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BACKGROUND: During recent years, X-ray microtomography (micro-CT) has seen an increasing use in biological research areas, such as functional morphology, taxonomy, evolutionary biology and developmental research. Micro-CT is a technology which uses X-rays to create sub-micron resolution images of external and internal features of specimens. These images can then be rendered in a three-dimensional space and used for qualitative and quantitative 3D analyses. However, the online exploration and dissemination of micro-CT datasets are rarely made available to the public due to their large size and a lack of dedicated online platforms for the interactive manipulation of 3D data. Here, the development of a virtual micro-CT laboratory (Micro-CTvlab) is described, which can be used by everyone who is interested in digitisation methods and biological collections and aims at making the micro-CT data exploration of natural history specimens freely available over the internet. NEW INFORMATION: The Micro-CTvlab offers to the user virtual image galleries of various taxa which can be displayed and downloaded through a web application. With a few clicks, accurate, detailed and three-dimensional models of species can be studied and virtually dissected without destroying the actual specimen. The data and functions of the Micro-CTvlab can be accessed either on a normal computer or through a dedicated version for mobile devices.
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BACKGROUND: Parallel data manipulation using R has previously been addressed by members of the R community, however most of these studies produce ad hoc solutions that are not readily available to the average R user. Our targeted users, ranging from the expert ecologist/microbiologists to computational biologists, often experience difficulties in finding optimal ways to exploit the full capacity of their computational resources. In addition, improving performance of commonly used R scripts becomes increasingly difficult especially with large datasets. Furthermore, the implementations described here can be of significant interest to expert bioinformaticians or R developers. Therefore, our goals can be summarized as: (i) description of a complete methodology for the analysis of large datasets by combining capabilities of diverse R packages, (ii) presentation of their application through a virtual R laboratory (RvLab) that makes execution of complex functions and visualization of results easy and readily available to the end-user. NEW INFORMATION: In this paper, the novelty stems from implementations of parallel methodologies which rely on the processing of data on different levels of abstraction and the availability of these processes through an integrated portal. Parallel implementation R packages, such as the pbdMPI (Programming with Big Data - Interface to MPI) package, are used to implement Single Program Multiple Data (SPMD) parallelization on primitive mathematical operations, allowing for interplay with functions of the vegan package. The dplyr and RPostgreSQL R packages are further integrated offering connections to dataframe like objects (databases) as secondary storage solutions whenever memory demands exceed available RAM resources. The RvLab is running on a PC cluster, using version 3.1.2 (2014-10-31) on a x86_64-pc-linux-gnu (64-bit) platform, and offers an intuitive virtual environmet interface enabling users to perform analysis of ecological and microbial communities based on optimized vegan functions. A beta version of the RvLab is available after registration at: https://portal.lifewatchgreece.eu/.
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BACKGROUND: Biodiversity data is characterized by its cross-disciplinary character, the extremely broad range of data types and structures, and the variety of semantic concepts that it encompasses. Furthermore there is a plethora of different data sources providing resources for the same piece of information in a heterogeneous way. Even if we restrict our attention to Greek biodiversity domain, it is easy to see that biodiversity data remains unconnected and widely distributed among different sources. NEW INFORMATION: To cope with these issues, in the context of the LifeWatch Greece project, i) we supported cataloguing and publishing of all the relevant metadata information of the Greek biodiversity domain, ii) we integrated data from heterogeneous sources by supporting the definitions of appropriate models, iii) we provided means for efficiently discovering biodiversity data of interest and iv) we enabled the answering of complex queries that could not be answered from the individual sources. This work has been exploited, evaluated and scientificaly confirmed by the biodiversity community through the services provided by the LifeWatch Greece portal.
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BACKGROUND: Biodiversity data is characterized by its cross-disciplinary character, the extremely broad range of data types and structures, and the plethora of different data sources providing resources for the same piece of information in a heterogeneous way. Since the web inception two decades ago, there are multiple initiatives to connect, aggregate, share, and publish biodiversity data, and to establish data and work flows in order to analyze them. The European program LifeWatch aims at establishing a distributed network of nodes implementing virtual research environment in Europe to facilitate the work of biodiversity researchers and managers. LifeWatchGreece is one of these nodes where a portal was developed offering access to a suite of virtual laboratories and e-services. NEW INFORMATION: Despite its strict definition in information technology, in practice "portal" is a fairly broad term that embraces many web architectures. In the biodiversity domain, the term "portal" is usually used to indicate either a web site that provides access to a single or an aggregation of data repositories (like: http://indiabiodiversity.org/, http://www.mountainbiodiversity.org/, http://data.freshwaterbiodiversity.eu), a web site that gathers information about various online biodiversity tools (like http://test-eubon.ebd.csic.es/, http://marine.lifewatch.eu/) or a web site that just gathers information and news about the biodiversity domain (like http://chm.moew.government.bg). LifeWatchGreece's portal takes the concept of a portal a step further. In strict IT terms, LifeWatchGreece's portal is partly a portal, partly a platform and partly an aggregator. It includes a number of biodiversity-related web tools integrated into a centrally-controlled software ecosystem. This ecosystem includes subsystems for access control, traffic monitoring, user notifications and web tool management. These subsystems are shared to all the web tools that have been integrated to the portal and thereby are part of this ecosystem. These web tools do not consist in external and completely independent web applications as it happens in most other portals. A quite obvious (to the user) indication of this is the Single-Sign-On (SSO) functionality for all tools and the common user interface wrapper that most of these tools use. Another example of a less obvious functionality is the common user profile that is shared and can be utilized by all tools (e.g user's timezone).
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BACKGROUND: A large percentage of scientific data with tabular structure are published on the Web of Data as interlinked RDF datasets. When we come to the issue of long-term preservation of such RDF-based digital objects, it is important to provide full support for reusing them in the future. In particular, it should include means for both players who have no familiarity with RDF data model and, at the same time, who by working only with the native format of the data still provide sufficient information. To achieve this, we need mechanisms to bring the data back to their original format and structure. NEW INFORMATION: In this paper, we investigate how to perform the reverse process for column-based data sources. In particular, we devise an algorithm, RML2CSV, and exemplify its implementation in transforming an RDF dataset into its CSV tabular structure, through the use of the same RML mapping document that was used to generate the set of RDF triples. Through a set of content-based criteria, we attempt a comparative evaluation to measure the similarity between the rebuilt CSV and the original one. The results are promising and show that, under certain assumptions, RML2CSV reconstructs the same data with the same structure, offering more advanced digital preservation services.
