Model Library Research Articles

Research on the Digital Preservation of Intangible Cultural Heritage of Folk Dance Art Category

Abstract In this paper, based on the rapid head generation technique of the model library, we obtain a frontal 2D face photo, mark 13 feature points selected from 7 parts, such as both eyes, nose, mouth, etc., to determine the approximate position of the whole facial features, simulate the real color of the face according to the texture mapping of the face, and at the same time, we add the texture features of the target face in the to the matching model, to achieve the mapping of overlaying texture to the neutral texture and the fusion of skin color. Using HigherHRNet network extraction to obtain the coordinate information of the joint points of the intangible cultural heritage dance inheritors and their heat maps, the obtained key frames of the dance features are connected in a certain order to obtain the synthesized folk dance video with gesture estimation. Combining semantic segmentation of keyframes and style rendering, the visual image of the dance is designed, and the intangible cultural heritage of folk dance is analyzed through examples. The results show that this paper’s method achieves more than 90% recognition accuracy on all three datasets and more than 94.8% recognition accuracy on the folk dance movement dataset. On the evaluation of folk dance movements, the average distance calculated by this paper’s algorithm is the largest, 95.7, and the average score is the lowest, 43.6. The average distance and average score of this paper’s algorithm are in between the above two cases, i.e., the experimental results verify the effectiveness of this paper’s method. This study promotes the intelligent protection and creative inheritance of Chinese non-heritage dances through digital protection.

Numerical Optimization of the Input Factors and Responses of an Experimental Design Reinforce PVC Composite

In this study, the input factors (PVC, rattan, plantain peduncle, and temperature) and the responses (flexural strength and modulus of elasticity) of an experimental design to reinforce PVC composite were investigated. The assessment of suitability and ultimately the choice of the models were done based on the values of statistical parameters like coefficient of determination (R2 value), p value, F value, etc. The experimental data was carried out by fitting a second-order model in the Design Expert model library to the data to estimate the unknown model parameters. This process was accomplished by applying multiple regression analyses to the data. The optimum values of the responses were obtained by numerical optimization based on the criterion of desirability. The results obtained showed that the design was adequate, and the models developed from it were useful because the off-diagonal values were close to zero. Also, increasing the proportion of PVC resulted in a steep and significant increase in the flexural strength of the composite. More so, this trend was similar to the flexural strength for the response surface and the corresponding contour plots representing the relationship between PVC, rattan, and modulus of elasticity. Besides, at higher temperatures, the PVC material could act as a binder, which results in a strong interaction between the components of the composite material.

The TANDEM Euratom project: Context, objectives and workplan

The TANDEM project is a European initiative funded under the EURATOM program. The project started on September 2022 and has a duration of 36 months. TANDEM stands for Small Modular ReacTor for a European sAfe aNd Decarbonized Energy Mix.Small Modular Reactors (SMRs) can be hybridized with other energy sources, storage systems and energy conversion applications to provide electricity, heat and hydrogen. Hybrid energy systems have the potential to strongly contribute to the energy decarbonization targeting carbon-neutrality in Europe by 2050. However, the integration of nuclear reactors, particularly SMRs, in hybrid energy systems, is a new R&D topic to be investigated. In this context, the TANDEM project aims to develop assessments and tools to facilitate the safe and efficient integration of SMRs into low-carbon hybrid energy systems. An open-source “TANDEM” model library of hybrid system components will be developed in Modelica language which, by coupling, will extend the capabilities of existing tools implemented in the project. The project proposes to specifically address the safety issues of SMRs related to their integration into hybrid energy systems, involving specific interactions between SMRs and the rest of the hybrid systems; new initiating events may have to be considered in the safety approach.TANDEM will study two hybrid systems covering the main trends of the European energy policy and market evolution at 2035's horizon: a district heating network and power supply in a large urban area, and an energy hub serving energy conversion systems, including hydrogen production; the energy hub is inspired from a harbor-like infrastructure. TANDEM will provide assessments on SMR safety, hybrid system operationality and techno-economics. Societal considerations will also be encased by analyzing European citizen engagement in SMR technology safety.The work will result in technical, economic and societal recommendations and policy briefs on the safety of SMRs and their integration into hybrid energy systems for industry, R&D teams, Technical Safety Organizations, regulators, Non-Governmental Organizations and policy makers. The TANDEM consortium will involve 17 partners from 8 European countries (Belgium, Czech Republic, Finland, France, Germany, Italy, Spain, Ukraine).The TANDEM project has the ambition to become a pioneer initiative in Europe in gathering efforts and expertise around development of SMRs integration into hybrid energy systems. The dissemination and the exploitation of the project outcomes as well as the proposed Education & Training activities shall serve as a basis for a number of new R&D and innovation projects addressing the safety issues of SMRs and their integration into hybrid energy systems.

The impact of convective criteria on the properties of massive stars

Context. Libraries of stellar models computed with either the Ledoux or the Schwarzschild criterion to determine the sizes of convective regions are available in the literature. It is still not clear, however, which of these two criteria should be used, although many works have been devoted to that question in the past. Aims. In the framework of the evolution of single rotating stars, we study the differences between models computed with Ledoux and Schwarzschild criteria on the internal structure, evolutionary track in the Hertzsprung–Russell diagram (HRD), lifetimes, evolution of the surface abundances and velocities, and masses of the He and CO cores. We investigate the consequences on the nature of the supernova (SN) progenitors and the type of SN events, as well as on the stellar yields of light elements. We also study the impact on the outputs of population synthesis models. Methods. Models with initial masses between 7 and 120 M⊙ at solar metallicity (Z = 0.014) and with an initial rotation equal to 0 or 0.4 times the critical velocity at the zero-age main sequence were computed with either the Schwarzschild or the Ledoux criterion until the end of the C-burning phase. Results. Models with initial masses between 15 and 32 M⊙ computed with the Schwarzschild criterion show larger intermediate convective zones attached to the H-burning shell than models computed with the Ledoux criterion. Their CO cores and outer convective zones in the red supergiant (RSG) phase are also smaller. This impacts many outputs of stars during the core He-burning phase. Schwarzschild models have smaller CO cores and outer convective zones in the RSG phase, and their blue-to-red supergiant ratio is much higher than for Ledoux models. They also produce longer crossings of the Hertzsprung gap and favour blue loops. The upper luminosity of RSGs is little affected by the change in the convective criterion. The maximum luminosity of RSG progenitors for type II-P SN events is lowered from 5.2 to 4.95 when the Ledoux criterion is used instead of the Schwarzschild criterion in non-rotating models. The Schwarzschild criterion predicts longer-lasting, less nitrogen-enriched, and faster-rotating Cepheids. Rotational mixing tends to decrease the differences between Schwarzschild and Ledoux models. Conclusions. The results of this paper can be used as first guidelines to set up observational programs that may help to distinguish between these two model families.

Orchestration of model computing assets for the development of digital twins

With the development of industries and manufacturing requirements, the use of digital twin technology is promising for increasing efficiency and improving product quality. An important component of digital twin implementation is the provision of tools for modeling and simulation processes. In this study, a solution based on the use of Python-based models and the Controller software platform, which provides communication between models and external elements of digital twins and other IIoT solutions, was proposed as such a toolkit. It defines the main approaches for creating model, scenario, and function libraries, along with the concept of implementing dynamic scenarios based on JSON requests from the orchestrator. In addition, the algorithm, the structure of the Controller, and its main functionality are considered. The resulting solution takes advantage of the Python and Node.js languages in performing the relevant tasks and contains several solutions that reduce traffic and workload on communication systems, increase system reliability, scale the system, etc.

A new perspective of wind speed forecasting: Multi-objective and model selection-based ensemble interval-valued wind speed forecasting system

Wind-speed forecasting is pivotal for optimizing resource utilization and promoting sustainable development. Previous studies have predominantly focused on point and interval forecasts derived from single-valued wind speed series, failing to capture the inherent fluctuations and uncertainties in wind speed. This study introduces a novel approach: a multi-objective and model selection-based ensemble interval-valued wind speed forecasting system. The primary objective is to empower decision-makers with enhanced decision support and improved risk management. The proposed system comprises four integral components: an interval-valued wind-speed preprocessing module, a model library module, a model selection module, and a multi-objective ensemble module. First, the preprocessing module decomposes the complex interval-valued wind speed forecasting task into multiple simpler forecasting subtasks. Subsequently, a model library is constructed for different forecasting subtasks. The model selection module utilizes a comprehensive evaluation metric to select the best-suited prediction model for each forecasting subtask. Finally, the multi-objective ensemble module integrates the subtask prediction results to yield the interval-valued wind speed forecasting outcomes. The most significant findings of this study are: (1) When faced with different forecasting subtasks, the choice of the optimal prediction model varies depending on the nature of the task. Therefore, the results of the model selection also differ with changes in the data characteristics. (2) In the ensemble stage, the importance and contribution of different subtasks may differ. The proposed ensemble module considers the interrelations and interactions between subtasks, resulting in varying weights for each subtask. For the two different datasets from the Chengde wind farm, the interval mean absolute percentage error values were 2.0862 % and 3.3632 %, and the interval standard deviation values of the error were 0.1383 and 0.3206, respectively. The experimental results clearly demonstrate the exceptional performance of the proposed system in interval-valued wind speed forecasting, which provides better decision support and risk management for wind speed forecasting.

Discovery and preclinical development of LY3473329, a potent small molecule inhibitor of lipoprotein(a) formation

Abstract Background Lipoprotein(a) [Lp(a)] is a lipoprotein particle consisting of a low-density lipoprotein (LDL) particle and apolipoprotein(a) [apo(a)]. Lp(a) is a causal risk factor for cardiovascular disease. The formation of Lp(a) requires an initial interaction of apo(a) Kringle IV Domains 7 and 8 (KIV7, KIV8) with apoB-100 on LDL, followed by formation of a disulfide bond between apo(a) and apoB-100. Blocking the initial apo(a)-apoB interaction is a viable therapeutic approach to reduce circulating levels of Lp(a). The apo(a) protein is encoded by the LPA gene that arose from the plasminogen gene through an evolutionary gene duplication event. Because of sequence conservation between apo(a) and plasminogen, compound selectivity for apo(a) is imperative for clinical development. Purpose We report the discovery and preclinical characterization of LY3473329, a novel selective small molecule inhibitor of Lp(a) formation. Methods Computational and synthetic chemistry approaches coupled with multiple biochemical and biophysical assays were used to create apo(a) KIV7,8 binders. Chemical optimization led to molecules with potent inhibition of in vitro Lp(a) formation. Both apo(a) and plasminogen binding assays were conducted to evaluate compound selectivity. The potential for LY3473329 to lower steady state Lp(a) levels was assessed in human Lp(a) transgenic mice and in cynomolgus monkeys, and its effect on plasminogen activity was assessed in rat and monkey. Results Computational modeling, synthetic chemistry and small molecule library screens identified compounds that bind apo(a) KIV7 and KIV8 domains, and subsequent chemical optimization yielded compounds with sub-micromolar Lp(a) inhibition potency. Exploration of compound multivalency created inhibitors with sub-nanomolar potency, including LY3473329. LY3473329 engages multiple apo(a) KIV motifs, allowing it to potently inhibit Lp(a) formation in vitro. Oral doses of LY3473329 given to human Lp(a) transgenic mice and cynomolgus monkeys caused dose-dependent decreases in plasma Lp(a). The key binding motif for LY3473329 is shared by two KIV domains in rat and monkey plasminogen, but only one KIV domain in human plasminogen. LY3473329 was non-selective for rat and monkey plasminogen, but showed ∼ 50-fold selectivity for human plasminogen in in vitro binding assays. In cynomolgus monkeys and rats, LY3473329 significantly reduced plasminogen activity levels without adverse effects. Given its selectivity against human plasminogen, LY3473329 is expected to lower Lp(a) in human without affecting plasminogen. LY3473329 has been evaluated in a human Phase 1 study and is currently in Phase 2 clinical development. Conclusions LY3473329 is a potent and selective small molecule inhibitor of Lp(a) formation and is the only orally administered Lp(a) investigational therapeutic in clinical development.

The Farmer: A Reproducible Profile-fitting Photometry Package for Deep Galaxy Surveys

Abstract While space-borne optical and near-infrared facilities have succeeded in delivering a precise and spatially resolved picture of our Universe, their small survey area is known to underrepresent the true diversity of galaxy populations. Ground-based surveys have reached comparable depths but at lower spatial resolution, resulting in source confusion that hampers accurate photometry extractions. What once was limited to the infrared regime has now begun to challenge ground-based ultradeep surveys, affecting detection and photometry alike. Failing to address these challenges will mean forfeiting a representative view into the distant Universe. We introduce The Farmer: an automated, reproducible profile-fitting photometry package that pairs a library of smooth parametric models from The Tractor with a decision tree that determines the best-fit model in concert with neighboring sources. Photometry is measured by fitting the models on other bands leaving brightness free to vary. The resulting photometric measurements are naturally total, and no aperture corrections are required. Supporting diagnostics (e.g., χ 2) enable measurement validation. As fitting models is relatively time intensive, The Farmer is built with high-performance computing routines. We benchmark The Farmer on a set of realistic COSMOS-like images and find accurate photometry, number counts, and galaxy shapes. The Farmer is already being utilized to produce catalogs for several large-area deep extragalactic surveys where it has been shown to tackle some of the most challenging optical and near-infrared data available, with the promise of extending to other ultradeep surveys expected in the near future. The Farmer is available to download from GitHub (https://github.com/astroweaver/the_farmer) and Zenodo (https://doi.org/10.5281/zenodo.8205817).

A Blockchain-Based Parametric Model Library for Knowledge Sharing in Building Information Modeling Collaboration

A Blockchain-Based Parametric Model Library for Knowledge Sharing in Building Information Modeling Collaboration

A two-stage optimization method for improving the load flexibility of existing district energy systems

Decarbonization of district energy systems is essential for China to meet its carbon neutrality goal by 2060. Most existing district energy systems are missing historical load data and have incomplete information, resulting in a lack of data support for the low-carbon transition. Moreover, demand-side load flexibility has not been fully exploited in the planning stage. In this paper, we developed a two-stage computational approach to optimize district loads. We first established an integrated Python framework, incorporating the TEASER simulation tool and AixLib model library, to efficiently calculate baseline loads through the bottom-up modeling and simulation of district buildings. Then, a price-based integrated demand response strategy was introduced. A mixed-integer nonlinear programming model was formulated to optimize the energy pricing strategy with the objective of minimum load fluctuations. Finally, a case study was employed to illustrate the feasibility of the calculation method, showing a normalized mean bias error of 7.17%. The results further demonstrated that the strategy could reduce the peak electric and heat loads by 3.55% and 9.57%, and increase load rates by 3.85% and 9.48%, respectively. The strategy could assist district energy service providers to optimize equipment capacity configuration and enhance the low-carbon planning potential of energy systems from the demand-side.

Modeling ROS Based Applications with AADL

This paper presents a library of AADL models for ROS based applications. AADL models are provided for every ROS services, namely nodes, and for complete robots hardware and embedded computer boards. The model of the complete system describes the binding of software onto hardware components, and allows for CPU and bus load analysis. To this purpose, dedicated AADL properties are included into the models, that come from actual measurements onto the hardware platforms.

The updated BaSTI stellar evolution models and isochrones – IV. α-Depleted calculations

ABSTRACT This is the fourth paper of our new release of the BaSTI (a Bag of Stellar Tracks and Isochrones) stellar model and isochrone library. Following the updated solar-scaled, α-enhanced, and white dwarf model libraries, we present here α-depleted ([α/Fe] = −0.2) evolutionary tracks and isochrones, suitable to study the α-depleted stars discovered in Local Group dwarf galaxies and in the Milky Way. These calculations include all improvements and updates of the solar-scaled and α-enhanced models, and span a mass range between 0.1 and 15 M⊙, and 21 metallicities between [Fe/H] = −3.20 and +0.45 with a helium-to-metal enrichment ratio ΔY/ΔZ = 1.31, homogeneous with the solar-scaled and α-enhanced models. The isochrones – available in several photometric filters – cover an age range between ∼20 Myr and 14.5 Gyr, including the pre-main-sequence phase. We have compared our isochrones with independent calculations of α-depleted stellar models, available for the same α-element depletion adopted in the present investigation. We have also discussed the effect of an α-depleted heavy element distribution on the bolometric corrections in different wavelength regimes. Our α-depleted evolutionary tracks and isochrones are publicly available at our BaSTI website.

Design and implementation of a virtual nuclear pulse signal generator

This paper presents a virtual nuclear pulse signal generator. The pulse generator can be used in specific scenarios such as calibration and maintenance of nuclear detection systems, validation of nuclear signal processing algorithms, and nuclear physics teaching experiments, as a substitute for real radioactive sources and detectors to generate nuclear pulse signals. This helps to avoid exposing experimental personnel to radiation hazards. The pulse generator is capable of generating specific nuclear pulse signals according to experimental requirements, and these signals has the same physical characteristics as real nuclear pulse signals, including amplitude distribution, time and amplitude randomness. In the pulse generator, we conducted theoretical analysis of the radioactive source and detector, and established a model library for both, to obtain crucial parameters of the nuclear pulse signals. The pulse generator is built on a hardware framework with field-programmable gate array (FPGA) as the core, utilizing these key parameters to generate signals with realistic physical characteristics of nuclear pulse signals, including amplitude and time characteristics. The counting rate of the output nuclear pulse signals can be adjusted by configuring the hardware parameters of the pulse generator.

Catalyst: Fast and flexible modeling of reaction networks.

We introduce Catalyst.jl, a flexible and feature-filled Julia library for modeling and high-performance simulation of chemical reaction networks (CRNs). Catalyst supports simulating stochastic chemical kinetics (jump process), chemical Langevin equation (stochastic differential equation), and reaction rate equation (ordinary differential equation) representations for CRNs. Through comprehensive benchmarks, we demonstrate that Catalyst simulation runtimes are often one to two orders of magnitude faster than other popular tools. More broadly, Catalyst acts as both a domain-specific language and an intermediate representation for symbolically encoding CRN models as Julia-native objects. This enables a pipeline of symbolically specifying, analyzing, and modifying CRNs; converting Catalyst models to symbolic representations of concrete mathematical models; and generating compiled code for numerical solvers. Leveraging ModelingToolkit.jl and Symbolics.jl, Catalyst models can be analyzed, simplified, and compiled into optimized representations for use in numerical solvers. Finally, we demonstrate Catalyst's broad extensibility and composability by highlighting how it can compose with a variety of Julia libraries, and how existing open-source biological modeling projects have extended its intermediate representation.

On automated model discovery and a universal material subroutine for hyperelastic materials

Constitutive modeling is the cornerstone of computational and structural mechanics. In a finite element analysis, the constitutive model is encoded in the material subroutine, a function that maps local strains onto stresses. This function is called within every finite element, at each integration point, within every time step, at each Newton iteration. Today’s finite element packages offer large libraries of material models to choose from. However, the scientific criteria for appropriate model selection remain highly subjective and prone to user bias. Here we fully automate the process of model selection, autonomously discover the best model and parameters from experimental data, encode all possible discoverable models into a single material subroutine, and seamlessly integrate this universal material subroutine into a finite element analysis. We prototype this strategy for incompressible, isotropic, hyperelastic soft matter systems that we characterize through a combination of twelve possible terms. These terms feature the first and second invariants, raised to the first and second powers, embedded in the identity, exponential, and logarithmic functions, generating 22×2×3= 4096 models in total. We demonstrate how to integrate these models into a single universal material subroutine that features the classical neo Hooke, Blatz Ko, Mooney Rivlin, Demiray, Gent, and Holzapfel models as special cases. Finite element simulations with our new universal material subroutine show that it specializes well to these widely used models, generalizes well to newly discovered models, and agrees excellently with both experimental data and previous simulations. It also performs well within realistic finite element simulations and accurately predicts stress concentrations in the human brain for six different head impact scenarios. We anticipate that integrating automated model discovery into a universal material subroutine will generalize naturally to more complex compressible, anisotropic, inelastic materials and to other nonlinear finite element platforms. Replacing dozens of individual material subroutines by a single universal material subroutine that is populated directly via automated model discovery – entirely without human interaction – makes finite element analyses more accessible, more robust, and less vulnerable to human error. This could forever change how we simulate materials and structures.Our source code, data, and examples are available at https://github.com/LivingMatterLab.

Daisy: An integrated repeat protein curation service

Tandem repeats in proteins identification, classification and curation is a complex process that requires manual processing from experts, processing power and time. There are recent and relevant advances applying machine learning for protein structure prediction and repeat classification that are useful for this process. However, no service contemplates required databases and software to supplement researching on repeat proteins. In this publication we present Daisy, an integrated repeat protein curation web service. This service can process Protein Data Bank (PDB) and the AlphaFold Database entries for tandem repeats identification. In addition, it uses an algorithm to search a sequence against a library of Pfam hidden Markov model (HMM). Repeat classifications are associated with the identified families through RepeatsDB. This prediction is considered for enhancing the ReUPred algorithm execution and hastening the repeat units identification process. The service can also operate every associated PDB and AlphaFold structure with a UniProt proteome registry.Availability: The Daisy web service is freely accessible at daisy.bioinformatica.org.

Technical note: A collision prediction tool using Blender.

Non-coplanar radiotherapy treatment techniques on C-arm linear accelerators have the potential to reduce dose to organs-at-risk in comparison with coplanar treatment techniques. Accurately predicting possible collisions between gantry, table and patient during treatment planning is needed to ensure patient safety. We offer a freely available collision prediction tool using Blender, a free and open-source 3D computer graphics software toolset. A geometric model of a C-arm linear accelerator including a library of patient models is created inside Blender. Based on the model, collision predictions can be used both to calculate collision-free zones and to check treatment plans for collisions. The tool is validated for two setups, once with and once without a full body phantom with the same table position. For this, each gantry-table angle combination with a 2° resolution is manually checked for collision interlocks at a TrueBeam system and compared to simulated collision predictions. For the collision check of a treatment plan, the tool outputs the minimal distance between the gantry, table and patient model and a video of the movement of the gantry and table, which is demonstrated for one use case. A graphical user interface allows user-friendly input of the table and patient specification for the collision prediction tool. The validation resulted in a true positive rate of 100%, which is the rate between the number of correctly predicted collision gantry-table combinations and the number of all measured collision gantry-table combinations, and a true negative rate of 89%, which is the ratio between the number of correctly predicted collision-free combinations and the number of all measured collision-free combinations. A collision prediction tool is successfully created and able to produce maps of collision-free zones and to test treatment plans for collisions including visualisation of the gantry and table movement.

Ionized regions in the central arcsecond of NGC 1068

Context. Several bright emission line regions have been observed in the central 100 parsecs of the active galaxy NGC 1068. Aims. We aim to determine the properties and ionization mechanism of three regions of NGC 1068: the nucleus (B) and two clouds located at 0.3″ and 0.7″ north of it (C and D). Methods. We combined SPHERE (0.95–1.65 μm) and SINFONI (1.5–2.45 μm) spectra for the three regions B, C, and D. We compared these spectra to several CLOUDY photoionization models and to the MAPPINGS III Library of Fast Radiative Shock Models. Results. The emission line spectra of the three regions are almost identical to each other and contribute to most of the emission line flux in the nuclear region. The emitting media contain multiple phases, the most luminous of which have temperatures ranging from 104.8 K to 106 K. Central photoionization models can reproduce some features of the spectra, but the fast radiative shock model provides the best fit to the data. Conclusions. The similarity between the three regions indicates that they belong to the same class of objects. Based on our comparisons, we conclude that they are shock regions located where the jet of the active galactic nucleus impacts massive molecular clouds.

β-Turn Induction by a Diastereopure Azepane-Derived Quaternary Amino Acid.

β-Turns are one of the most common secondary structures found in proteins. In the interest of developing novel β-turn inducers, a diastereopure azepane-derived quaternary amino acid has been incorporated into a library of simplified tetrapeptide models in order to assess the effect of the azepane position and peptide sequence on the stabilization of β-turns. The conformational analysis of these peptides by molecular modeling, NMR spectroscopy, and X-ray crystallography showed that this azepane amino acid is an effective β-turn inducer when incorporated at the i + 1 position. Moreover, the analysis of the supramolecular self-assembly of one of the β-turn-containing peptide models in the solid state reveals that it forms a supramolecular helical arrangement while maintaining the β-turn structure. The results here presented provide the basis for the use of this azepane quaternary amino acid as a strong β-turn inducer in the search for novel peptide-based bioactive molecules, catalysts, and biomaterials.

Beyond the appearance. Overwritten heritage communication

The knowledge of an urban space does not end with the collection of superficial information but requires a two-way relationship between subject and object. We are talking about an active process in which man has the opportunity to interact; man is the protagonist of an urban experience that leads him to formalize an image in his mind. If we think about the whole process, the goal is based on a research process, systematization of existing and new data, and, therefore, of all the analyses and studies carried out so far to access a deep knowledge capable of achieving the standardization of the acquisition process. It is intended to establish a codification of data (e.g., texts, bibliographies, maps, drawings, traditional and massive surveys, virtual reconstructions, etc.) in order to create a virtual environment (digital library) of heterogeneous digital models of cultural heritage, from large to small scale, but also of intangible data. From this paper’s specific point of view, this research presents a pilot experience that consists of structuring a protocol for documenting the eclectic historical heritage of the city of São Carlos, located in the State of São Paulo, Brazil. In addition to developing the protocol, this research also proposes that its results can be accessed digitally and democratically by society. Thus, it is emphasized that this work is the beginning of a process that does not end in this article, but rather, it will serve for the consolidation and systematization of data with the municipal institutions of São Carlos in order to value the eclectic style, which for many years was placed on the fringes of architectural studies in schools in the country.