Metadata Visualization of Cultural Heritage Information within a Collaborative Environment

Cultural content on the Web is available in various domains (cultural objects, datasets, geospatial data, moving images, scholarly texts and visual resources), concerns various topics, is written in different languages, targeted to both laymen and experts, and provided by different communities (libraries, archives museums and information industry) and individuals (Figure 1). The integration of information technologies and cultural heritage content on the Web is expected to have an impact on everyday life from the point of view of institutions, communities and individuals. In particular, collaborative environment scan recreate 3D navigable worlds that can offer new insights into our cultural heritage (Chan 2007). However, the main barrier is to find and relate cultural heritage information by end-users of cultural contents, as well as by organisations and communities managing and producing them. In this paper, we explore several visualisation techniques for supporting cultural interfaces, where the role of metadata is essential for supporting the search and communication among end-users (Figure 2). A conceptual framework was developed to integrate the data, purpose, technology, impact, and form components of a collaborative environment, Our preliminary results show that collaborative environments can help with cultural heritage information sharing and communication tasks because of the way in which they provide a visual context to end-users. They can be regarded as distributed virtual reality systems that offer graphically realised, potentially infinite, digital information landscapes. Moreover, collaborative environments also provide a new way of interaction between an end-user and a cultural heritage data set. Finally, the visualisation of metadata of a dataset plays an important role in helping end-users in their search for heritage contents on the Web.

Sensitivity analysis to assess the influence of the inertial properties of railway vehicle bodies on the vehicle’s dynamic behaviour

A sensitivity analysis has been performed to assess the influence of the inertial properties of railway vehicles on their dynamic behaviour. To do this, 216 dynamic simulations were performed modifying, one at a time, the masses, moments of inertia and heights of the centre of gravity of the carbody, the bogie and the wheelset. Three values were assigned to each parameter, corresponding to the percentiles 10, 50 and 90 of a data set stored in a database of railway vehicles. After processing the results of these simulations, the analyzed parameters were sorted by increasing influence. It was also found which of these parameters could be estimated with a lesser degree of accuracy for future simulations without appreciably affecting the simulation results. In general terms, it was concluded that the most sensitive inertial properties are the mass and the vertical moment of inertia, and the least sensitive ones the longitudinal and lateral moments of inertia.

A novel topology control approach to maintain the node degree in dynamic wireless sensor networks

Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power.

Nuevos Esquemas de Visualizaciones para Mejorar la Comprensibilidad de Modelos de Data Mining

La gran cantidad de datos que se registran diariamente en los sistemas de base de datos de las organizaciones ha generado la necesidad de analizarla. Sin embargo, se enfrentan a la complejidad de procesar enormes volúmenes de datos a través de métodos tradicionales de análisis. Además, dentro de un contexto globalizado y competitivo las organizaciones se mantienen en la búsqueda constante de mejorar sus procesos, para lo cual requieren herramientas que les permitan tomar mejores decisiones. Esto implica estar mejor informado y conocer su historia digital para describir sus procesos y poder anticipar (predecir) eventos no previstos. Estos nuevos requerimientos de análisis de datos ha motivado el desarrollo creciente de proyectos de minería de datos. El proceso de minería de datos busca obtener desde un conjunto masivo de datos, modelos que permitan describir los datos o predecir nuevas instancias en el conjunto. Implica etapas de: preparación de los datos, procesamiento parcial o totalmente automatizado para identificar modelos en los datos, para luego obtener como salida patrones, relaciones o reglas. Esta salida debe significar un nuevo conocimiento para la organización, útil y comprensible para los usuarios finales, y que pueda ser integrado a los procesos para apoyar la toma de decisiones. Sin embargo, la mayor dificultad es justamente lograr que el analista de datos, que interviene en todo este proceso, pueda identificar modelos lo cual es una tarea compleja y muchas veces requiere de la experiencia, no sólo del analista de datos, sino que también del experto en el dominio del problema. Una forma de apoyar el análisis de datos, modelos y patrones es a través de su representación visual, utilizando las capacidades de percepción visual del ser humano, la cual puede detectar patrones con mayor facilidad. Bajo este enfoque, la visualización ha sido utilizada en minería datos, mayormente en el análisis descriptivo de los datos (entrada) y en la presentación de los patrones (salida), dejando limitado este paradigma para el análisis de modelos. El presente documento describe el desarrollo de la Tesis Doctoral denominada “Nuevos Esquemas de Visualizaciones para Mejorar la Comprensibilidad de Modelos de Data Mining”. Esta investigación busca aportar con un enfoque de visualización para apoyar la comprensión de modelos minería de datos, para esto propone la metáfora de modelos visualmente aumentados. ABSTRACT The large amount of data to be recorded daily in the systems database of organizations has generated the need to analyze it. However, faced with the complexity of processing huge volumes of data over traditional methods of analysis. Moreover, in a globalized and competitive environment organizations are kept constantly looking to improve their processes, which require tools that allow them to make better decisions. This involves being bettered informed and knows your digital story to describe its processes and to anticipate (predict) unanticipated events. These new requirements of data analysis, has led to the increasing development of data-mining projects. The data-mining process seeks to obtain from a massive data set, models to describe the data or predict new instances in the set. It involves steps of data preparation, partially or fully automated processing to identify patterns in the data, and then get output patterns, relationships or rules. This output must mean new knowledge for the organization, useful and understandable for end users, and can be integrated into the process to support decision-making. However, the biggest challenge is just getting the data analyst involved in this process, which can identify models is complex and often requires experience not only of the data analyst, but also the expert in the problem domain. One way to support the analysis of the data, models and patterns, is through its visual representation, i.e., using the capabilities of human visual perception, which can detect patterns easily in any context. Under this approach, the visualization has been used in data mining, mostly in exploratory data analysis (input) and the presentation of the patterns (output), leaving limited this paradigm for analyzing models. This document describes the development of the doctoral thesis entitled "New Visualizations Schemes to Improve Understandability of Data-Mining Models". This research aims to provide a visualization approach to support understanding of data mining models for this proposed metaphor visually enhanced models.

Parallel execution of Prolog programs: a survey

Since the early days of logic programming, researchers in the field realized the potential for exploitation of parallelism present in the execution of logic programs. Their high-level nature, the presence of nondeterminism, and their referential transparency, among other characteristics, make logic programs interesting candidates for obtaining speedups through parallel execution. At the same time, the fact that the typical applications of logic programming frequently involve irregular computations, make heavy use of dynamic data structures with logical variables, and involve search and speculation, makes the techniques used in the corresponding parallelizing compilers and run-time systems potentially interesting even outside the field. The objective of this article is to provide a comprehensive survey of the issues arising in parallel execution of logic programming languages along with the most relevant approaches explored to date in the field. Focus is mostly given to the challenges emerging from the parallel execution of Prolog programs. The article describes the major techniques used for shared memory implementation of Or-parallelism, And-parallelism, and combinations of the two. We also explore some related issues, such as memory management, compile-time analysis, and execution visualization.

Feature selection in the reconstruction of complex network representations of spectral data

Complex networks have been extensively used in the last decade to characterize and analyze complex systems, and they have been recently proposed as a novel instrument for the analysis of spectra extracted from biological samples. Yet, the high number of measurements composing spectra, and the consequent high computational cost, make a direct network analysis unfeasible. We here present a comparative analysis of three customary feature selection algorithms, including the binning of spectral data and the use of information theory metrics. Such algorithms are compared by assessing the score obtained in a classification task, where healthy subjects and people suffering from different types of cancers should be discriminated. Results indicate that a feature selection strategy based on Mutual Information outperforms the more classical data binning, while allowing a reduction of the dimensionality of the data set in two orders of magnitude

In situ surveillance of capacitive pressure transmitter dynamic poles

In this work, a methodology is proposed to find the dynamic poles of a capacitive pressure transmitter in order to enhance and extend the online surveillance of this type of sensor based on the response time measurement by applying noise analysis techniques and the dynamic data system procedure. Several measurements taken from a pressurized water reactor have been analyzed. The methodology proposes an autoregressive fit whose order is determined by the sensor dynamic poles. Nevertheless, the signals that have been analyzed could not be filtered properly in order to remove the plant noise; thus, this was considered as an additional pair of complex conjugate poles. With this methodology we have come up with the numerical value of the sensor second real pole in spite of its low influence on the sensor dynamic response. This opens up a more accurate online sensor surveillance since the previous methods were achieved by considering one real pole only.

Assessment of the influence of the elastic properties of rail vehicle suspensions on safety, ride quality and track fatigue

A sensitivity analysis has been performed to assess the influence of the elastic properties of railway vehicle suspensions on the vehicle dynamic behaviour. To do this, 144 dynamic simulations were performed modifying, one at a time, the stiffness and damping coefficients, of the primary and secondary suspensions. Three values were assigned to each parameter, corresponding to the percentiles 10, 50 and 90 of a data set stored in a database of railway vehicles.After processing the results of these simulations, the analyzed parameters were sorted by increasing influence. It was also found which of these parameters could be estimated with a lesser degree of accuracy in future simulations without appreciably affecting the simulation results. In general terms, it was concluded that the highest influences were found for the longitudinal stiffness and the lateral stiffness of the primary suspension, and the lowest influences for the vertical stiffness and the vertical damping of the primary suspension, with the parameters of the secondary suspension showing intermediate influences between them.

Inteligencia artificial para la predicción y control del acabado superficial en procesos de fresado a alta velocidad

El objetivo principal de esta tesis doctoral es profundizar en el análisis y diseño de un sistema inteligente para la predicción y control del acabado superficial en un proceso de fresado a alta velocidad, basado fundamentalmente en clasificadores Bayesianos, con el prop´osito de desarrollar una metodolog´ıa que facilite el diseño de este tipo de sistemas. El sistema, cuyo propósito es posibilitar la predicción y control de la rugosidad superficial, se compone de un modelo aprendido a partir de datos experimentales con redes Bayesianas, que ayudar´a a comprender los procesos dinámicos involucrados en el mecanizado y las interacciones entre las variables relevantes. Dado que las redes neuronales artificiales son modelos ampliamente utilizados en procesos de corte de materiales, también se incluye un modelo para fresado usándolas, donde se introdujo la geometría y la dureza del material como variables novedosas hasta ahora no estudiadas en este contexto. Por lo tanto, una importante contribución en esta tesis son estos dos modelos para la predicción de la rugosidad superficial, que se comparan con respecto a diferentes aspectos: la influencia de las nuevas variables, los indicadores de evaluación del desempeño, interpretabilidad. Uno de los principales problemas en la modelización con clasificadores Bayesianos es la comprensión de las enormes tablas de probabilidad a posteriori producidas. Introducimos un m´etodo de explicación que genera un conjunto de reglas obtenidas de árboles de decisión. Estos árboles son inducidos a partir de un conjunto de datos simulados generados de las probabilidades a posteriori de la variable clase, calculadas con la red Bayesiana aprendida a partir de un conjunto de datos de entrenamiento. Por último, contribuimos en el campo multiobjetivo en el caso de que algunos de los objetivos no se puedan cuantificar en números reales, sino como funciones en intervalo de valores. Esto ocurre a menudo en aplicaciones de aprendizaje automático, especialmente las basadas en clasificación supervisada. En concreto, se extienden las ideas de dominancia y frontera de Pareto a esta situación. Su aplicación a los estudios de predicción de la rugosidad superficial en el caso de maximizar al mismo tiempo la sensibilidad y la especificidad del clasificador inducido de la red Bayesiana, y no solo maximizar la tasa de clasificación correcta. Los intervalos de estos dos objetivos provienen de un m´etodo de estimación honesta de ambos objetivos, como e.g. validación cruzada en k rodajas o bootstrap.---ABSTRACT---The main objective of this PhD Thesis is to go more deeply into the analysis and design of an intelligent system for surface roughness prediction and control in the end-milling machining process, based fundamentally on Bayesian network classifiers, with the aim of developing a methodology that makes easier the design of this type of systems. The system, whose purpose is to make possible the surface roughness prediction and control, consists of a model learnt from experimental data with the aid of Bayesian networks, that will help to understand the dynamic processes involved in the machining and the interactions among the relevant variables. Since artificial neural networks are models widely used in material cutting proceses, we include also an end-milling model using them, where the geometry and hardness of the piecework are introduced as novel variables not studied so far within this context. Thus, an important contribution in this thesis is these two models for surface roughness prediction, that are then compared with respecto to different aspects: influence of the new variables, performance evaluation metrics, interpretability. One of the main problems with Bayesian classifier-based modelling is the understanding of the enormous posterior probabilitiy tables produced. We introduce an explanation method that generates a set of rules obtained from decision trees. Such trees are induced from a simulated data set generated from the posterior probabilities of the class variable, calculated with the Bayesian network learned from a training data set. Finally, we contribute in the multi-objective field in the case that some of the objectives cannot be quantified as real numbers but as interval-valued functions. This often occurs in machine learning applications, especially those based on supervised classification. Specifically, the dominance and Pareto front ideas are extended to this setting. Its application to the surface roughness prediction studies the case of maximizing simultaneously the sensitivity and specificity of the induced Bayesian network classifier, rather than only maximizing the correct classification rate. Intervals in these two objectives come from a honest estimation method of both objectives, like e.g. k-fold cross-validation or bootstrap.

Application of Independent Components Analysis with the JADE algorithm and NIR hyperspectral imaging for revealing food adulteration

In recent years, Independent Components Analysis (ICA) has proven itself to be a powerful signal-processing technique for solving the Blind-Source Separation (BSS) problems in different scientific domains. In the present work, an application of ICA for processing NIR hyperspectral images to detect traces of peanut in wheat flour is presented. Processing was performed without a priori knowledge of the chemical composition of the two food materials. The aim was to extract the source signals of the different chemical components from the initial data set and to use them in order to determine the distribution of peanut traces in the hyperspectral images. To determine the optimal number of independent component to be extracted, the Random ICA by blocks method was used. This method is based on the repeated calculation of several models using an increasing number of independent components after randomly segmenting the matrix data into two blocks and then calculating the correlations between the signals extracted from the two blocks. The extracted ICA signals were interpreted and their ability to classify peanut and wheat flour was studied. Finally, all the extracted ICs were used to construct a single synthetic signal that could be used directly with the hyperspectral images to enhance the contrast between the peanut and the wheat flours in a real multi-use industrial environment. Furthermore, feature extraction methods (connected components labelling algorithm followed by flood fill method to extract object contours) were applied in order to target the spatial location of the presence of peanut traces. A good visualization of the distributions of peanut traces was thus obtained

Aprendizaje integrado en arquitectura con modelos virtuales : implementación de metodología BIM en la docencia universitaria

Los procesos de diseño y construcción en Arquitectura han mostrado un desarrollo de optimización históricamente muy deficiente cuando se compara con las restantes actividades típicamente industriales. La aspiración constante a una industrialización efectiva, tanto en aras de alcanzar mayores cotas de calidad así como de ahorro de recursos, recibe hoy una oportunidad inmejorable desde el ámbito informático: el Building Information Modelling o BIM. Lo que en un inicio puede parecer meramente un determinado tipo de programa informático, en realidad supone un concepto de “proceso” que subvierte muchas rutinas hoy habituales en el desarrollo de proyectos y construcciones arquitectónicas. La inclusión y desarrollo de datos ligados al proyecto, desde su inicio hasta el fin de su ciclo de vida, conlleva la oportunidad de crear una realidad virtual dinámica y actualizable, que por añadidura posibilita su ensayo y optimización en todos sus aspectos: antes y durante su ejecución, así como vida útil. A ello se suma la oportunidad de transmitir eficientemente los datos completos de proyecto, sin apenas pérdidas o reelaboración, a la cadena de fabricación, lo que facilita el paso a una industrialización verdaderamente significativa en edificación. Ante una llamada mundial a la optimización de recursos y el interés indudable de aumentar beneficios económicos por medio de la reducción del factor de incertidumbre de los procesos, BIM supone un opción de mejora indudable, y así ha sido reconocido a través de la inminente implantación obligatoria por parte de los gobiernos (p. ej. Gran Bretaña en 2016 y España en 2018). La modificación de procesos y roles profesionales que conlleva la incorporación de BIM resulta muy significativa y marcará el ejercicio profesional de los futuros graduados en las disciplinas de Arquitectura, Ingeniería y Construcción (AEC por sus siglas en inglés). La universidad debe responder ágilmente a estas nuevas necesidades incorporando esta metodología en la enseñanza reglada y aportando una visión sinérgica que permita extraer los beneficios formativos subyacentes en el propio marco BIM. En este sentido BIM, al aglutinar el conjunto de datos sobre un único modelo virtual, ofrece un potencial singularmente interesante. La realidad tridimensional del modelo, desarrollada y actualizada continuamente, ofrece al estudiante una gestión radicalmente distinta de la representación gráfica, en la que las vistas parciales de secciones y plantas, tan complejas de asimilar en los inicios de la formación universitaria, resultan en una mera petición a posteriori, para ser extraída según necesidad del modelo virtual. El diseño se realiza siempre sobre el propio modelo único, independientemente de la vista de trabajo elegida en cada momento, permaneciendo los datos y sus relaciones constructivas siempre actualizados y plenamente coherentes. Esta descripción condensada de características de BIM preconfiguran gran parte de las beneficios formativos que ofrecen los procesos BIM, en especial, en referencia al desarrollo del diseño integrado y la gestión de la información (incluyendo TIC). Destacan a su vez las facilidades en comprensión visual de elementos arquitectónicos, sistemas técnicos, sus relaciones intrínsecas así como procesos constructivos. A ello se une el desarrollo experimental que la plataforma BIM ofrece a través de sus software colaborativos: la simulación del comportamiento estructural, energético, económico, entre otros muchos, del modelo virtual en base a los datos inherentes del proyecto. En la presente tesis se describe un estudio de conjunto para explicitar tanto las cualidades como posibles reservas en el uso de procesos BIM, en el marco de una disciplina concreta: la docencia de la Arquitectura. Para ello se ha realizado una revisión bibliográfica general sobre BIM y específica sobre docencia en Arquitectura, así como analizado las experiencias de distintos grupos de interés en el marco concreto de la enseñanza de la en Arquitectura en la Universidad Europea de Madrid. El análisis de beneficios o reservas respecto al uso de BIM se ha enfocado a través de la encuesta a estudiantes y la entrevista a profesionales AEC relacionados o no con BIM. Las conclusiones del estudio permiten sintetizar una implantación de metodología BIM que para mayor claridad y facilidad de comunicación y manejo, se ha volcado en un Marco de Implantación eminentemente gráfico. En él se orienta sobre las acciones docentes para el desarrollo de competencias concretas, valiéndose de la flexibilidad conceptual de los Planes de Estudio en el contexto del Espacio Europeo de Educación Superior (Declaración de Bolonia) para incorporar con naturalidad la nueva herramienta docente al servicio de los objetivos formativo legalmente establecidos. El enfoque global del Marco de Implementación propuesto facilita la planificación de acciones formativas con perspectiva de conjunto: combinar los formatos puntuales o vehiculares BIM, establecer sinergias transversales y armonizar recursos, de modo que la metodología pueda beneficiar tanto la asimilación de conocimientos y habilidades establecidas para el título, como el propio flujo de aprendizaje o learn flow BIM. Del mismo modo reserva, incluso visualmente, aquellas áreas de conocimiento en las que, al menos en la planificación actual, la inclusión de procesos BIM no se considera ventajosa respecto a otras metodologías, o incluso inadecuadas para los objetivos docentes establecidos. Y es esta última categorización la que caracteriza el conjunto de conclusiones de esta investigación, centrada en: 1. la incuestionable necesidad de formar en conceptos y procesos BIM desde etapas muy iniciales de la formación universitaria en Arquitectura, 2. los beneficios formativos adicionales que aporta BIM en el desarrollo de competencias muy diversas contempladas en el currículum académico y 3. la especificidad del rol profesional del arquitecto que exigirá una implantación cuidadosa y ponderada de BIM que respete las metodologías de desarrollo creativo tradicionalmente efectivas, y aporte valor en una reorientación simbiótica con el diseño paramétrico y fabricación digital que permita un diseño finalmente generativo. ABSTRACT The traditional architectural design and construction procedures have proven to be deficient where process optimization is concerned, particularly when compared to other common industrial activities. The ever‐growing strife to achieve effective industrialization, both in favor of reaching greater quality levels as well as sustainable management of resources, has a better chance today than ever through a mean out of the realm of information technology, the Building Information Modelling o BIM. What may initially seem to be merely another computer program, in reality turns out to be a “process” concept that subverts many of today’s routines in architectural design and construction. Including and working with project data from the very beginning to the end of its full life cycle allows for creating a dynamic and updatable virtual reality, enabling data testing and optimizing throughout: before and during execution, all the way to the end of its lifespan. In addition, there is an opportunity to transmit complete project data efficiently, with hardly any loss or redeveloping of the manufacture chain required, which facilitates attaining a truly significant industrialization within the construction industry. In the presence of a world‐wide call for optimizing resources, along with an undeniable interest in increasing economic benefits through reducing uncertainty factors in its processes, BIM undoubtedly offers a chance for improvement as acknowledged by its imminent and mandatory implementation on the part of governments (for example United Kingdom in 2016 and Spain in 2018). The changes involved in professional roles and procedures upon incorporating BIM are highly significant and will set the course for future graduates of Architecture, Engineering and Construction disciplines (AEC) within their professions. Higher Education must respond to such needs with swiftness by incorporating this methodology into their educational standards and providing a synergetic vision that focuses on the underlying educational benefits inherent in the BIM framework. In this respect, BIM, in gathering data set under one single virtual model, offers a uniquely interesting potential. The three‐dimensional reality of the model, under continuous development and updating, provides students with a radically different graphic environment, in which partial views of elevation, section or plan that tend characteristically to be difficult to assimilate at the beginning of their studies, become mere post hoc requests to be ordered when needed directly out the virtual model. The design is always carried out on the sole model itself, independently of the working view chosen at any particular moment, with all data and data relations within construction permanently updated and fully coherent. This condensed description of the features of BIM begin to shape an important part of the educational benefits posed by BIM processes, particularly in reference to integrated design development and information management (including ITC). At the same time, it highlights the ease with which visual understanding is achieved regarding architectural elements, technology systems, their intrinsic relationships, and construction processes. In addition to this, there is the experimental development the BIM platform grants through its collaborative software: simulation of structural, energetic, and economic behavior, among others, of the virtual model according to the data inherent to the project. This doctoral dissertation presents a broad study including a wide array of research methods and issues in order to specify both the virtues and possible reservations in the use of BIM processes within the framework of a specific discipline: teaching Architecture. To do so, a literature review on BIM has been carried out, specifically concerning teaching in the discipline of Architecture, as well as an analysis of the experience of different groups of interest delimited to Universidad Europea de Madrid. The analysis of the benefits and/or limitations of using BIM has been approached through student surveys and interviews with professionals from the AEC sector, associated or not, with BIM. Various diverse educational experiences are described and academic management for experimental implementation has been analyzed. The conclusions of this study offer a synthesis for a Framework of Implementation of BIM methodology, which in order to reach greater clarity, communication ease and user‐friendliness, have been posed in an eminently graphic manner. The proposed framework proffers guidance on teaching methods conducive to the development of specific skills, taking advantage of the conceptual flexibility of the European Higher Education Area guidelines based on competencies, which naturally facilitate for the incorporation of this new teaching tool to achieve the educational objectives established by law. The global approach of the Implementation Framework put forth in this study facilitates the planning of educational actions within a common perspective: combining exceptional or vehicular BIM formats, establishing cross‐disciplinary synergies, and sharing resources, so as to purport a methodology that contributes to the assimilation of knowledge and pre‐defined competencies within the degree program, and to the flow of learning itself. At the same time, it reserves, even visually, those areas of knowledge in which the use of BIM processes is not considered necessarily an advantage over other methodologies, or even inadequate for the learning outcomes established, at least where current planning is concerned. It is this last category which characterizes the research conclusions as a whole, centering on: 1. The unquestionable need for teaching BIM concepts and processes in Architecture very early on, in the initial stages of higher education; 2. The additional educational benefits that BIM offers in a varied array of competency development within the academic curriculum; and 3. The specific nature of the professional role of the Architect, which demands a careful and balanced implementation of BIM that respects the traditional teaching methodologies that have proven effective and creative, and adds value by a symbiotic reorientation merged with parametric design and digital manufacturing so to enable for a finally generative design.