Open Data Model Research Articles

An Inspection of IFC Models from Practice

Industry Foundation Classes (IFC) is a complete, wide and complex open standard data model to represent Building Information Models. Big efforts are being made by the standardization organization buildingSMART, to develop and maintain this standard in collaboration with researchers, companies and institutions. However, when trying to use IFC models from practice for automatic analysis, some issues emerge, as a consequence of a misalignment between what is prescribed by, or available in, the standard with the data sets that are produced in practice. In this study, a sample of models produced by practitioners for aims different from their explicit use within automatic processing tools is inspected and analyzed. The aim is to find common patterns in data set from practice and their possible discrepancies with the standard, in order to find ways to address such discrepancies in a next step. In particular, it is noticeable that the overall quality of the models requires specific additional care by the modellers before relying on them for automatic analysis, and a high level of variability is present concerning the storage of some relevant information (such as georeferencing).

Расчет гравитационных поправок с использованием данных воздушного лазерного сканирования

Calculation of corrections to gravity measurements is one of the most important stages that determine the whole quality of research. Wrong corrections can lead to incorrect interpretation of the obtained measurements and lead to their false interpretation. To achieve highly accurate results, it is necessary to take into account not only the height, but also the entire array of information about the relief. In this case, level of detail of relief model becomes critically important, especially in case of working with rugged terrain with large number of vertically developed rock formations (outliers, rock faults, steep slopes). Now the methods normally used are based on the use of previously created materials from cartographic archives (topographic maps at a scale of 1:100,000–1:25,000). It is also possible to use open (free) terrain models. These materials have a number of drawbacks, for example, low detail of the microrelief and steep inclined surfaces (slopes, walls, faults, incisions) that have a significant effect on the values measured by gravimeters located at a small distance from such forms. The available methods do not assume ability to work with dense terrain models. These shortcomings lead to wrong corrections during gravimetric measurements. however, using of modern remote sensing methods makes possible to obtain a high-precision terrain models easily. The best opportunities are provided by lIDAR technology. here we describe differences between using lIDAR data and other types of data (1:25,000 maps, open data models), and make comparison between corrections, calculated using different data sources.

A New Model for Manuscript Provenance Research: The Mapping Manuscript Migrations Project

Since it was awarded a Round 4 Trans-Atlantic Platform Digging into Data Challenge grant in 2017, the Mapping Manuscript Migrations project has been working to develop and test a methodology to link disparate datasets from Europe and North America with the aim of providing large-scale analysis and visualizations of the history and provenance of medieval and Renaissance manuscripts. Guided by a set of research questions identified at the outset of the project, MMM developed an innovative Linked Open Data model and dataset which unifies three separate manuscript-related databases in a semantically consistent way, together with the workflows for transforming the institutional data contributions into the common structure. The dataset has been made available through a Linked Open Data service hosted by the Linked Data Finland platform and the MMM semantic portal. The aggregated data can be queried and visualized at scales ranging from a single manuscript to a total of more than 216,000 manuscripts as a group. Visualization tools developed in the portal show how the manuscripts have traveled across time and space from their place of production to their current locations, where they continue to find new audiences. The following report summarizes our methodology and results, and lays the groundwork for further research using our processes.

AUTOMATIC CONVERSION OF CITYGML TO IFC

Abstract. The trend of increased usage of both BIM and 3D GIS and the similarity between the two has led to an increase in the overlap between them. A key application of such overlap is providing geospatial context data for BIM models through importing 3D GIS-data to BIM software to help in different design-related issues. However, this is currently difficult because of the lack of support in BIM software for the formats and data models of 3D Geo-information. This paper deals with this issue by developing and implementing a methodology to convert the common open 3D city model data model into the most common open BIM data format, namely CityGML (Gröger et al., 2012) to IFC (buildingsmart, 2019b). For the aim of this study, the two standards are divided into 5 comparable subparts: Semantics, Geometry, Geographical coordinates, Topology, and Encoding. The characteristics of each of these subparts are studied and a conversion method is proposed for each of them from the former standard to the latter. This is done by performing a semantic and geometrical mapping between the two standards, converting the georeferencing from global to local, converting the encoding that the two standards use from XML to STEP, and deciding which topological relations are to be retained. A prototype implementation has been created using Python to combine the above tasks. The work presented in this paper can provide a foundation for future work in converting CityGML to IFC. It provides an insight into the relationship between the two standards and a methodology for the conversion from one to the other, and the process of developing software to perform such conversion. This is done in a way that can be extended for future specific needs.

Applying BIM to support dispute avoidance in managing multi-owned buildings

Abstract With the growth of high-density living, disputes experienced by residents in multi-owned buildings (MOBs) have become an ongoing challenge in urban areas. A significant number of the disputations have found their root cause in the issues concerning improper use and management of MOBs by residents. It stems from their inaccurate understanding of ownership rights that are inherently 3D but using 2D cadastral survey plans, authoritative documents of ownership. This research explores the ability of building information modeling (BIM) to address required information for improving the perception of ownership rights that affect resident behaviors in managing MOBs. An open data model of BIM is extended to accommodate the necessary information for preventing resident misbehaviors that led to dispute cases in Victoria state, Australia. In this study, we implement BIM data of an MOB where a real dispute happened to demonstrate the validity of the enriched data model on the information delivery and an enhanced understanding of ownership rights. It is confirmed that the use of BIM facilitates the alleviation of the misbehaviors by informing residents with accurate communication of ownership rights and could support the avoidance of disputes in MOBs.

The multi-energy system co-planning of nearly zero-energy districts – Status-quo and future research potential

The deep-decarbonization of local energy systems is vital to achieving our climate protection obligations. To that effect, the existence of energy modeling and simulation tools that provide accurate planning insights is imperative.The coupling of multiple energy vectors increase the flexibility of the local energy system and increase the renewable energy hosting capacity. The added-benefits of multi-energy systems comprise the reliability of energy supply, improve the socio-economic value proposition of decentralized and renewable technologies, and reduce the environmental impacts of energy use. The simultaneous consideration of the expansion planning requirements and the operational details of the energy system becomes mandatory when the variable renewable energy generation significantly increases.This review focuses on the multi-energy system co-planning in nearly zero-energy districts. We discuss how the temporal representation of multi-energy system co-planning models influence the optimal sizing and scheduling of resources. We also look at the existing methods of representing distributed generators and energy network and their limitations. Thirdly, we discuss the significance of spatial resolution and how open data models, such as CityGML, can enable more comprehensive multi-energy scenario modeling.Above all, we highlight the limitations of the existing models to adequately represent and evaluate the added-value streams associated with multi-energy systems in a nearly zero-energy district. The review examines several research gaps, such as investigating the influence of temporal resolution in multi-energy system models, integration of spatial and topological details of districts, detailed distributed-technology models, accurate network models, and integrating the transportation sector.

BIM data model requirements for asset monitoring and the circular economy

Purpose The purpose of this paper is to review and provide recommendations to extend the current open standard data models for describing monitoring systems and circular economy precepts for built assets. Open standard data models enable robust and efficient data exchange which underpins the successful implementation of a circular economy. One of the largest opportunities to reduce the total life cycle cost of a built asset is to use the building information modelling (BIM) approach during the operational phase because it represents the largest share of the entire cost. BIM models that represent the actual conditions and performance of the constructed assets can boost the benefits of the installed monitoring systems and reduce maintenance and operational costs. Design/methodology/approach This paper presents a horizontal investigation of current BIM data models and their use for describing circular economy principles and performance monitoring of built assets. Based on the investigation, an extension to the industry foundation classes (IFC) specification, recommendations and guidelines are presented which enable to describe circular economy principles and asset monitoring using IFC. Findings Current open BIM data models are not sufficiently mature yet. This limits the interoperability of the BIM approach and the implementation of circular economy principles. An overarching approach to extend the current standards is necessary, which considers aspects related to not only modelling the monitoring system but also data management and analysis. Originality/value To the authors’ best knowledge, this is the first study that identifies requirements for data model standards in the context current linear economic model of making, using and disposing is growing unsustainably far beyond the finite limits of planet of a circular economy. The results of this study set the basis for the extension of current standards required to apply the circular economy precepts.

Towards a SpatioTemporal Data Model for Traditional Ecological Knowledge/Indigenous Knowledge

Indigenous peoples have been making maps and utilizing GIS for some time, and have been mapped and cadastralized for some time as well. Models of Indigenous spatiality have been the topic of some work, but the data for modelling Indigenous spatiotemporality remain scant, and the subject matter is rich. This paper suggests another layer of representation for GIS when dealing with complex data with a strong relational and qualitative component. In this paper, we present a new data model that we are calling the spatiotemporal motif. It is an open data model incorporating choric (coordinate) as well as topic (attribute) space and chronic (coordinate) as well as kairic (attribute) time. The model aims to fill gaps in other data model depictions concerning lack of support for cyclical time, multiple constraints on what constitutes a proper time or place for a given activity, fluid and dynamic spatiotemporal boundaries, support for narratives and contingencies, and privacy and sensitivity concerns.

Resolving data sparsity and cold start problem in collaborative filtering recommender system using Linked Open Data

The web contains a huge volume of data, and it's populating every moment to the point that human beings cannot deal with the vast amount of data manually or via traditional tools. Hence an advanced tool is required to filter such massive data and mine the valuable information. Recommender systems are among the most excellent tools for such a purpose in which collaborative filtering is widely used. Collaborative filtering (CF) has been extensively utilized to offer personalized recommendations in electronic business and social network websites. In that, matrix factorization is an efficient technique; however, it depends on past transactions of the users. Hence, there will be a data sparsity problem. Another issue with the collaborative filtering method is the cold start issue, which is due to the deficient information about new entities. A novel method is proposed to overcome the data sparsity and the cold start problem in CF. For cold start issue, Recommender System with Linked Open Data (RS-LOD) model is designed and for data sparsity problem, Matrix Factorization model with Linked Open Data is developed (MF-LOD). A LOD knowledge base “DBpedia” is used to find enough information about new entities for a cold start issue, and an improvement is made on the matrix factorization model to handle data sparsity. Experiments were done on Netflix and MovieLens datasets show that our proposed techniques are superior to other existing methods, which mean recommendation accuracy is improved.

Using knowledge management to improve inter-institutional collaboration in crisis events

The aim of the study is to propose policy guidelines that can help to improve the likelihood of success in crisis events, highlighting the need of better knowledge management to improve crisis management. After a brief analysis of three crisis events occurred in the USA, Chile and Peru, the study deepens in the situation that was lived in the Peru's earthquake. Furthermore, an innovative model of inter-institutional collaboration based on the concept of open data as a tool for knowledge management is proposed, obtaining information from the problems encountered in situations of crisis that occurred previously. Three groups of stakeholders (academics, public servants and citizens) validated the proposed policy guidelines and the open data model. Finally, this study can serve as a starting point for the development of an open data platform that helps society to face crisis events through knowledge management, promoting transparency, participation and collaboration among stakeholders.

Using knowledge management to improve inter-institutional collaboration in crisis events

The aim of the study is to propose policy guidelines that can help to improve the likelihood of success in crisis events, highlighting the need of better knowledge management to improve crisis management. After a brief analysis of three crisis events occurred in the USA, Chile and Peru, the study deepens in the situation that was lived in the Peru's earthquake. Furthermore, an innovative model of inter-institutional collaboration based on the concept of open data as a tool for knowledge management is proposed, obtaining information from the problems encountered in situations of crisis that occurred previously. Three groups of stakeholders (academics, public servants and citizens) validated the proposed policy guidelines and the open data model. Finally, this study can serve as a starting point for the development of an open data platform that helps society to face crisis events through knowledge management, promoting transparency, participation and collaboration among stakeholders.

Developing the Quality Model for Collaborative Open Data

Abstract Nowadays, the development of data sharing technologies allows to involve more people to collaboratively contribute knowledge on the Web. The shared knowledge is usually represented as Collaborative Open Data (COD), for example, Wikipedia is one of the well-known sources for COD. The Wikipedia articles can be written in different languages, updated in real time, and originated from a vast variety of editors. However, COD also bring different data quality problems such as data inconsistency and low data objectiveness due to the crowd-based and dynamic nature. These data quality problems such as biased information may lead to sentimental changes or social impacts. This paper therefore proposes a new measurement model to assess the quality of COD. In order to evaluate the proposed model, A preliminary experiment is conducted with a large scale of Wikipedia articles to validate the applicability and efficiency of this proposed quality model in the real-world scenario.

Open interactive education algorithm based on cloud computing and big data

In order to improve the self-learning ability of cloud computing and scheduling ability of big data resources in open interactive education, an open interactive education algorithm based on cloud computing and big data is proposed. An information flow model for open education big data is constructed, and big data mining is conducted to an open interactive education platform through the association rules mining method based on parallel scheduling to extract semantic ontology information feature quantity of interactive education; spatial attribute clustering is performed in the cloud computing environment according to the feature extraction results, and big data information is scheduled through the multi-feature weight allocation method. Simulation results show that in open interactive education, this method can cause relatively good output performance of big data mining, relatively high accuracy of feature information clustering of open interactive education and relatively strong feature resolution and recognition ability of data output, which meets the educational resource scheduling and allocation requirements of open education.

Open interactive education algorithm based on cloud computing and big data

In order to improve the self-learning ability of cloud computing and scheduling ability of big data resources in open interactive education, an open interactive education algorithm based on cloud computing and big data is proposed. An information flow model for open education big data is constructed, and big data mining is conducted to an open interactive education platform through the association rules mining method based on parallel scheduling to extract semantic ontology information feature quantity of interactive education; spatial attribute clustering is performed in the cloud computing environment according to the feature extraction results, and big data information is scheduled through the multi-feature weight allocation method. Simulation results show that in open interactive education, this method can cause relatively good output performance of big data mining, relatively high accuracy of feature information clustering of open interactive education and relatively strong feature resolution and recognition ability of data output, which meets the educational resource scheduling and allocation requirements of open education.

Development of a CityGML Application Domain Extension for Simulating the Building Construction Process

Virtual 3D city models can be stored and exchanged in the CityGML open data model. When dynamic phenomena in 3D cities are represented with a CityGML application domain extension (ADE), the objects in CityGML are often used as static background, and it is difficult to represent the evolutionary process of the objects themselves. Although a construction process model in building information modeling (BIM) is available, it cannot efficiently and accurately simulate the building construction process at the city level. Accordingly, employing the arrow diagramming method, we developed a CityGML ADE to represent this process. We extended the hierarchy of the model and proposed the process levels of detail model. Subsequently, we explored a mechanism to associate the construction process and building objects as well as the mechanism to automate construction process transitions. Experiments indicated that the building construction process ADE (BCPADE) could adequately express the characteristics of this process. Compared with the building construction process model in the architecture, engineering, and construction field, BCPADE removes redundant information, i.e., that unrelated to a 3D city. It can adequately express building construction processes at multiple spatiotemporal scales and accurately convey building object behavior during building evolution, such as adding, removal, merging, and change. Such characteristics enable BCPADE to render efficient and accurate simulations of the building construction process at the city level.

Virtualization of disaggregated optical networks with open data models in support of network slicing

Network slicing has been a major selling point of 5G networks, where a slice is roughly defined as a self-contained logical network on top of a shared infrastructure tailored for a specific service or vertical industry, composed of heterogeneous resources (computing, storage, bandwidths) and typically involving specific application and/or networking functions. The relationship between the network slicing and the underlying network virtualization is an open research topic, allowing multiple deployment models. In particular, a specific model of interest involves the virtualization of the optical infrastructure, where optical virtual networks are instantiated in support of network slicing, so the virtual network underlies and provides connectivity to component functions of a network slice. In this paper, we propose and implement a network virtualization architecture for open optical (partially) disaggregated networks, based on the concept of a device hypervisor relying on OpenROADM data models, in support of 5G network slicing over interconnected network function virtualization infrastructure points of presence (NFVI-PoPs). The architecture is experimentally validated, showing the provisioning of ITU-T flexigrid network media channels across a virtualized network.

3D LANDSCAPE OBJECTS FOR BUILDING INFORMATION MODELS (BIM)

Abstract. Building Information Modeling (BIM) is a method for the digital collaborative design, construction and operation of buildings. However, in order to realize a complete view on needed work and expenses of a building, the surrounding landscape elements must be considered as well. Within this paper, the BIM authoring tool Autodesk Revit and the open BIM data model and exchange format Industry Foundation Classes (IFC) has been investigated for its capability to represent landscape elements like a terrain model, retaining walls, and ways. Therefore, a feasibility study has been carried out including the surveying of real-world landscape objects like terrain, buildings, ways and paths, playgrounds, and retaining walls, in order to use actual existing objects instead of idealized, theoretical elements. The aim was to develop and evaluate a workflow from the surveying over the modeling in BIM-able software to the export of an IFC data file. Therefore, the general modeling concepts of BIM and their suitability and limitations for representing landscape elements has been investigated. Experiences made within the project are discussed and first solutions and concepts are recommended. In addition, this paper reports from the buildingSmart International working group “Site, Landscape, and Urban Planning”, their current work and future goals, in order to extend IFC for landscape objects. Additionally, a concept for level of information need referring to landscape elements is shown.

A new model for effective and efficient open government data

Open government data (OGD) is attracting stakeholders from different backgrounds. The call for OGD has been especially pronounced in the last 6 or 7 years. OGD demand accelerated after the launch of the US OGD initiative portal in 2009, followed by the UK in 2010. Before that, the availability and accessibility of government data were limited to certain executives and few government employees, whereas for others, it was either partially available or completely unavailable. Publishing government data, thereby making it available to the public, could be useful in many ways such as increasing transparency and accountability in governments, increasing overall efficiency and performance, encouraging publics’ engagement, and achieving trust and reputation. As an example of the role that OGD may provide, this paper compares the different financial reporting and auditing systems in the public sector between Brazil and Saudi Arabia. Also, the paper examines OGD initiatives among different countries with the focus of the Republic of Brazil and the Kingdom of Saudi Arabia’s open data portals. Moreover, it assesses the level of data transparency based on the definition of the open data model, and more importantly, the paper suggests new dimensions to the open data concept when utilized by governments. In addition, it argues that the OGD in Saudi Arabia, which is an emerging initiative in a country that has centralized power, could be improved dramatically. We demonstrate by using a sample of procurement contracts data taken from the Council of Saudi Chambers Web site, which is publicly available and shows the potential of monitoring or auditing public spending.

Transformation of 3D geospatial data into CityGML – a case of Prague

Abstract The 3D geoinformation is becoming important for cities and their policies. The cities are therefore exploring the possibilities of 3D virtual city models for more efficient decision making. To maximize the economic benefit of such data, the cities can provide their 3D geospatial data for further usage, and so, new applications can be created. The paper defines a way how the freely available 3D geospatial data of Prague can be transformed from the proprietary data format into the open data model. The 3D geospatial data about the buildings, bridges and digital terrain model were transformed from the 3D shapefile into the CityGML. This is an application independent information model and exchange format. This will allow for the wider use of the 3D city model by different groups of users. The generated CityGML files were further imported into the spatial database with appropriate database CityGML-based scheme. It enables more efficient management and querying of CityGML data. To enable the wider audience to explore the 3D city model, the visualization in the web environment was also explored. The paper also presents the way how the attributes from the external data sources can be connected to the 3D objects in the web environment.

The Equity and Inclusion in Higher Education: A Proposed Model for Open Data

Recently, governmental institutions and private industries in power have been pushed to be more transparent so that more people can have ownership of their data. Another type of institution with a large amount of power over data are educational institutions. Colleges and Universities around the globe store a significant amount of data on millions of students, such as financial aid, grades, dropout or graduation, successes after graduation. Each institution is rated with respect to these items and more, and potential students are making decisions to go to the school based on these ratings. Therefore, it is imperative for students, who invest their time and their money into the school of their choice, to know the truth. In 2017, the College Transparency Act and the Student Right to Know Before You Go Act were passed, which were created to push transparency for data in higher education. The openness of data in higher education will be beneficial to prospective students. The push for these two bills coincided with the bitcoin bubble. In the past three years, experts in economics, medicine, and supply chain management have been researching methods on how to implement blockchains to create optimal and decentralized data systems. In this paper, we propose a model for open data in higher education inspired by the Bitcoin, which uses blockchain. When used together with InterPlanetary File System, a peer-to-peer distributed file system, we can create a decentralized platform that increases accessibility of data and autonomy of prospective students.