Data Model Building Research Articles

“Big Data” Analysis: Putting the Data Cart Before the Modelling Horse?

The statistical analysis of very large data sets, so‐called Big Data or Data Analytics, has become enormously popular in Statistical Analysis and Operations Research. In some cases, such as research into the buying habits of online consumers, the results have come quickly and been very significant. Analysis of other data sets, however, is questionable. For example, time‐series based statistical analysis, often under the descriptive envelope of “neural networks” and “data mining,” of stock market and futures prices, sometimes in combination with historical accounting figures such as earnings and cash flows.The appeal is understandable given the availability of share price data and cheap computer processing power. Nevertheless, the notion that historical data form some sort of repeatable pattern over time, and that complex time series or neural network techniques can be then be used to forecast future prices is hard to justify.Economic modeling necessarily needs to factor in human behavior, unlike modeling in the pure sciences. The authors cite Lancaster University Professor Michael Pidd who summarizes six relevant principles: Model simple, think complicated Be parsimonious, start small and add Divide and conquer, avoid mega models Use metaphors, analogies and similarities Do not fall in love with data Model building may feel like muddling through. Economic modeling must recognize three key components: (i) the incorporation of human cognitive understanding and experience of the underlying systems, (ii) the use of data to validate emerging models, and (iii) the role of mathematics to ensure internal coherence and logic. Decision‐makers ought to be very skeptical of models which skimp on any one of these three components. The authors emphasize that, rather than Big Data adding value, per se, people add value by creating models that use it.

HYBRID MODELING BASED ON SCSG-BR AND ORTHOPHOTO

Abstract. With the development of digital city, digital applications are more and more widespread, while the urban buildings are more complex. Therefore, establishing an effective data model is the key to express urban building models accurately. In addition, the combination of 3D building model and remote sensing data become a trend to build digital city there are a large amount of data resulting in data redundancy. In order to solve the limitation of single modelling of constructive solid geometry (CSG), this paper presents a mixed modelling method based on SCSG-BR for urban buildings representation. On one hand, the improved CSG method, which is called as “Spatial CSG (SCSG)” representation method, is used to represent the exterior shape of urban buildings. On the other hand, the boundary representation (BR) method represents the topological relationship between geometric elements of urban building, in which the textures is considered as the attribute data of the wall and the roof of urban building. What's more, the method combined file database and relational database is used to manage the data of three-dimensional building model, which can decrease the complex processes in texture mapping. During the data processing, the least-squares algorithm with constraints is used to orthogonalize the building polygons and adjust the polygons topology to ensure the accuracy of the modelling data. Finally, this paper matches the urban building model with the corresponding orthophoto. This paper selects data of Denver, Colorado, USA to establish urban building realistic model. The results show that the SCSG-BR method can represent the topological relations of building more precisely. The organization and management of urban building model data reduce the redundancy of data and improve modelling speed. The combination of orthophoto and urban building model further strengthens the application in view analysis and spatial query, which enhance the scope of digital city applications.

Understanding Regional Building Characteristics in Yangon Based on Digital Building Model

It is indispensable for a government to assess urban vulnerability to natural disasters such as earthquakes or flood in order to take appropriate disaster measures. However, it is sometimes difficult to obtain necessary dataset for cities or regions, especially for developing countries. The authors have been involved in a SATREPS project named “Development of a Comprehensive Disaster Resilience System and Collaboration Platform in Myanmar,” which aims to make urban vulnerability maps for Yangon City based on several datasets including building inventory of each ward. However, Yangon City has not catalogued enough data for the assessment so far. In this context, in order to understand and to arrange regional building characteristics of the city, this paper explores the possibility of using digital building model (DBM) data obtained from remote sensing imageries for the urban vulnerability assessment. Firstly, a field survey was conducted in Sanchaung Township, and building characteristics such as structural types and the number of stories were analyzed. Therefore, DBM data was prepared for the following comparative analysis. Thirdly, additional field surveys were conducted in Latha and Pabedan Townships, located in the central business districts in the city. Finally, DBM data and the actual building data obtained by the surveys were compared to examine the applicability of DBM for building collapse risk assessment. As a result, it was found that DBM data of 3 m- 7 m represent low-rise buildings, and DBM data of more than 18 m reflect high-rise buildings.

La terminología ATIC como herramienta de soporte a la gestión

This article is intended to continue the one published in the previous journal issue (“ATIC Terminology: Considerations of use in patient care”). Based on the same theoretical-conceptual framework, and in the healthcare setting, the first article was targeted to placing ATIC from the perspective of patient care, and the objective of this second article is to state the considerations and review the evidence for the use of the ATIC terminology as a support tool for the healthcare and administrative management of patient care. To this aim, there has been an adaptation of the mixed, narrative, adjacent method, where the outcomes of study review are presented sequentially, together with their essential considerations. ATIC offers an adequate support for building data models and standards for patient care provision and management. It also guarantees semantic interoperability, by implementing mapping with those of other controlled vocabularies. It offers an adequate conceptual coverage, and minimizes the underuse effect, with a noticeable level of satisfaction by users. At the same time, it suggests new data models, and orientates emerging formulas for measuring the intensity and complexity of patient care. The evidence supporting and demonstrating the use of ATIC as support tool for patient care management seems to support the scenario that ATIC offers a range of new tools, even though the method used in this article leaves conclusions to be drawn by each reader.

The ecological origins of snakes as revealed by skull evolution

The ecological origin of snakes remains amongst the most controversial topics in evolution, with three competing hypotheses: fossorial; marine; or terrestrial. Here we use a geometric morphometric approach integrating ecological, phylogenetic, paleontological, and developmental data for building models of skull shape and size evolution and developmental rate changes in squamates. Our large-scale data reveal that whereas the most recent common ancestor of crown snakes had a small skull with a shape undeniably adapted for fossoriality, all snakes plus their sister group derive from a surface-terrestrial form with non-fossorial behavior, thus redirecting the debate toward an underexplored evolutionary scenario. Our comprehensive heterochrony analyses further indicate that snakes later evolved novel craniofacial specializations through global acceleration of skull development. These results highlight the importance of the interplay between natural selection and developmental processes in snake origin and diversification, leading first to invasion of a new habitat and then to subsequent ecological radiations.

Developing 3D microscopy with CLARITY on human brain tissue: Towards a tool for informing and validating MRI-based histology

Recent breakthroughs in magnetic resonance imaging (MRI) enabled quantitative relaxometry and diffusion-weighted imaging with sub-millimeter resolution. Combined with biophysical models of MR contrast the emerging methods promise in vivo mapping of cyto- and myelo-architectonics, i.e., in vivo histology using MRI (hMRI) in humans. The hMRI methods require histological reference data for model building and validation. This is currently provided by MRI on post mortem human brain tissue in combination with classical histology on sections. However, this well established approach is limited to qualitative 2D information, while a systematic validation of hMRI requires quantitative 3D information on macroscopic voxels.We present a promising histological method based on optical 3D imaging combined with a tissue clearing method, Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging compatible Tissue hYdrogel (CLARITY), adapted for hMRI validation. Adapting CLARITY to the needs of hMRI is challenging due to poor antibody penetration into large sample volumes and high opacity of aged post mortem human brain tissue. In a pilot experiment we achieved transparency of up to 8 mm-thick and immunohistochemical staining of up to 5 mm-thick post mortem brain tissue by a combination of active and passive clearing, prolonged clearing and staining times. We combined 3D optical imaging of the cleared samples with tailored image processing methods. We demonstrated the feasibility for quantification of neuron density, fiber orientation distribution and cell type classification within a volume with size similar to a typical MRI voxel. The presented combination of MRI, 3D optical microscopy and image processing is a promising tool for validation of MRI-based microstructure estimates.

Comparison of Forecasting Energy Consumption in Shandong, China Using the ARIMA Model, GM Model, and ARIMA-GM Model

To scientifically predict the future energy demand of Shandong province, this study chose the past energy demand of Shandong province during 1995–2015 as the research object. Based on building model data sequences, the GM-ARIMA model, the GM (1,1) model, and the ARIMA model were used to predict the energy demand of Shandong province for the 2005–2015 data, the results of which were then compared to the actual result. By analyzing the relative average error, we found that the GM-ARIMA model had a higher accuracy for predicting the future energy demand data. The operation steps of the GM-ARIMA model were as follows: first, preprocessing the date and determining the dimensions of the GM (1,1) model. This was followed by the establishment of the metabolism GM (1,1) model and by calculation of the forecast data. Then, the ARIMA residual error was used to amend and test the model. Finally, the obtained prediction results and errors were analyzed. The prediction results show that the energy demand of Shandong province in 2016–2020 will grow at an average annual rate of 3.9%, and in 2020, the Shandong province energy demand will have increased to about 20% of that in 2015.

Visualizing dependence in high-dimensional data: An application to S&P 500 constituent data

The notion of a zenpath and a zenplot is introduced to search and detect dependence in high-dimensional data for model building and statistical inference. By using any measure of dependence between two random variables (such as correlation, Spearman’s rho, Kendall’s tau, tail dependence etc.), a zenpath can construct paths through pairs of variables in different ways, which can then be laid out and displayed by a zenplot. The approach is illustrated by investigating tail dependence and model fit in constituent data of the S&P 500 during the financial crisis of 2007–2008. The corresponding Global Industry Classification Standard (GICS) sector information is also addressed.Zenpaths and zenplots are useful tools for exploring dependence in high-dimensional data, for example, from the realm of finance, insurance and quantitative risk management. All presented algorithms are implemented using the R package zenplots and all examples and graphics in the paper can be reproduced using the accompanying demo SP500.

Population Pharmacokinetics of Topiramate in Japanese Pediatric and Adult Patients With Epilepsy Using Routinely Monitored Data.

Topiramate is a second-generation antiepileptic drug used as monotherapy and adjunctive therapy in adults and children with partial seizures. A population pharmacokinetic (PPK) analysis was performed to improve the topiramate dosage adjustment for individualized treatment. Patients whose steady-state serum concentration of topiramate was routinely monitored at Kyoto University Hospital from April 2012 to March 2013 were included in the model-building data. A nonlinear mixed effects modeling program was used to evaluate the influence of covariates on topiramate pharmacokinetics. The obtained PPK model was evaluated by internal model validations, including goodness-of-fit plots and prediction-corrected visual predictive checks, and was externally confirmed using the validation data from January 2015 to December 2015. A total of 177 steady-state serum concentrations from 93 patients were used for the model-building analysis. The patients' age ranged from 2 to 68 years, and body weight ranged from 8.6 to 105 kg. The median serum concentration of topiramate was 1.7 mcg/mL, and half of the patients received carbamazepine coadministration. Based on a one-compartment model with first order absorption and elimination, the apparent volume of distribution was 105 L/70 kg, and the apparent clearance was allometrically related to the body weight as 2.25 L·h·70 kg without carbamazepine or phenytoin. Combination treatment with carbamazepine or phenytoin increased the apparent clearance to 3.51 L·h·70 kg. Goodness-of-fit plots, prediction-corrected visual predictive check, and external validation using the validation data from 43 patients confirmed an appropriateness of the final model. Simulations based on the final model showed that dosage adjustments allometrically scaling to body weight can equalize the serum concentrations in children of various ages and adults. The PPK model, using the power scaling of body weight, effectively elucidated the topiramate serum concentration profile ranging from pediatric to adult patients. Dosage adjustments based on body weight and concomitant antiepileptic drug help obtain the dosage of topiramate necessary to reach an effective concentration in each individual.

Towards toxicokinetic modelling of aluminium exposure from adjuvants in medicinal products

As a potentially toxic agent on nervous system and bone, the safety of aluminium exposure from adjuvants in vaccines and subcutaneous immune therapy (SCIT) products has to be continuously re-evaluated, especially regarding concomitant administrations. For this purpose, knowledge on absorption and disposition of aluminium in plasma and tissues is essential. Pharmacokinetic data after vaccination in humans, however, are not available, and for methodological and ethical reasons difficult to obtain. To overcome these limitations, we discuss the possibility of an in vitro-in silico approach combining a toxicokinetic model for aluminium disposition with biorelevant kinetic absorption parameters from adjuvants. We critically review available kinetic aluminium-26 data for model building and, on the basis of a reparameterized toxicokinetic model (Nolte et al., 2001), we identify main modelling gaps. The potential of in vitro dissolution experiments for the prediction of intramuscular absorption kinetics of aluminium after vaccination is explored. It becomes apparent that there is need for detailed in vitro dissolution and in vivo absorption data to establish an in vitro-in vivo correlation (IVIVC) for aluminium adjuvants. We conclude that a combination of new experimental data and further refinement of the Nolte model has the potential to fill a gap in aluminium risk assessment.

DataMock: An Agile Approach for Building Data Models from User Interface Mockups

In modern software development, much time is devoted and much attention is paid to the activity of data modeling and the translation of data models into databases. This has motivated the proposal of different approaches and tools to support this activity, such as semiautomatic approaches that generate data models from requirements artifacts using text analysis and sets of heuristics, among other techniques. However, these approaches still suffer from important limitations, including the lack of support for requirements traceability, the poor support for detecting and solving conflicts in domain-specific requirements, and the considerable effort required for manually checking the generated models. This paper introduces DataMock, an Agile approach that enables the iterative building of data models from requirements specifications, while supporting traceability and allowing inconsistencies detection in data requirements and specifications. The paper also describes how the approach effectively allows improving traceability and reducing errors and effort to build data models in comparison with traditional, state-of-the-art, data modeling approaches.

AN INSPIRE-KONFORM 3D BUILDING MODEL OF BAVARIA USING CADASTRE INFORMATION, LIDAR AND IMAGE MATCHING

The federal governments of Germany endeavour to create a harmonized 3D building data set based on a common application schema (the AdV-CityGML-Profile). The Bavarian Agency for Digitisation, High-Speed Internet and Surveying has launched a statewide 3D Building Model with standardized roof shapes for all 8.1 million buildings in Bavaria. For the acquisition of the 3D Building Model LiDAR-data or data from Image Matching are used as basis in addition with the building ground plans of the official cadastral map. The data management of the 3D Building Model is carried out by a central database with the usage of a nationwide standardized CityGML-Profile of the AdV. The update of the 3D Building Model for new buildings is done by terrestrial building measurements within the maintenance process of the cadaster and from image matching. In a joint research project, the Bavarian State Agency for Surveying and Geoinformation and the TUM, Chair of Geoinformatics, transformed an AdV-CityGML-Profilebased test data set of Bavarian LoD2 building models into an INSPIRE-compliant schema. For the purpose of a transformation of such kind, the AdV provides a data specification, a test plan for 3D Building Models and a mapping table. The research project examined whether the transformation rules defined in the mapping table, were unambiguous and sufficient for implementing a transformation of LoD2 data based on the AdV-CityGML-Profile into the INSPIRE schema. The proof of concept was carried out by transforming production data of the Bavarian 3D Building Model in LoD2 into the INSPIRE BU schema. In order to assure the quality of the data to be transformed, the test specifications according to the test plan for 3D Building Models of the AdV were carried out. The AdV mapping table was checked for completeness and correctness and amendments were made accordingly.

AN INSPIRE-KONFORM 3D BUILDING MODEL OF BAVARIA USING CADASTRE INFORMATION, LIDAR AND IMAGE MATCHING

Abstract. The federal governments of Germany endeavour to create a harmonized 3D building data set based on a common application schema (the AdV-CityGML-Profile). The Bavarian Agency for Digitisation, High-Speed Internet and Surveying has launched a statewide 3D Building Model with standardized roof shapes for all 8.1 million buildings in Bavaria. For the acquisition of the 3D Building Model LiDAR-data or data from Image Matching are used as basis in addition with the building ground plans of the official cadastral map. The data management of the 3D Building Model is carried out by a central database with the usage of a nationwide standardized CityGML-Profile of the AdV. The update of the 3D Building Model for new buildings is done by terrestrial building measurements within the maintenance process of the cadaster and from image matching. In a joint research project, the Bavarian State Agency for Surveying and Geoinformation and the TUM, Chair of Geoinformatics, transformed an AdV-CityGML-Profilebased test data set of Bavarian LoD2 building models into an INSPIRE-compliant schema. For the purpose of a transformation of such kind, the AdV provides a data specification, a test plan for 3D Building Models and a mapping table. The research project examined whether the transformation rules defined in the mapping table, were unambiguous and sufficient for implementing a transformation of LoD2 data based on the AdV-CityGML-Profile into the INSPIRE schema. The proof of concept was carried out by transforming production data of the Bavarian 3D Building Model in LoD2 into the INSPIRE BU schema. In order to assure the quality of the data to be transformed, the test specifications according to the test plan for 3D Building Models of the AdV were carried out. The AdV mapping table was checked for completeness and correctness and amendments were made accordingly.

ESTABLISHING A NATIONAL 3D GEO-DATA MODEL FOR BUILDING DATA COMPLIANT TO CITYGML: CASE OF TURKEY

This paper presents the generation of the 3D national building geo-data model of Turkey, which is compatible with the international OGC CityGML Encoding Standard. We prepare an ADE named CityGML-TRKBIS.BI that is produced by extending existing thematic modules of CityGML according to TRKBIS needs. All thematic data groups in TRKBIS geo-data model have been remodelled in order to generate the national large scale 3D geo-data model for Turkey. Specific attention has been paid to data groups that have different class structure according to related CityGML data themes such as building data model. Current 2D geo-information model for building data theme of Turkey (TRKBIS.BI) was established based on INSPIRE specifications for building (Core 2D and Extended 2D profiles), ISO/TC 211 standards and OGC web services. New version of TRKBIS.BI which is established according to semantic and geometric rules of CityGML will represent 2D-2.5D and 3D objects. After a short overview on generic approach, this paper describes extending CityGML building data theme according to TRKBIS.BI through several steps. First, building models of both standards were compared according to their data structure, classes and attributes. Second, CityGML building model was extended with respect to TRKBIS needs and CityGML-TRKBIS Building ADE was established in UML. This study provides new insights into 3D applications in Turkey. The generated 3D geo-data model for building thematic class will be used as a common exchange format that meets 2D, 2.5D and 3D implementation needs at national level.

ESTABLISHING A NATIONAL 3D GEO-DATA MODEL FOR BUILDING DATA COMPLIANT TO CITYGML: CASE OF TURKEY

Abstract. This paper presents the generation of the 3D national building geo-data model of Turkey, which is compatible with the international OGC CityGML Encoding Standard. We prepare an ADE named CityGML-TRKBIS.BI that is produced by extending existing thematic modules of CityGML according to TRKBIS needs. All thematic data groups in TRKBIS geo-data model have been remodelled in order to generate the national large scale 3D geo-data model for Turkey. Specific attention has been paid to data groups that have different class structure according to related CityGML data themes such as building data model. Current 2D geo-information model for building data theme of Turkey (TRKBIS.BI) was established based on INSPIRE specifications for building (Core 2D and Extended 2D profiles), ISO/TC 211 standards and OGC web services. New version of TRKBIS.BI which is established according to semantic and geometric rules of CityGML will represent 2D-2.5D and 3D objects. After a short overview on generic approach, this paper describes extending CityGML building data theme according to TRKBIS.BI through several steps. First, building models of both standards were compared according to their data structure, classes and attributes. Second, CityGML building model was extended with respect to TRKBIS needs and CityGML-TRKBIS Building ADE was established in UML. This study provides new insights into 3D applications in Turkey. The generated 3D geo-data model for building thematic class will be used as a common exchange format that meets 2D, 2.5D and 3D implementation needs at national level.

An ontology-based approach for developing data exchange requirements and model views of building information modeling

Each domain industry requires the detailed specifications for sharing and exchanging building information models throughout the design, construction, and operation phases. Industry Foundation Classes (IFC) Model View Definitions (MVDs) specify required information for exchanges of building model data among building project experts. The data involves the identification of model semantics shared by two or more applications. However, since no robust standard for defining building semantics and requirements for data exchange has been agreed upon, information embedded in domain-specific MVDs are generated separately and are vague in scope, which results in a lack of consistency. In addition, the Information Delivery Manual (IDM) that includes exchange specifications needed for each exchange process of a product model is manually defined in a paper-based document. Because there is no clear logical link between the units of information in the exchange requirements of an IDM, and those of MVDs, the mapping that translates requirements of an IDM into ones of an MVD is open to various interpretation, without semantic and logical consistency. Such challenges might result in redundant requirements and rules for data exchange that are not supposed to be handled in the process of MVDs. To ameliorate this situation, this research proposes the new approach of formalizing domain knowledge and defining accurate data modules for model views. To achieve this goal, the authors employed ontological principles for generating an IDM for the precast concrete domain and for linking its MVD with formal information models. The formalized structure of domain knowledge is expected to support defining explicit data modules and developing manageable relationships among entities using semantic reasoning so that domain professionals and software vendors can identify the intents of the requirements of mapped MVDs and keep track of mapping problems. Moreover, to integrate IDM and MVD development processes, the ontology-based IDM is parsed and translated from OWL/XML to mvdXML, which automatically generates MVD documentation in the IfcDoc tool.

True orthoimage generation by mutual recovery of occlusion areas

Demand for orthoimages is increasing as a crucial component of geographic information systems (GISs). Orthoimages are geometrically equivalent to planimetric maps, which show true geographic locations of terrain features. To produce orthoimages, geometric distortions from camera tilt and relief displacement from perspective images must be corrected. Traditionally, removing such distortions has been accomplished by differential rectification in a pixel-by-pixel fashion. However, this method cannot produce true orthoimages because of the double-mapping problem. We propose a method of generating patch-based true orthoimages for surface patches in buildings. The proposed method utilizes three-dimensional (3D) building model data. Patches from the data were projected onto aerial images to extract image patches and analysis of the superstructures was performed. Because orthoimages are generated for each building, the orthoimage quality is enhanced when using building data with a high level of detail. Instead of performing the complex visibility analysis of existing approaches, this article identifies occlusion areas based on unit surfaces of buildings and presents mutual recovery of occlusions using multiple images. To evaluate the feasibility of the method, experiments were performed with real datasets: (1) a building with a dome superstructure, (2) high-rise buildings close to each other, and (3) buildings with various shapes.

Managing Big City Information Based on WebVRGIS

A 3-D Shenzhen City Web platform based on the Web virtual reality geographical information system is presented. A 3-D global browser is employed to load multiple types of demand data from the city, such as 3-D building model data, residents’ information, and real-time and historical traffic data. Using these data, a 3-D analysis and visualization of the city’s information are conducted on a platform. The amount of information that can be visualized with this platform is very large, and the GIS-based navigational scheme enables great flexibility to access different available data sources. All the presented functions of the platform are extracted from the customers’ practical demand. The system design considers some existing geographic human–computer interaction research results.

Validation of a Technique for Estimating Alfalfa (<i>Medicago sativa</i>) Biomass from Canopy Volume

Determining biomass production of individual alfalfa (Medicago sativa L.) plants in space planted evaluation studies is generally not feasible. Clipping plants is time consuming, expensive, and often not possible if the plants are subjected to grazing. A regression function (B′ = 0.72558 + 0.11638 × V′) was developed from spaced plants growing on rangeland in northwestern South Dakota near Buffalo to nondestructively estimate individual plant biomass (B) from canopy volume (V). However, external validation is necessary to effectively apply the model to other environments. In the summer of 2015, new data to validate the model were collected from spaced plants near Brookings, South Dakota. Canopy volume and clipped plant biomass were obtained from ten alfalfa populations varying in genetic background, growth habit, and growth stage. Fitted models for the model-building and validation data sets had similar estimated regression coefficients and attributes. Mean squared prediction errors (MSPR) were similar to or smaller than error mean square (MSE) of the model-building regression model, indicating reasonable predictive ability. Validation results indicated that the model reliably estimated biomass of plants in another environment. However, the technique should not be utilized where individual plants are not easily distinguished, such as alfalfa monocultures. Estimating biomass from canopy volume values that are extrapolations (>2.077 × 106 cm3) of the model-building data set is not recommended.

A pattern-based automated approach to building energy model calibration

Building model calibration is critical in bringing simulated energy use closer to the actual consumption. This paper presents a novel, automated model calibration approach that uses logic linking parameter tuning with bias pattern recognition to overcome some of the disadvantages associated with traditional calibration processes. The pattern-based process contains four key steps: (1) running the original pre-calibrated energy model to obtain monthly simulated electricity and gas use; (2) establishing a pattern bias, either Universal or Seasonal Bias, by comparing load shape patterns of simulated and actual monthly energy use; (3) using programmed logic to select which parameter to tune first based on bias pattern, weather and input parameter interactions; and (4) automatically tuning the calibration parameters and checking the progress using pattern-fit criteria. The automated calibration algorithm was implemented in the Commercial Building Energy Saver, a web-based building energy retrofit analysis toolkit. The proof of success of the methodology was demonstrated using a case study of an office building located in San Francisco. The case study inputs included the monthly electricity bill, monthly gas bill, original building model and weather data with outputs resulting in a calibrated model that more closely matched that of the actual building energy use profile. The novelty of the developed calibration methodology lies in linking parameter tuning with the underlying logic associated with bias pattern identification. Although there are some limitations to this approach, the pattern-based automated calibration methodology can be universally adopted as an alternative to manual or hierarchical calibration approaches.