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Los sistemas de registro y de reporte de datos son de gran interés, puesto que respaldan la reproducibilidad y transparencia científica. La investigación actual genera una gran cantidad de datos que ya no se pueden documentar utilizando cuadernos de laboratorio de papel (CLP). Los cuadernos electrónicos de laboratorio (CEL) podrían ser una solu-ción prometedora para reemplazar los CLP y promover la reproducibilidad científica y su transparencia. Anteriormente analizamos cinco CEL y realizamos dos encuestas para implementar un CEL en un instituto de investigación biomédica. Entre los CEL proba-dos, encontramos que Microsoft OneNote presenta numerosas características relacio-nadas con las mejores funcionalidades del CEL. Además, ambos grupos encuestados prefirieron OneNote sobre un CEL científico (Elements de PerkinElmer). Sin embargo, OneNote es una aplicación general para tomar notas que no ha sido diseñada para fi-nes científicos. Por lo tanto, en este trabajo proporcionamos varias pautas para adaptar OneNote a un flujo de trabajo experimental.

Organizations around the world require a sound process of change management to innovate and remain competitive over time. Change and knowledge management needs to be supported with the right tools to overcome the challenges of transformations and transitions in the business models and processes of diverse organizations. Steering boards can use enterprise architecture (EA) to implement new knowledge management initiatives in their strategic planning. EA allows companies to model the current situation (as-is models) of the organization and the desired future scenarios (to-be models) and to establish road maps to enable adequate transformations. Different frameworks exist in the market that support the management of organizations, for example: Control Objectives for Information and Related Technologies (COBIT), Information Technology Infrastructure Library (ITIL), quality models such as the one proposed by the European Foundation for Quality Management (EFQM) and systems such as the Balanced Scorecard (BSC) are widely used for the management of business and information technologies (IT). However, EA is not widely used with the other mentioned tools. This paper analyzes EA as a tool for change and knowledge management and compares its functionality with other frameworks in the market. The analysis performed in this paper checks if EA can be used and is compatible with other frameworks. To answer this question, an analysis of the most important processes, good practices, perspectives and tools provided by each framework was performed. Las organizaciones de todo el mundo requieren un proceso sólido de gestión del cambio para innovar y seguir siendo competitivas a lo largo del tiempo. La gestión del cambio y del conocimiento debe ser respaldada con las herramientas adecuadas para superar los desafíos de las transformaciones y transiciones en los modelos y procesos de negocios de diversas organizaciones. Las juntas directivas pueden utilizar la arquitectura empresarial (AE) para implementar nuevas iniciativas de gestión del conocimiento en su planificación estratégica. AE permite a las empresas modelar la situación actual de la organización y los escenarios futuros deseados y establecer mapas de ruta para permitir las transformaciones adecuadas. Existen diferentes marcos de trabajo que apoyan la gestión, por ejemplo: Objetivos de control para información y tecnologías relacionadas (COBIT, por su sigla en inglés), Biblioteca de infraestructura de tecnología de la información (ITIL, por su sigla en inglés), modelos de calidad como el de la Fundación Europea para la Gestión de la Calidad (EFQM, por su sigla en inglés) y sistemas como el Cuadro de mando Integral (BSC, por su sigla en inglés). Sin embargo, la AE no es muy utilizada junto con las herramientas mencionadas. Este documento analiza AE como una herramienta para el cambio y la gestión del conocimiento y compara su funcionalidad con otros marcos en el mercado. El análisis realizado en este documento comprueba si se puede utilizar AE y es compatible con otros marcos de trabajo para gestionar el cambio organizativo y la gestión del conocimiento.

Advances in science and technology, the Internet of Things, and the proliferation of mobile apps are critical factors to the current increase in the amount, structure, and size of information that organizations have to store, process, and analyze. Traditional data storages present technical deficiencies when handling huge volumes of data and are not adequate for process modeling and business intelligence; to cope with these deficiencies, new methods and technologies have been developed under the umbrella of big data. However, there is still the need in higher education institutions (HEIs) of a technological tool that can be used for big data processing and knowledge management (KM). To overcome this issue, it is essential to develop an information infrastructure that allows the capturing of knowledge and facilitates experimentation by having cleaned and consistent data. Thus, this paper presents a hybrid information infrastructure for business intelligence and analytics (BI&A) and KM based on an educational data warehouse (EDW) and an enterprise architecture (EA) repository that allows the digitization of knowledge and empowers the visualization and the analysis of dissimilar organizational components as people, processes, and technology. The proposed infrastructure was created based on research and will serve to run different experiments to analyze educational data and academic processes and for the creation of explicit knowledge using different algorithms and methods of educational data mining, learning analytics, online analytical processing (OLAP), and EA analytics.

Cloud computing services are nowadays advertised as an emerging business model. Moreover, these services bring innovative solutions in a more sophisticated competitive market. But, the decision for their adoption could be significantly reduced due to organizations’ concerns related to security, privacy, and trust. The challenge involves such questions as where to start, which provider should the company choose or whether it is even worthwhile. Thus, this paper proposes an improved unified framework, based on a previous study where a 6 step process framework was introduced. This improved framework add one new step for security and control after the migration process. At the end, a 7 processes framework is proposed aimed to fulfill organizations’ concerns when decide to adopt cloud computing services with a follow-up step. This additional step intends to help IT directors to make sure everything is working properly in a methodological way, in order to achieve a successful cloud computing migration process. An effective solution that is gaining momentum and popularity for competitive organizations.&nbsp

Cloud computing adoption has represented a big challenge for all kinds of companies all over the world. The challenge involves such questions as where to start, which provider should the company choose or whether it is even worthwhile. With a constantly changing economic environment, businesses must assess current technologies and offerings to remain competitive. The possibility of migrating a company's services and infrastructure to the cloud may seem attractive. However, without proper guidance, the results may not be as expected, leading a loss of time and money. As each company has its own needs and requirements, industry-focused frameworks have been proposed (e.g. for educational or governmental institutions). Although these frameworks are useful, they are not applicable to every business. Hence, a generic, widely-applicable and implementable cloud computing adoption framework is proposed in this paper. It takes the best outcomes of previous studies, best-practice suggestions, as well as authors' additions, and sums them up into a more robust, unified framework. The framework consists of 6 detailed phases carrying the user from knowing the company's current state to successfully migrating the data, services, and infrastructure to the cloud. These steps are intended to help IT directors and other decision-makers to reduce risks and maximize benefits throughout the cloud computing adoption process. Data security risks are not discussed in this paper as other authors have already sufficiently studied them. This framework was developed from a business perspective.

This study shows the influence of Cl−, SO4 2−, NO3 −, SiO3 2−, Na+, and Ca2+ on arsenate removal by anion exchanger polymers using the liquid-phase polymer-based retention (LPR) technique. The LPR was carried out in the presence of anion exchanger soluble polymers containing quaternary ammonium salts. These polymers were characterized by NMR. Compared with As(V) removal from deionized water, the results showed that in the presence of ionic mixture, the As(V) removal capacity decreased. However, P(ClVBTA) showed As(V) removal ability of 91 % when the ionic mixture was used. Polymers with chloride exchanger groups showed a higher ability to remove arsenate than the polymer that contains methyl sulfate as anion exchanger group. At higher arsenate concentration (47.6 mg L−1), arsenate retention by the water-soluble polymers ranged between 58 and 91 %. This removal capacity increased gradually reaching 100 % retention when the arsenate concentration in the cell was minimum (5.5 mg L−1). The values of maximum retention capacity were 264 mg g−1 for P(ClMPTA), 260 mg g−1 for P(ClVBTA), and 200 mg g−1 for P(ClAPTA) at the total filtrate volume of 300 mL. The charge–discharge process found to be suitable for saturate the polymer with As(V) and then eluting As(V) for regenerating the extracting capacity of polymer.

The synthesis and sorption performance of As(V) with a copolymer resin is presented. The resin was obtained via the radical polymerization of a 1:1 mixture of N-(4-vinyl benzyl)-N-methyl-D-glucamine and (4-vinyl benzyl)trimethyl ammonium chloride using N,N-methylene-bis-acrylamide as the crosslinker. The effect of pH, concentration, and time on the arsenic sorption was studied. The copolymer exhibited good performance over a wide pH range regardless of the initial concentrations. The equilibrium experiments presented better results under alkaline conditions (pH 9.0) compared with acidic conditions (pH 3.0). The kinetic sorption was quite fast, particularly at low arsenic concentrations. In addition, the arsenic anions were eluted with different acid/alkaline reagents, and the acid eluents exhibited the best results. © 2013 American Institute of Chemical Engineers Environ Prog, 33: 1187–1193, 2014