A comprehensive and generic machine tools data model

The data model of machine tools plays a key role to share and manage machine tools information among modern manufacturing systems and has been considered as a fundamental basis for achieving various manufacturing activities such as process planning, machining simulation and production scheduling. Although research into modelling machine tools has been done, these modelling approaches are either machine vendor specific, or limited and incomplete in their scope to represent machine tools. Therefore, a comprehensive and generic machine tools data model (CGMTDM) is proposed in this paper. The proposed data model is constructed based on the oriented-object EXPRESS language, which not only includes the information of mechanical elements, but the information of the electro-mechanical and electronic elements. The case study is used to demonstrate the proposed data model at the end. It has been concluded that CGMTDM can consistently, completely and flexibly represent the information of machine tools. [Received 14 April 2016; Revised 4 September 2016; Accepted 8 September 2016]

Data modelling patterns provide a good guideline for creating a data model of a software or service. However, there is a lack of such a pattern respecting data protection requirements that an online service should satisfy. Especially for social media services, this is a relevant topic as end-users' data are collected and processed. In this work, we introduce conceptual data model in different abstraction layer: a generic and an application specific layer. The generic conceptual data model for a social media service can be refined to present the conceptual data model of a specific social media service. The primary target audience of this work are academics, who are interested in the research on social media service analysis with respect to privacy and data protection. However, the generic conceptual data model of social media services may support social media service designers in obtaining an overview of data that a service collects and processes for service provisioning. By using our descriptive conceptual data model, service providers are supported to gain valuable information for addressing data protection regulations and to document collected and processed data in a transparent and understandable way. For example, the service providers can use the data model (created by refining the generic conceptual data model) for generating more transparent and usable privacy policies for their end-users. Furthermore, the created data model supports communication of different stakeholders, i.e. service developers, service providers and other involved stakeholders. We illustrate application of our generic conceptual data model with refining it for the online dating application Tinder. We consider our generic conceptual model for capturing data model of social media services as a pattern candidate.

The constant irruption of new sensors is a challenge for software systems that do not rely on generic data models able to manage change or innovation. Several data modeling standards exist. Some of these address the problem from a generic perspective but are far too complex for the kind of applications targeted by this work, while others focus strictly on specific kinds of sensors. These approaches pose a problem for the maintainability of software systems dealing with sensor data. This work presents ASTROLABE, a generic and extensible data model specifically devised for trajectory determination systems working with sensors whose error distributions may be fully modeled using means and covariance matrices. A data model relying on four fundamental entities (observation, state, instrument, mathematical model) and related metadata is described; two compliant specifications (for file storage and network communications) are presented; a portable C++ library implementing these specifications is also briefly introduced. STROLABE, integrated in CTTC’s trajectory determination system NAVEGA, has been extensively used since 2009 in research and production (real-life) projects, coping successfully with a significant variety of sensors. Such experience helped to improve the data model and validate its suitability for the target problem. The authors are considering putting ASTROLABE in the public domain.

Machine tool capability profiles for representing machine tool health

The machine tool data model of STEP-NC (ISO 14649) was conceived as a necessary extension to the original STEP-NC set of standards to make efficient control possible. The intention of this paper is to describe the background to the data model as well as related research work building on a higher level of information than can currently be found in the control information. The development of STEP-NC controllers promises improved manufacturing and resource use. However, even with legacy controllers there are advantages in using STEP-NC as an intermediate representation. This paper describes how the data model for describing machine capability was developed and what can be delivered by using this standard data model for machine tool. A machine tool selection algorithm is developed in order to validate the data model. Technical issues were derived from developing a system for process planning based on STEP-NC. Machine tools are selected automatically by the comparison with machine capability, work space and tolerance with the proposed data model. This function can contribute reconfigurable manufacturing systems and distributed and multi-controller-based manufacturing environment.

Developing High Quality Data Models

Cyber-Manufacturing System (CMS) is a vision for the factory of the future, where physical manufacturing resources and processes are integrated with computational workflows to provide on-demand, adaptive, and scalable manufacturing services. In CMS, functional manufacturing components in a factory floor are digitized and encapsulated in production services; and are accessible by users throughout the network. CMS utilizes data-centric technologies to program manufacturing activities in factory floors. Leveraging advanced technologies, CMS can provide robust solutions to achieve better manufacturing agility, flexibility, scalability, and sustainability than from traditional factories. While data is the main driver of the manufacturing activities in CMS, the lack of (i) a generic data model of explicit representation of the entities and stakeholders in CMS and (ii) workflow definition and analysis for service-orientated functionalities and manufacturing intelligence of CMS is still hindering the implementation of a fully executable CMS. To address such problems, this paper (i) formalizes a data modeling of CMS using Entity-Relationship (E-R) diagram, (ii) presents the definition and analysis of workflows along with data pipelines and Extract/Transform/Load (ETL) processes that automate the entire lifecycle activities in CMS and (iii) deploys the proposed data model and workflows in a Web-based application, and (iv) tests the functionality of this application with an industrial case and eventually validates the proposed data model and workflows.

XQuery as a retrieval mechanism for longitudinal multiscale forest resource data

Hair-oriented data model for spatio-temporal data representation

GIS is increasingly used in poverty mapping but there is no generic data model for database development. Examples exist already of industry‐specific models. Having such a data model eases the complexity of incorporating spatial data in poverty assessments. This article raises awareness about the need for a generic poverty data model for use in poverty mapping. It seeks to stimulate a lively debate that will lead to the development and adoption of such a data model. The ultimate goal will be to get to some level of standardization for common data types that would facilitate spatial data use in poverty assessment and sharing among poverty projects. This article is a first step at developing a data model for poverty mapping at a conceptual level. Handling multidimensional social problems, such as poverty, using a spatial framework can be challenging because of the myriad of poverty indicators in use. Employing the entity‐relationship approach, a conceptual model is developed in the current article that identifies the key thematic layers, entities, and relationships. The conceptual model produced is useful for modeling the content of the database for use in assessing and monitoring poverty.

SkiQL: A unified schema query language

Sub Saharan Africa region is synonymous with various health problems ranging from diseases (such as malaria, measles, and tuberculosis), environmental to other public health related problems. In the region, most of the diseases and health related problems are as a result of environmental problems. Despite all the health problems, sub Saharan Africa most especially Nigeria lacks national health database. In the country, there is inadequate health care delivery system and patchy epidemiological data couple with the fact that there is no reliable method of epidemiological data collections. In order to solve these problems, this paper proposed a well organised conceptual public health data model for Nigeria, which addresses all the health problems and their causes. The proposed data model could be used to develop any health related system such as national public health database system, and disease surveillance system, which we intend to develop from this, proposed data model. The model is motivated by an interoperable disease surveillance and prediction system in Nigeria. We started with review of the existing health data models which include disease surveillance data models developed for Nigeria and Kenya which we modified and extended to develop a spatial conceptual public health data model in Nigeria. The proposed data model contributed to the existing health data models with its environmental health feature, which makes the model to be unique from other existing health data models. The model is developed using unified modelling language. We intend to make the model and health related systems that would be developed from the proposed data model open so as to allow other researchers most especially from sub Saharan Africa region and those that are interested in the region to contribute to the maintenance of the public health data model. The systems that would be developed from the proposed data model would make use of web feature services technology and allow interoperability with other health related systems. The proposed system would be able to capture, store, query, retrieve, and generate reports on any disease and the environmental problems that caused such health related problems among other things.

STEP-NC-based manufacturing is a promising approach for digital manufacturing applications. However, as STEP-NC data are machine tool independent, when implementing STEP-NC-based process planning and manufacturing, a comprehensive machine tool database is required to provide machine tool data for generating machine-tool-dependent process plans. A novel STEP-NC compliant machine tool data model named STEP-NCMtDm has been developed to realise STEP-NC based process planning and manufacturing. The goals of STEP-NCMtDm are to meet the data requirements for implementing STEP-NC data model in process planning and scheduling, and to support the distributed manufacturing environment. EXPRESS language is used for constructing the data model, and a web-based data model is also built to support distributed manufacturing scenarios by using the corresponding extensible markup language (XML) schema. A milling machine tool is used to evaluate the proposed data model. It has been demonstrated that STEP-NCMtDm can provide adequate information for STEP-NC programming.

BackgroundFlow cytometry technology is widely used in both health care and research. The rapid expansion of flow cytometry applications has outpaced the development of data storage and analysis tools. Collaborative efforts being taken to eliminate this gap include building common vocabularies and ontologies, designing generic data models, and defining data exchange formats. The Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) standard was recently adopted by the International Society for Advancement of Cytometry. This standard guides researchers on the information that should be included in peer reviewed publications, but it is insufficient for data exchange and integration between computational systems. The Functional Genomics Experiment (FuGE) formalizes common aspects of comprehensive and high throughput experiments across different biological technologies. We have extended FuGE object model to accommodate flow cytometry data and metadata.MethodsWe used the MagicDraw modelling tool to design a UML model (Flow-OM) according to the FuGE extension guidelines and the AndroMDA toolkit to transform the model to a markup language (Flow-ML). We mapped each MIFlowCyt term to either an existing FuGE class or to a new FuGEFlow class. The development environment was validated by comparing the official FuGE XSD to the schema we generated from the FuGE object model using our configuration. After the Flow-OM model was completed, the final version of the Flow-ML was generated and validated against an example MIFlowCyt compliant experiment description.ResultsThe extension of FuGE for flow cytometry has resulted in a generic FuGE-compliant data model (FuGEFlow), which accommodates and links together all information required by MIFlowCyt. The FuGEFlow model can be used to build software and databases using FuGE software toolkits to facilitate automated exchange and manipulation of potentially large flow cytometry experimental data sets. Additional project documentation, including reusable design patterns and a guide for setting up a development environment, was contributed back to the FuGE project.ConclusionWe have shown that an extension of FuGE can be used to transform minimum information requirements in natural language to markup language in XML. Extending FuGE required significant effort, but in our experiences the benefits outweighed the costs. The FuGEFlow is expected to play a central role in describing flow cytometry experiments and ultimately facilitating data exchange including public flow cytometry repositories currently under development.

Towards greener production, manufacturing companies face several challenges, for example peak load shaving or flexible production planning as parts of demand-side management (DSM). DSM uses processes that can be shut down, shifted, or controlled. Advances in digitalization in the energy sector and manufacturing systems create transparency which in turn offers new opportunities to commercialize energy flexibility potentials as optimally and automatically as possible. The variety of flexibilities in manufacturing systems and various dependencies of different kinds of complex manufacturing processes complicate the modelling and aggregation of flexibility. To overcome this challenge, we developed a method for the aggregation of energy flexibilities that is based on a generic energy flexibility data model. The method proposes a two-step approach to aggregate flexibilities cost efficiently and considers manufacturing specific limitations. For cost-efficient aggregation, we use in the first step the merit-order model known from the energy industry and in the second step the bin-packing problem originating from combinatorial optimization, adapted according to the generic data model. The two-step approach allows energy flexibilities to be aggregated across industries, facilities, and systems, thus ensuring broad applicability.KeywordsDemand-side managementEnergy flexible manufacturingEnergy flexibility aggregation