Big data analytics correlation taxonomy

Big data analytics (BDA) is an increasingly popular research area for both organisations and academia due to its usefulness in facilitating human understanding and communication. In the literature, researchers have focused on classifying big data according to data type, data security or level of difficulty, and many research papers reveal that there is a lack of information on evidence of a real-world link of big data analytics methods and its associated techniques. Thus, many organisations are still struggling to realise the actual value of big data analytic methods and its associated techniques. Therefore, this paper gives a design research account for formulating and proposing a step ahead to understand the relation between the analytical methods and its associated techniques. Furthermore, this paper is an attempt to clarify this uncertainty and identify the difference between analytics methods and techniques by giving clear definitions for each method and its associated techniques to integrate them later in a new correlation taxonomy based on the research approaches. Thus, the primary outcome of this research is to achieve for the first time a correlation taxonomy combining analytic methods used for big data and its recommended techniques that are compatible for various sectors. This investigation was done through studying various descriptive articles of big data analytics methods and its associated techniques in different industries

Exploring Model-to-Model Transformations for RIA Architectures by means of a Systematic Mapping Study

This study focuses on model-to-model – M2M – transformations, as part of the Model- Driven Development – MDD – approach, for Rich Internet Applications – RIA. The main aim of this study is to identify fields that require further contributions, and/or research opportunities in the previously mentioned context. We applied mapping studies techniques, since these techniques use the same basic methodology as reviews but are more general and aimed at discovering what the research trends are, allowing to identify gaps in the literature. From an initial set of 132 papers, we selected 30 papers first. Then, thanks to experts’ suggestion, we added 3 additional papers. Therefore, we considered 33 research papers. The performed analysis led to various considerations. Among the important ones, we can mention: there are many newly proposed methods, the scarcity of rigorous and formal validation of such methods, the problem of the portability of Platform Independent Models – PIM, and the low number of tools available for MDD.Laboratorio de Investigación y Formación en Informática Avanzad

Exploring Model-to-Model Transformations for RIA Architectures by means of a Systematic Mapping Study

This study focuses on model-to-model – M2M – transformations, as part of the Model-Driven Development – MDD – approach, for Rich Internet Applications – RIA. The main aim of this study is to identify fields that require further contributions, and/or research opportunities in the previously mentioned context.CONACYT – Consejo Nacional de Ciencia y TecnologíaPROCIENCI

Scientific History of Incipit in the period 2010-2016

Historial de la actividad científica y técnica del Instituto de Ciencias del Patrimonio (Incipit) del CSIC, basado en Santiago de Compostela, desde su fecha de creación (2010) hasta el año 2016. Se presentan la misión y las líneas de investigación del Incipit, centradas principalmente en el estudio de los procesos de patrimonialización y de valorización social del patrimonio cultural realizadas con una perspectiva transdisciplinar. Se relacionan las publicaciones, proyectos de investigación, actividades de ciencia pública, eventos de comunicación y productos de divulgación que su personal investigador ha producido a lo largo de estos años.General introduction to the Incipit. Presentation of the Research Line: Cultural Heritage Studies: Sub-Theme: Landscape Archaeology and Cultural Landscapes, Sub-theme: Heritagization Processes: Memory, Power and Ethnicity, Sub-theme: Socioeconomics of Cultural Heritage, Sub-theme: Archaeology of the Contemporary Past, Sub-theme: Material culture and formalization processes of cultural heritage. Scientific Contributions. Transfer of Knowledge. International Activities. Other Activities and Results. Scientific DisseminationN

Exploring Model-to-Model Transformations for RIA Architectures by means of a Systematic Mapping Study

This study focuses on model-to-model – M2M – transformations, as part of the ModelDriven Development – MDD – approach, for Rich Internet Applications – RIA. The main aim of this study is to identify fields that require further contributions, and/or research opportunities in the previously mentioned context. We applied mapping studies techniques, since these techniques use the same basic methodology as reviews but are more general and aimed at discovering what the research trends are, allowing to identify gaps in the literature. From an initial set of 132 papers, we selected 30 papers first. Then, thanks to experts’ suggestion, we added 3 additional papers. Therefore, we considered 33 research papers. The performed analysis led to various considerations. Among the important ones, we can mention: there are many newly proposed methods, the scarcity of rigorous and formal validation of such methods, the problem of the portability of Platform Independent Models – PIM, and the low number of tools available for MDD

Engineering scalable modelling Languages

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Ingeniería Informática. Fecha de lectura: 08-11-2019Esta tesis tiene embargado el acceso al texto completo hasta el 08-05-2021Model-Driven Engineering (MDE) aims at reducing the cost of system development by raising the level of abstraction at which developers work. MDE-based solutions frequently involve the creation of Domain-Specific Modelling Languages (DSMLs). WhilethedefinitionofDSMLsandtheir(sometimesgraphical)supportingenvironments are recurring activities in MDE, they are mostly developed ad-hoc from scratch. The construction of these environments requires high expertise by developers, which currently need to spend large efforts for their construction. This thesis focusses on the development of scalable modelling environments for DSMLs based on patterns. For this purpose, we propose a catalogue of modularity patterns that can be used to extend a modelling language with services related to modularization and scalability. More specifically, these patterns allows defining model fragmentation strategies, scoping and visibility rules, model indexing services, and scoped constraints. Once the patterns have been applied to the meta-model of a modelling language, we synthesize a customized modelling environment enriched with the defined services, which become applicable to both existing monolithic legacy models and new models. A second contribution of this thesis is a set of concepts and technologies to facilitate the creation of graphical editors. For this purpose, we define heuristics which identify structures in the DSML abstract syntax, and automatically assign their diagram representation. Using this approach, developers can create a graphical representation by default from a meta-model, which later can be customised. These contributions have been implemented in two Eclipse plug-ins called EMFSplitter and EMF-Stencil. On one hand, EMF-Splitter implements the catalogue of modularity patterns and, on the other hand, EMF-Stencil supports the heuristics and the generation of a graphical modelling environment. Both tools were evaluated in different case studies to prove their versatility, efficiency, and capabilitieEl Desarrollo de Software Dirigido por Modelos (MDE, por sus siglas en inglés) tiene como objetivo reducir los costes en el desarrollo de aplicaciones, elevando el nivel de abstracciónconelqueactualmentetrabajanlosdesarrolladores. Lassolucionesbasadas en MDE frecuentemente involucran la creación de Lenguajes de Modelado de Dominio Específico (DSML, por sus siglas en inglés). Aunque la definición de los DSMLs y sus entornos gráficos de modelado son actividades recurrentes en MDE, actualmente en la mayoría de los casos se desarrollan ad-hoc desde cero. La construcción de estos entornos requiere una alta experiencia por parte de los desarrolladores, que deben realizar un gran esfuerzo para construirlos. Esta tesis se centra en el desarrollo de entornos de modelado escalables para DSML basados en patrones. Para ello, se propone un catálogo de patrones de modularidad que se pueden utilizar para extender un lenguaje de modelado con servicios relacionados con la modularización y la escalabilidad. Específicamente, los patrones permiten definir estrategias de fragmentación de modelos, reglas de alcance y visibilidad, servicios de indexación de modelos y restricciones de alcance. Una vez que los patrones se han aplicado al meta-modelo de un lenguaje de modelado, se puede generar automáticamente un entorno de modelado personalizado enriquecido con los servicios definidos, que se vuelven aplicables tanto a los modelos monolíticos existentes, como a los nuevos modelos. Una segunda contribución de esta tesis es la propuesta de conceptos y tecnologías para facilitar la creación de editores gráficos. Para ello, definimos heurísticas que identifican estructuras en la sintaxis abstracta de los DSMLs y asignan automáticamente su representación en el diagrama. Usando este enfoque, los desarrolladores pueden crear una representación gráfica por defecto a partir de un meta-modelo. Estas contribuciones se implementaron en dos plug-ins de Eclipse llamados EMFSplitter y EMF-Stencil. Por un lado, EMF-Splitter implementa el catálogo de patrones y, por otro lado, EMF-Stencil implementa las heurísticas y la generación de un entorno de modelado gráfico. Ambas herramientas se han evaluado con diferentes casos de estudio para demostrar su versatilidad, eficiencia y capacidade

Agile Manifesto and Practices Selection for Tailoring Software Development: A Systematic Literature Review

peer reviewedAgile methods have been largely used for many years to provide developers with a flexible software development process leading to software quality improvement. To get the best results and eliminate unnecessary efforts, the development team should select the most appropriate methods and techniques. The fundamental core of an agile method has to be well-understood before deciding which parts of the method need to be adopted. We believe that the quickest way to do so is to understand the prescripts of the Agile Manifesto. Many researches have proposed different tailoring approaches based on the relation and straight-forward interpretation between each agile practice and agile values or principles. We however have observed that agile practitioners do not dedicate the necessary attention to the Agile Manifesto before adopting agile methods or practices and directly use them. It is because the importance of Agile Manifesto in tailoring context is not obvious enough to the community. This study aims at doing a systematic literature review on the existing case studies, to verify the relation between the Agile Manifesto and agile practice selection

Occam's Razor For Big Data?

Detecting quality in large unstructured datasets requires capacities far beyond the limits of human perception and communicability and, as a result, there is an emerging trend towards increasingly complex analytic solutions in data science to cope with this problem. This new trend towards analytic complexity represents a severe challenge for the principle of parsimony (Occam’s razor) in science. This review article combines insight from various domains such as physics, computational science, data engineering, and cognitive science to review the specific properties of big data. Problems for detecting data quality without losing the principle of parsimony are then highlighted on the basis of specific examples. Computational building block approaches for data clustering can help to deal with large unstructured datasets in minimized computation time, and meaning can be extracted rapidly from large sets of unstructured image or video data parsimoniously through relatively simple unsupervised machine learning algorithms. Why we still massively lack in expertise for exploiting big data wisely to extract relevant information for specific tasks, recognize patterns and generate new information, or simply store and further process large amounts of sensor data is then reviewed, and examples illustrating why we need subjective views and pragmatic methods to analyze big data contents are brought forward. The review concludes on how cultural differences between East and West are likely to affect the course of big data analytics, and the development of increasingly autonomous artificial intelligence (AI) aimed at coping with the big data deluge in the near future. Keywords: big data; non-dimensionality; applied data science; paradigm shift; artificial intelligence; principle of parsimony (Occam’s razor