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With the increasing adoption of smart factories in manufacturing sites, a large amount of raw data is being generated from manufacturers’ sensors and Internet of Things devices. In the manufacturing environment, the collection of reliable data has become an important issue. When utilizing the collected data or establishing production plans based on user-defined data, the actual performance may differ from the established plan. This is particularly so when there are modifications in the physical production line, such as manual processes, newly developed processes, or the addition of new equipment. Hence, the reliability of the current data cannot be ensured. The complex characteristics of manufacturers hinder the prediction of future data based on existing data. To minimize this reliability problem, the M5P algorithm, is used to predict dynamic data using baseline information that can be predicted. It combines linear regression and decision-tree-supervised machine learning algorithms. The algorithm recommends the means to reflect the predicted data in the production plan and provides results that can be compared with the existing baseline information. By comparing the existing production plan with the planning results based on the changed master data, it provides data results that help production management determine the impact of work time and quantity and confirm production plans. This means that forecasting data directly affects production capacity and resources, as well as production times and schedules, to help ensure efficient production planning.

Background and objectives: Documenting patient data in psoriasis clinical practice can improve care, but standardized and transparent documentation is rare. The current project aimed to develop a data set for the documentation of psoriasis in daily practice. Material and methods: In four online Delphi rounds and one in-person meeting, 27 psoriasis experts allocated variables to a standard, an optimal and an optional data set. Most of the questions were standardized. Open questions were included to allow for the provision of reasons and to enlarge the data sets. Furthermore, in the in-person meeting we considered a) patients' attitudes and b) dermatologists' information on the current usage and acceptability in Germany. Results: The consensus approach resulted in a data set with 69 variables. The standard data set includes 20, the optimal data set 31 and the optional data set 18 variables. In summary, the data set can mainly be grouped into master data, general status and medical history data, medical history of psoriasis, status of psoriasis, diagnostics and comorbidity, therapies and patient-reported outcomes. Conclusions: The consensus recommendation of a standard, an optimal and an optional data set for routine care of psoriasis intends to be a decision-making aid and an orientation for both daily practice and further development of documentation systems.

Semantik web merupakan teknologi yang mampu memahami konteks seperti halnya manusia memahami konteks tersebut. Teknologi semantik dapat dimanfaatkan dalam berbagai bidang, salah satunya adalah klasifikasi topik skripsi mahasiwa. Banyak skripsi membahas topik serupa, tapi dengan peristilahan berbeda. Hal tersebut seringkali menimbulkan kesulitan dalam menentukan apakah suatu topik sudah terlalu sering dibahas. Oleh sebab itu, penelitian ini bertujuan untuk mengklasifikasikan dan memetakan bidang minat skripsi mahasiswa Program Studi S1 Teknik Informatika (TI) Unpad. Langkah-langkah yang dilakukan dalam penelitian ini adalah mengumpulkan data, menentukan entitas, implementasi ontologi, dan klasifikasi data menjadi beberapa kelas berdasarkan bidang minat di Program Studi TI Unpad (Sistem Informasi dan Multimedia, Kecerdasan Buatan dan Robotika, Jaringan Komputer, dan Metode Numerik). Langkah akhirnya adalah proses training dan testing data menggunakan algoritma k-nearest neighbour (KNN). Klasifikasi aktual data menunjukkan bahwa mayoritas skripsi di Prodi TI Unpad adalah tentang Sistem Informasi dan Multimedia, dengan presentase 50.23%. Sedangkan, klasifikasi prediktif data dengan algoritma KNN menunjukkan persentase 47.88%. Hasil yang berbeda tersebut diperoleh karena Confusion Matrix menunjukkan nilai sebagai berikut: AUC (0.711), CA (0.545), F1(0.578), Precision (0.669), Recall (0.545).

Master data governance is not a new field, and it has existed since the early 90s (8). However, the demand for master data governance has been rising recently due to the ever-increasing demand for cost optimization, faster product innovations, compliance with the set rules and regulations, and competitive advantage in the business field. One of the areas in which companies can achieve master data governance is through maintaining consistent data quality. Handling data is one of the pain areas in most companies due to the complicities involved in managing data. Still, companies that succeed in handling data compete well in their business since data leads to optimal decision-making. Data mismatch is putting so many companies projecting to accelerate their growth on brakes. This paper outlines the best practices of master data governance, which can help the companies solve and improve their odds in data governance and improve their business quickly, predictably when planning and implementing the decisions made.

The need for transportation for the community, especially in Tangerang Regency, which is used for holidays, tours, study tours, or pilgrimage. is a promising business opportunity for transportation companies.Because the need for transportation is important for the smooth running of its activities. PT. Sumber Jaya Trans Tangerang, which is involved in passenger transportation services, is one of the companies engaged in this field. In its operation still uses a manual system in renting buses. Many obstacles occur in this bus rental, such as business processes that have not been computerized, and data storage that is less effective and efficient. The research method in the analysis of the system used is PIECES which consists of Performance, Information, Economy, Control, Efficiency and Service. The system design uses object-oriented analysis method with Unified modeling Language (UML), the programming language used is PHP and the database used is MySQL. This system is web-based and uses the PHP 7 programming language, Web Design with CSS Bootstrap, Laravel Framework and MySQL for database design, while supporting software used in making programs is Visual Studio Code. In this research, a system has features such as master data, transactions, bus schedules, destinations, calendars, transaction reports, road warrant reports and activity logs. With this bus rental system, the bus rental process that is running will be more effective and efficient.

Production tends to become decentralized to provide more flexibility and robustness. Hence planning and control is also shifting to decentralized solutions to cope with a changing product mix. We present an intensive simulation study of different types of production and analyze the influence of product structure, product complexity and multiple use of materials. We show for which type of production self-organizing planning and control performs best. For this, we give a brief introduction to our self-organizing production and outline how we generate a wide variety of production master data that are freely customizable in terms of their statistical parameters, like product complexity, multiple use of materials and degree of organization, to reflect different types of productions. The results of our simulation study show the advantages of our self-organizing production.

Many companies have implemented technology in conducting their business, one of them is by using information systems in managing their business. The business process that runs on the Konveksi A&N is still manual because the Konveksi A&N has not implemented or is familiar with information systems like other companies has. This causes all the data collection process of goods, production, and transactions are all documented in different books, making it possible for errors in recording and calculating the data. In addition, the owner also needs to come directly to the location to find out new data or updated data where this takes more time. This research aims to establish a web-based system that can make business processes in Konveksi A&N more effective. This web-based system will be built using a system development methodology in the form of a prototyping method that uses the Hypertext Preprocessor (PHP) programming language. System modeling was developed using UML 2.5, use case diagrams, activity diagrams, and class diagrams. The final result of this study is a website-shaped information system that can document all data contained in the Konveksi A&N such as the existence of a master data that contains all the data of convection, production data, and also transaction data to facilitate the owner in checking back all activities that are occurs in Konveksi A&N. There are also some reports about the transaction that can display information related to data contained in the system.

MarketPlace of livestock is engaged in the business of selling and purchasing which broadly has the activities of selling and purchasing animals. Usually have several system Admins who work and control an application system by handling also the development of businessmen in the application, including making reports and managing master data. In this study business process observations were made from observations of free-range applications which have become a unique marketplace specifically for livestock. The business process that is happening right now, that an application provides a place for various pet shops to pour their sales business activities in accordance with the dimensions of the animals they sell, on the other hand also receives intensive care services for animal development for farmers. It takes a long time for a common marketplace application to get a service maintenance partner, and time brackets along with maintenance service wages that are proportional to the value of feed prices, an increase in the amount of food, and season conditions for a sales activity there is no precise analysis. Based on the needs of this matter, a design of a new market place application design is needed which is equivalent to a market place in general, which only has the ability to sell and purchase. In the analysis phase of modeling using Business Process Modeling Notation (BPMN), while the design stage uses Unified Modeling Language (UML). The design of this application will be a guideline in implementing software in future research.

In the era of industry 4.0, digitalization is a very significant step to adopt in a company. Every worldly renowned industry, oil and gas included, needs to assimilate this term into its business process. Reserves and resources report depicts an oil and gas company future cash flow, wealth, performance, as well as growth. Therefore, creating and managing this report need meticulous attention. In order to comply with demand in industry 4.0 and simplify reserves and resources reporting process, reserves and resources database and web-based application need to be developed. First task to carry in establishing database is to create and input master data. Companies’ asset is classified into four common entities: asset, area, structure, and layer – as the smallest entity. Layer contains fluid type and oil and gas specific attributes. After master data is established, a web-based application to handle data transaction and reporting is developed. In order to maintain data security, access to this application is restricted into four roles: data entry user, data approval user, administrator, and management. Every role has its own privilege, for example data entry user can create, edit, and view data, while management can only view it. Other employees that need to access this application are based on management approval and restricted into view privilege under their asset location. This application has already been tested in two reserves and resources reporting window, and underwent bug-fixing and improvement process. Implementing this application in oil and gas company’s business process gives several benefits: minimizing human error, establishing a single data source, and cutting time consumption in creating reserves and resources report. This application is the solution in creating and managing the report, as well as displaying data in graphical view to help management makes corporate decision.

Background: Manufacturing companies nowadays have to cope with ever-increasing speed and complexity to manage their global supply chain. Information flow manage the supply chain needs to be more accurate and real-time than ever before. Item master data management is no exception as well. This research demonstrates the potential benefits of applying robotic process automation (RPA) technology in master data management based on two companies in the manufacturing industry. Methods: The method approached by the research was a qualitative method, utilizing interpretation of data extracted from literature and semi-constructed interviews. Results: The article proposes a framework for RPA implementation in the master data managing process. Automation with software robots can greatly benefit the organization, namely: lower processing time, reduce human errors, lower operations cost, improved compliance level and higher data accuracy. Conclusions: With the objective to examine the benefits of RPA in master data management, the researchers have investigated 2 companies in the manufacturing industry to understand how they have benefited from RPA for item master data management processes. The result showed that RPA is affirmed to bring about many benefits for the organizations through structured automation. The researchers have proposed a framework for implementing RPA to capture item master data based on the change management model and the framework is separated in 3 phases involving important tasks in each phase. Future researches might use this study as a stepping stone for further studies in cognitive RPA, utilizing cognitive technology in combination with RPA technology with the mean to achieve a higher level of automation.

Productivity in the construction industry (both houses and infrastructure) has not been improving as expected, while other industries have been able to improve their productivity significantly. The appropriate use of building information modelling (BIM) technologies brings several benefits and advantages to construction projects. The main challenges of project efficiency emerge in the form of numerous requests for information during the construction project, which are considered to be waste in the processes. This highlights the need for a practical process model to plan the information flow for BIM-based projects. The main aim of this study is to propose a model to plan the flow of project information among primary stakeholders especially in infrastructure projects. Our main findings are firstly, the foundation for data management starts from defining unified one data for the product and the for the process. Unified data means one single repository of data – all stakeholders use the same unified data. It is also essential that data responsibilities and ownership are defined. Secondly, we found that the biggest challenges are that the data needs are not planned beforehand, resistance to change, difficulty receiving existing data and data must be modified before use. As a whole, it seems sometimes that the technology on data transfer is more important that what has been transferred and why. Finally our construction, the life cycle model for data flow originates from one data to all stakeholders, single data repository must be updated along the life- cycle of the object covering also the operations and maintenance, where the data has to be updated through the whole life-cycle. This new approach is intended to enable the early involvement of maintenance stakeholders in designing product data for a project lifecycle perspective. The model helps to change the current information flow and gain the benefits that a BIM-based process can offer. This study is based on case studies and is qualitative in nature and naturally needs more validation.

Dissertação de mestrado integrado em Engenharia e Gestão Industrial, A presente dissertação foi desenvolvida no âmbito do 5º ano do Mestrado Integrado em Engenharia e Gestão Industrial do Departamento de Produção de Sistemas da Universidade do Minho, na empresa Browning Viana. No contexto atual de mercado e concorrência globalizada, a sobrevivência das empresas depende da adoção de medidas que lhes permitam aumentar a sua eficiência, e destacar-se da concorrência através da diferenciação dos seus produtos. Portanto, neste trabalho propôs-se a criação de procedimentos para modelar os processos, bem como a implementação de novas medidas. De forma a ser possível automatizar determinados processos relacionados com a gestão de informação do Manufacturing Execution System (MES) da empresa, que ainda se encontrava numa fase inicial de implementação, inferior a um ano. O objetivo principal foca-se em obter uma Master Data de qualidade, porque será através dessa informação que o sistema irá trabalhar. Ou seja, um erro na Master Data poderá ter várias implicações, por exemplo, futuramente, se um colaborador tomar decisões com base num relatório do MES, que é baseado em dados incorretos ou de baixa qualidade, isso irá implicar tomadas de decisão erradas. Face a isto, foi analisada a situação atual da gestão de informação centrando-se na criação de artigos e listas de materiais. Com a informação recolhida foram analisados os problemas detetados e como deveriam ser solucionados. Numa última fase deste projeto foram desenvolvidos e testados dois ficheiros de forma a automatizar a criação de artigos e integrar a informação do MES com o Enterprise Resource Planning. Com base nas propostas de melhoria e implementações, conseguiu-se reduzir o tempo de criação dos artigos, sendo a mais significativa no caso das sub-peças de 77%, bem como eliminar problemas por falta de integração. Os resultados foram utilizados para a conclusão do objetivo principal, ou seja, mudar a tendência negativa de uma má qualidade da Master Data., The present Master's thesis was developed in the 5th year of the Integrated Master in Industrial Engineering and Management of the Systems Production Department of Minho University, in the company’s Browning Viana. In the current context of globalised market and competition, the survival of companies depends on the adoption of measures that allow them to increase their efficiency and to stand out from the competition through the differentiation of their products. In this work, the main purpose was creating procedures and implement measures in order to automate certain processes related to the information management of the company's Manufacturing Execution System (MES), which is in an initial implementation phase, during almost a year. The main purpose of this project includes a quality Master Data because it is through this information that the system will work and an error in the Master Data would has several implications. In the future, if a company employee takes decisions based on a report, which is based on incorrect or low quality data due to Master Data errors this would certainly imply wrong decisions. At this point of view, the current situation of information management was analysed focusing on the creation of articles and material lists. With the information collected, the problems detected were analysed and how they should be solved. In a last stage of this project two files were developed in order to automate the creation of articles and the integration of MES with ERP and they were tested. Meetings were also held for actions that are needed at other Departments to be able to increase the quality of the MES information. Based on the improvement proposals and implementations, it was possible to reduce the time to create the articles, being the most significant in the case of the subparts of 77%, as well as eliminating them due to lack of integration. The results were used for the conclusion of the main objective, that is, to change a negative trend of a bad quality of the Master Data.

Master data management programs are large by nature since the aim is to provide the entire enterprise with a shared trusted view of the organisation’s most critical data assets. In this paper, we present what dimensions and activities a master data management program in a large organisation should consider and how to monitor such a program once it is up and running. Our findings result from an autoethnography study where personal experiences are connected to previous research. A heatmap approach is used to visualize the inherent complexity of a master data management program. Our approach is derived from participating in four different master data management programs in four different global organisations during 2007-2020.

Der Begriff der Nachhaltigkeit hat in den letzten Jahren an Stellenwert gewonnen, so gilt nachhaltiges Handeln als unabdingbar für einen ressourcenschonenden Lebensstil und gilt gerade in Verbindung mit der Digitalisierung durchaus als Megatrend. Um diesen Entwicklungen gerecht zu werden, setzen viele Unternehmen auf Produktlabels, die Konsumentinnen und Konsumenten die gewünschten Werte vermitteln sollen. Die Firma GS1 Austria beschäftigt sich mit Standards zur Unterstützung der Wertschöpfungskette. Teil des Angebots ist ein Lebensmittelstammdatenpool, welcher auf einem internationalen Datenmodell, dem Standard des sogenannten Global Data Synchronisation Network (GDSN), basiert. Dieser dient dem Austausch und der Beschreibung von Gütern aller Arten. Inhalte der Etiketten von Produkten des täglichen Bedarfs werden in einer Datenbank (GS1 Sync) gesammelt und stehen in digitaler Form zur Verfügung, um Online-Shops und Inhouse-Systeme des Handels mit diesen Inhalten zu versorgen. Dieser internationale Standard enthält unter anderem eine Vielzahl an möglichen Labelangaben. Ziel der vorliegenden Arbeit ist es, mithilfe der Dokumentation des GS1 Sync Systems einen Überblick über die im GS1 System gesammelten Labels zu verschaffen, bei dem ein besonderes Augenmerk auf Labels mit verpackungsbezogenen Inhalten liegen soll. Zusätzlich soll aus den gewonnenen Erkenntnissen ein Vorschlag zur besseren Abbildung von Labels im GS1 System geschaffen werden. Die Analyse der 716 untersuchten und zur Auswahl stehenden Labels im GS1 System hat ergeben, dass diese sich hauptsächlich mit den Bereichen Lebensmittel, Landwirtschaft und Weinbau beschäftigen. Vergebende Organisationen befinden sich mehrheitlich in westlichen Ländern, allen voran die USA gefolgt von Deutschland und Kanada. 20 Labels beschäftigen sich explizit mit verpackungsrelevanten Inhalten. Ein Abgleich mit den Dateninhalten der GS1 Sync Datenbank für den österreichischen Zielmarkt hat ergeben, dass 179 der 716 Labels von Anwenderinnen und Anwendern aktiv verwendet werden. Aufgrund der analysierten Daten wurde eine überarbeitete Liste inklusive Reihung erstellt, welche Anwenderinnen und Anwender von GS1 Sync die Angabe von Labels in Zukunft erleichtern und somit zu einer höheren Befüllungsrate von Labelangaben führen soll. The concept of sustainability has gained in importance in recent years; sustainable action is considered indispensable for a resource-conserving lifestyle and is definitely considered a megatrend, especially in connection with digitalization. In order to fulfil these developments, many companies rely on product labels that are intended to convey the desired values to consumers. The company GS1 Austria deals with standards to support the value chain. Part of the offer is a food master data pool, which is based on an international data model, the so-called Global Data Synchronisation Network (GDSN) standard. This serves the exchange and description of goods of all kinds. Contents of the labels of everyday products are collected in a database (GS1 Sync) and are available in digital form to supply online stores and in-house systems of retailers with these contents. Among other things, this international standard contains a large number of possible marked labels. The aim of the present work is to provide an overview of the labels collected in the GS1 system with the help of the documentation of the GS1 Sync system, with a special focus on labels with packaging-related content. In addition, a proposal for better mapping of labels in the GS1 system is to be created from the findings obtained. The analysis of the 716 labels examined and available for selection in the GS1 system has shown that these are mainly concerned with the areas of food, agriculture and viticulture. The majority of awarding organizations are located in Western countries, first and foremost the USA, followed by Germany and Canada. 20 labels explicitly deal with packaging-related content. A comparison with the data content of the GS1 Sync database for the Austrian target market showed that 179 of the 716 labels are actively applied by users. Based on the analyzed data, a revised list including ranking was created, which should make it easier for GS1 Sync users to specify labels in the future and thus lead to a higher filling rate of label specifications.

In automotive industries, pricing anomalies may occur for components of different products, despite their similar physical characteristics, which raises the total production cost of the company. However, detecting such discrepancies is often neglected since it is necessary to find the problems considering the observation of thousands of pieces, which often present inconsistencies when specified by the product engineering team. In this investigation, we propose a solution for a real case study. We use as strategy a set of clustering algorithms to group components by similarity: K-Means, K-Medoids, Fuzzy C-Means (FCM), Hierarchical, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Self-Organizing Maps (SOM), Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Differential Evolution (DE). We observed that the methods could automatically perform the grouping of parts considering physical characteristics present in the material master data, allowing anomaly detection and identification, which can consequently lead to cost reduction. The computational results indicate that the Hierarchical approach presented the best performance on 1 of 6 evaluation metrics and was the second place on four others indexes, considering the Borda count method. The K-Medoids win for most metrics, but it was the second best positioned due to its bad performance regarding SI-index. By the end, this proposal allowed identify mistakes in the specification and pricing of some items in the company.

Master data management (MDM) is a method of maintaining, integrating, and harmonizing master data to ensure consistent system information. The primary function of MDM is to control master data to keep it consistent, accurate, current, relevant, and contextual to meet different business needs across applications and divisions. MDM also affects data governance, which is related to establishing organizational actors’ roles, functions, and responsibilities in maintaining data quality. Poor management of master data can lead to inaccurate and incomplete data, leading to lousy stakeholder decision-making. This article is a literature review that aims to determine how MDM improves the data quality and data governance and assess the success of MDM implementation. The review results show that MDM can overcome data quality problems through the MDM process caused by data originating from various scattered sources. MDM encourages organizations to improve data management by adjusting the roles and responsibilities of business actors and information technology (IT) staff documented through data governance. Assessment of the success of MDM implementation can be carried out by organizations to improve data quality and data governance by following the existing framework.

The authors discuss the use of files being accumulated by library www-serves (log-files) for calculating altmetrics. The log-files comprise information on all queries therefore they can be used for calculating statistical indicators of online user activity index in compliance with the federal standard GOST 7.0.20-2014. The authors also analyze the provisions of the standard as referred to online user services control. The COUNTER format is the international format assigning the list and form for presenting statistical data on using digital resources. The current version 5, the COUNTER Code and the algorithm of master data (log-files) processing are discussed. The authors conclude that Russian libraries have not introduced the unified method for counting the requests to their digital resources so far. Meaningful combination of GOST requirements, COUNTER fundamental indicators and calculation of indicators obtained through log-files analysis enable to analyze the relevance of library digital resources to various user categories.

The objective of this study is to analyze the potential of company data assets for data-driven, fact-based decision-making in product portfolio management (PPM). Data assets are categorized from th...

The airport is one of the entry gates of a country, in the airport there are many work divisions that support and facilitate all existing activities, one of which is a cleaning service that has a large enough function that is to improve cleanliness and comfort in the airport area, cleaning services that exist when This is managed by the company and works with companies that focus on cleaning service in each terminal. The placement of the cleaning service area is still manual and takes a lot of time and involves several parts in the process, and inhibits in terms of time in the process of cleaning the area at the airport so that it can reduce the quality of services that have an inconvenience, to overcome the problem. which is currently running to find out the components of the problem that exist. The results to be achieved in this study is the application of a system that facilitates the process, namely by making an information system placement of web-based cleaning service work areas that is used as a reference in the system development process later. The analytical method used in this study uses the PIECES method, to assist in the process of analyzing the system that has been running. The Programming Language used in building this system uses PHP, MySQL as a database to store master data, transactions and users.

Inventory information system is a system to determine stock inventory in the warehouse of a company. Inventory information system has been widely used or developed in a company with a wide range of technologies and systems. Problems at UD. Miasa is not the availability of an information system for controlling inventory of stock items available in the warehouse. a system of inventory information would be very helpful UD. Miasa in running the business. Therefore, in this study will be to design and build an information system that supplies desktop based on inventory information in clear and detailed. The system built can also perform archiving of data such as data items item master data, supplier master data, master customer data, incoming goods, goods out, inventory taking, as well as forecasting for the purchase of goods in the next month. The end result of this research is the creation of an information system invetory built using Visual Studio 2010 application and uses the MySQL database system.

Regional Water Company (PDAM) Gianyar Regency is one of the regionally owned companies in Gianyar Regency. Gianyar PDAM is responsible for the availability of clean water for consumers in the Gianyar region and its surroundings. In a water distribution system, the PDAM monitors water pressure in the pipeline so that water is guaranteed to flow to the customer. During this time the system of recording water pressure on the manometer installed in each particular zone is done manually using report paper. The difficulty caused is the slow monitoring of water pressure reported by the recording officer to the distribution officer, so that the water distribution process becomes stagnant which ultimately harms the customers and the PDAM itself. This study aims to create a system that can record water pressure which makes it easier for the distribution head to get information quickly. With the research phase which includes data collection techniques, system analysis, and system design to maximize research and implement systems and tests on each system, it can be concluded that the system that has been made can run well and as expected. The functional features generated in this study are the dashboard graph of the average water pressure per month, processing master employee data, processing village master data, processing master manometer data, processing schedule data, manometer monitoring by officers, manometer monitoring by admin and manometer monitoring report .

Master Data Management (MDM) is an approach for effective management of shared master data across organizations. In the public sector, MDM initiatives have been developed; however, the adoption among local government remains slow and there has been little interest in MDM adoption in extant research. Building on a Technology-Organization-Environment (TOE) framework, a conceptual model which highlights a set of potential determinants affecting the adoption of MDM by local government was developed. To validate the model, data were collected via survey from 224 responses from Malaysian local government department units. Using SEM-PLS, the study confirmed that data quality and data governance are two determinants of MDM adoption specific to the context of Malaysian local government, and four other determinants – complexity, top management support, technological competence, and citizen demand – are found to have significant effects on MDM adoption by local government. Surprisingly, three determinants – relative advantage, data security, and government policy – are found to have non-significant relationships to the adoption of MDM by local government. In addition, top management support is revealed to be a cornerstone of MDM technological competence in local government. The study contributes to the theoretical, contextual, and practical knowledge of MDM and IT adoption in the context of local government.

The use of information and communication technologies facilitates energy management (EM) at both district and building levels, but also generates a considerable amount of data. To gain insights into such data, it is essential to resolve the cross-domain data interoperability problem and determine an approach to exchange performance information and insightful data among various stakeholders. This paper developed an EM-KPI (key performance indicator) ontology to exchange key performance information and data for districts and buildings. The ontology contains two components: namely KPIs and EM master data; these, respectively, represent the multi-level performance information for energy performance tracking and the key data for data exploitation. Through a demonstration, a sample linked dataset generated using the data correlation predefined in the ontology is presented. The linked data analysis proves the feasibility of the ontology for exchanging data among different stakeholders and for exploring insights in relation to performance improvement. European Commission - Seventh Framework Programme (FP7) China Scholarship Council Guangzhou Science and Technology Innovation Talent Project UCD Energy Institute 24 month embargo - AC

Industrial enterprises rely on prediction of market behavior, monitoring of performance measures, evaluation of production processes and other data analyses to support strategic and operational decisions. However, although an adequate data quality (DQ) is essential for any data analysis and several methodologies for DQ assessment exist, not all organizations consider DQ in decision-making processes. E.g., inaccurate and delayed data acquisition leads to imprecise master data and poor knowledge of machine utilization. While these aspects should influence production planning and control, current approaches to data evaluation are too complex to use them on a-day-to-day basis. In this paper, we propose a methodology that simplifies the execution of DQ evaluations and improves the understandability of its results. One of its main concerns is to make DQ assessment usable to small and medium-sized enterprises (SME). The approach takes selected, context related structured or semi-structured data as input and uses a set of generic test criteria applicable to different tasks and domains. It combines data and domain driven aspects and can be partly executed automated and without context specific domain knowledge. The results of the assessment can be summarized into quality dimensions and used for benchmarking. The methodology is validated using data from the enterprise resource planning (ERP) and manufacturing execution system (MES) of a sheet metal manufacturer covering a year of time. The particular application aims at calculating logistic key performance indicators. Based on these conditions, data requirements are defined and the available data is evaluated considering domain specific characteristics.

Jiaji Logistics is one of the biggest logistics enterprises in our country, but the survey found that there are still many problems in it, which limits the development of Jiaji logistics. One of the important factors is the location of the distribution center. In order to overcome this difficulty, the location of Jiaji logistics is used scientifically, and it can also help the development of logistics industry in China. First of all, in this paper, by analyzing distribution center location of the relevant literature both at home and abroad, according to oneself the circumstance of master data, choose the Baumov Model for the theme as a solution. Then, the factors affecting the distribution center of Jiaji logistics are selected, and the optimal solution is obtained by the successive approximation method. The final result will be the distribution center capacity, location, volume allocation and so on. The improved model of the Baumov Model was a great help to the location of the Jiaji logistics, which reduced the cost of the Jiaji logistics.

Relying on the Biomedical Big Data Center of West China Hospital, this paper makes an in-depth research on the construction method and application of breast cancer-specific database system based on full data lifecycle, including the establishment of data standards, data fusion and governance, multi-modal knowledge graph, data security sharing and value application of breast cancer-specific database. The research was developed by establishing the breast cancer master data and metadata standards, then collecting, mapping and governing the structured and unstructured clinical data, and parsing and processing the electronic medical records with NLP natural language processing method or other applicable methods, as well as constructing the breast cancer-specific database system to support the application of data in clinical practices, scientific research, and teaching in hospitals, giving full play to the value of medical big data of the Biomedical Big Data Center of West China Hospital.