM) methodology. FBM has allowed us to distill the concepts, relationships and business rules - thereby capsulizing the Cloud Computing standards to enable understanding, and also exposing the strengths and weakness of the models, and thus allowing for identification of any gaps towards furthering the ISO standard.

In The Netherlands, all legislation regarding infrastructure and environment is described in more than 250 legal documents. In 2019 the new “Omgevingswet” (translated as “Environment and planning act” [1, 4]) was supposed to come into force. This law modernizes, harmonizes and simplifies the mentioned regulation and integrates this myriad of legislations, decrees and regulations into one legal framework. To be able to apply the environment and planning act, legal analysis of this legislation is required. The Dutch Rijkswaterstaat ministerial department [2, 3] has developed an approach to analyze (interpret), structure and store the rules contained in the legislation. In their approach, all rules are associated with activities, which form a functional structure. This functional structure is the baseline from which relevant parts of the legislation is grouped. This paper describes how this approach works, how it is supported by Fact Based Modeling and the software environment used (Cognitation) to perform the document analysis.

In 2012 some Dutch government services organizations, academia and innovative companies decided to establish a co-creation, named Blue Chamber, with the aim to develop a national protocol to “translate regulations” into a durable, IT-independent model or specifications for interactive regulation based services. Regulation here means the union of laws and decrees, both government and ministerial. Such a protocol acts like a process and each process requires a conceptual data structure or IT-independent reference model. After 5 years of research, development and validation, version 1 of the Reference model is ready for publication. The Dutch Government has decided to provide IT-based services and enforcement actions based on as many laws and decrees as appropriate. The core of this Reference model will be described in this paper. The CogNIAM variant of Fact Based Modeling has been used to develop the Reference model, using field-testing with the associated prototypes.

The theory and engineering of states and transitions has been developed since WWII, with considerable success. Since 2012 some Dutch government services organizations, academia and innovative companies decided to establish a co-creation, named Blue Chamber, with the aim to develop a national protocol to “translate the regulations” into a durable, IT-independent model or specifications for IT-supported, interactive, regulation based services. Regulation here means the union of laws, associated decrees and policies, both government and ministerial. Such a protocol acts like a process and each process requires a conceptual data structure or IT-independent reference model. During the analysis of the deep structure of regulations and the associated services it became clear that the theory and application of states and transitions could be applied as innovative tool in the process of specifying the durable specifications. In this paper we describe this approach using a small but significant law and associated services.

The theory and engineering of states and transitions has been developed since WWII, with considerable success. Since 2012 some Dutch government services organizations, academia and innovative companies decided to establish a co-creation, named Blue Chamber, with the aim to develop a national protocol to “translate the regulations” into a durable, IT-independent model or specifications for IT-supported, interactive, regulation based services. Regulation here means the union of laws, associated decrees and policies, both government and ministerial.Such a protocol acts like a process and each process requires a conceptual data structure or IT-independent reference model. During the analysis of the deep structure of regulations and the associated services it became clear that the theory and application of states and transitions could be applied as innovative tool in the process of specifying the durable specifications. In this paper we describe this approach using a small but significant law and associated services.

Organizations, and financial organizations in particular, have to fulfil an increasing amount of regulations imposed by external entities. Moreover, these regulations impose shorter lead times and require much more granularity of the data that needs to be reported than traditional reports. In addition, lineage requirements are imposed more strictly and at a faster pace. For organizations to fulfil all these requirements, having insight in the link between the reported data and the source provides (part of) the key to success. To achieve this insight, the creation of a common understanding forms the foundation.

This paper describes a research approach to an evaluation of a Design Science Research (DSR) Artefact in the field of Agile Enterprise Design. The Artefact, the result of a program which engineered and combined three methodologies, is developed on the basis of an emerging concept since 2009 and recently (in 2016) implemented in several information systems. Because of the availability of several implementations of the artefact, a post evaluation based on hypothesis testing of the real artefacts is a feasible and necessary next research step, on which will we elaborate in this paper. Rather than a research question, three hypotheses are proposed in this research.

AIPLA 2017 Spring Conference turned out to be the most interesting event by AIPLA’s standing, especially as to the IDL. This paper upfront confirms the truth of this assumption: The event provided the best survey/comment up to now concerning the recent nationwide §101/Alice-guidelines and similar international developments. Section 2 namely reports that the AIPLA 2017 Spring Conference was the first internationally attended meeting of the large expert community of 35 USC Substantive Patent Law (“SPL”) that in several panelsshowed the by now vastly stabilized understanding of the Supreme Court’s Alice decisioncomplained of the still total helplessness as to an urgently needed key to ─ or, to the point: ‘clou’ of ─ the Supreme Court’s Alice analysis, i.e. its MBA-framework, which would clearly/convincingly, totally robustly, and broadly acceptably separate patent-eligible (“PE”) from nPE inventions.But this ‘clou’ exists, even a ‘big clou’, as the latter enables by IDL for any ETCI to prove rationally & mathematically •trivially and •semi-automatically its totally robust SPL satisfaction (comprising its PE).

User Experience and Agile Software Development are both user-focused iterative methods. Usually they both are difficult to realize as per the theoretical concepts in real world development. The challenge is how to integrate them in the development process. There is a need for gaining perspective from all the stakeholders which includes not only customers but internal teams involved in development. This approach will lay the foundation of taking care of the requirements from both the product and human perspective so that the development and expectations are consistent.The paper will present the framework for managing the design of processes for each stake holders – Developer, QA, Customer and Management. The framework tries to resolve the complexity that evolves through collaboration between self-organizing, cross-functional teams.

With the Physical Internet (PI), a global economic transformation towards a more holistic consideration and collaboration of different agents is promoted. Its goal is the implementation of global sustainable logistics by increasing the utilization of available resources. This should be reached by developing a network in which goods of different organizations are transported, stored and handled. One aspect of the PI is the optimization of the transport procedure. In this paper, potential optimization models for a subset of three key elements of the PI, the containers, movers (all kinds of transportation means), and nodes (all kinds of locations), are presented. Moreover, corresponding algorithmic approaches are proposed. The novel modeling approach of optimization networks (ON) with the objective of finding an overall optimized solution considering the involved interrelated subtasks in a holistic sense is compared to highly reactive solution methods based on rules that are learned offline. With the proposed approaches, interoperability between different (economic) agents and (software) systems is supported. The goal of multidisciplinary collaboration of different participants and their integration into one PI network should be approached.

Today, the Industry 4.0 paradigm has penetrated the everyday processes and operations of manufacturers, reframing traditional value chains and delivering novel products and services. Products and services need to be appropriately blended in the path to servitisation, yet manufacturers still struggle with gaining insights and collaborating with all involved stakeholders in the most effective way in order to design smart and connected products-services. In this context, this paper presents how smart furniture product-service bundles have been designed according to the needs of the furniture industry. Such bundles provide value added services during the whole Product Life Cycle of the furniture and range from IoT-enabled workplace monitoring to collaborative ideation and sentiment analysis in order to deliver manufacturing intelligence.

The dev-ops era has taken the IT world by storm and it has redefined the way the code is deployed into production environments. There are many tools which facilitates the standardization of flow of the artifacts onto the nodes. These workflows are certainly a great way of managing what goes into which environments but there is a lack of consideration of design and planning in the way it is done leading to more frequent patches. Many a times we firefight to keep the environments stable but we tend to ignore the considerations of a new feature to be designed. These scenarios are common in most of the cloud applications so there is a need to design the workflows, the code, the acceptance criteria and the preventive conditioning. The methods which are effective for scenarios are explored in this paper and concepts are presented to work towards a dynamic development environment.

With increasing automation of business processes, the possibilities for the automation of routine business decisions grow: granting a loan, insurance or energy premium; simple diagnosis; sensor control systems in manufacturing; etc. are not uncommon automated decisions anymore, deployed and supported by systems and processes. Although each decision is relatively small and operational, they come in large numbers so that they eventually represent a large value for organizations. Reconciling and integrating processes and decisions is therefore of paramount importance, both when it comes to modelling the two concerns consistently, as well as in terms of automated discovery of process-decision models. This paper outlines a research proposal for the development of a framework allowing a sound integration of processes and decisions both for modelling and mining, relying on the newly developed Decision Model and Notation (DMN) standard.

Business organizations acknowledge the importance of Information Systems (IS) to cope with their responsibility in environmental degradation. The problem with current IS contributions is that the crucial role of process-centered techniques is often ignored. Moreover, a common understanding of environmental sustainability is missing. In response, this paper introduces Green Business Process Management (BPM) which focuses on the ecological impact of business processes. The concept of a circular economy is introduced to concretize environmental sustainability at the organizational level. Following the design-science paradigm, this paper provides a work plan to examine the theoretical and practical evidence on Green BPM instruments. The research methods we propose are a systematic literature review (SLR), expert panels, case studies and field-testing.

Due to the use of thousands of often very complex process models, having them immediately usable towards their purpose is of great economic benefit. In order to maximize usability, process models must be intuitive and easily understandable. In other words, processing the information contained within the process models must enable a successful completion of the task for which the model is being used. Recently, research efforts into the effects of user characteristics on understandability have increased. However, current limitations create promising research possibilities, particularly with regard to the use of realistic process models and direct data collection techniques. This thesis will contribute to the existing body of knowledge by investigating domain knowledge as a fundamental user characteristic and utilizing eye-tracking as a direct data collection method while using realistic, complex process models. The end goal of this research is to propose an automatic process model tailoring technique, with the aim of enhancing a user’s understanding and thus their performance. As of now a pilot study has indicated the existence of distinct reading strategies, which establishes the viability of the proposed future work.

Technologies of the Semantic Web stack promise to alleviate some of the challenges related to data integration on a massive scale and high level of heterogeneity. This paper explores their application in the smart cities domain with a focus on energy efficient districts. We develop an ontology grounded in several well-established vocabularies to leverage their shared semantics and facilitate data interoperability and we apply the developed ontology to integrate state-of-the-art energy simulation facilities into a general district-level monitoring framework.

The market of Product Lifecycle Management (PLM) applications has changed into a complex landscape of heterogeneous systems in recent years. Consequently, it has become increasingly challenging for enterprises to identify a PLM application that meets their requirements and that can be successfully integrated into their existing IT systems. The approach presented in this paper aims at developing a decision-supporting model of the IT system landscape that provides different analysis tools based on existing IT systems. The model which is expressed by an ontology is intended to represent data flows between the different IT applications in order to provide relevant information through requests and rules in further proceedings.

This paper presents a representation for storing OBDA mapping information in an easily understandable, user-accessible, and extensible format in dedicated metadata tables in the relational database.

Among models and information about economic phenomena that help to understand how enterprises produce value, Accounting and Financial Reporting still play a leading and regulative role. The regulative role is established by enforceable International Financial Reporting (FR) Standards. Ontology engineering methods, which have proven to cope with difficult standardization issues, are seldom used in developing these standards. Furthermore, no widely accepted computational ontology, covering the concepts and relations of FR, and the Information Systems supporting FR, exists. This paper proposes an initial version of the Core Ontology of Financial Reporting Information Systems (COFRIS) grounded on the Unified Foundational Ontology (UFO).