Serviço de intercâmbio de material bibliográfico da Biblioteca da Câmara dos Deputados : uma proposta de melhoria que contemple a arquitetura da informação

Proposta de melhoria do Serviço de Intercâmbio da Biblioteca da Câmara dos Deputados a partir da adoção de um novo modelo balizado pela Arquitetura da Informação e que contemple os recursos tecnológicos atualmente disponíveis. Dentre as justificativas para esta proposta estão a necessidade de modernização para manutenção do serviço, um dos pilares do desenvolvimento de coleções; e o alinhamento deste serviço ao comportamento do usuário pela busca de informação, que vem mudando após o advento da internet. A pesquisa é do tipo exploratória que apresenta a revisão de literatura como base para a fundamentação teórica, na qual são discutidos os aspectos teóricos do desenvolvimento de coleções na modalidade de aquisição por doação, realizada por meio do serviço de intercâmbio entre as bibliotecas. No procedimento metodológico foi feito um estudo no Serviço de Intercâmbio da Biblioteca da Câmara dos Deputados para obter os dados estatísticos que quantificam essa atividade. Foi elaborado um questionário, e enviado as 14 bibliotecas da Rede RVBI para conhecer o funcionamento do serviço de intercâmbio em cada uma delas. Com base nas respostas advindas do questionário foi sugerida a criação de um catálogo coletivo de acesso público via web, nos moldes do Portal Estante Virtual, para centralizar e gerenciar as atividades de intercâmbio de publicações. Os objetivos do catálogo são centralizar as informações e substituir um serviço pouco automatizado nas bibliotecas, outros objetivos do catálogo são agilizar a troca de publicações entre bibliotecas, propiciar economia de espaço, de recursos humanos e financeiros ao otimizar as rotinas e promover a democratização das listas de doações para um número maior de bibliotecas.

Statistics of Turbulence in Benthal Boundary Layers

This paper deals with turbulence behavior inbenthalboundarylayers by means of large eddy simulation (LES). The flow is modeled by moving an infinite plate in an otherwise quiescent water with an oscillatory and a steady velocity components. The oscillatory one aims to simulate wave effect on the flow. A number of large-scale turbulence databases have been established, based on which we have obtained turbulencestatisticsof the boundarylayers, such as Reynolds stress, turbulence intensity, skewness and flatness ofturbulence, and temporal and spatial scales of turbulent bursts, etc. Particular attention is paid to the dependences of those statistics on two nondimensional parameters, namely the Reynolds number and the current-wave velocity ratio defined as the steady current velocity over the oscillatory velocity amplitude. It is found that the Reynolds stress and turbulence intensity profile differently from phase to phase, and exhibit two types of distributions in an oscillatory cycle. One is monotonic occurring during the time when current and wave-induced components are in the same direction, and the other inflectional occurring during the time when current and wave-induced components are in opposite directions. Current component makes an asymmetrical time series of Reynolds stress, as well as turbulence intensity, although the mean velocity series is symmetrical as a sine/cosine function. The skewness and flatness variations suggest that the turbulence distribution is not a normal function but approaches to a normal one with the increasing of Reynolds number and the current-wave velocity ratio as well. As for turbulent bursting, the dimensionless period and the mean area of all bursts per unit bed area tend to increase with Reynolds number and current-wave velocity ratio, rather than being constant as in steady channel flows.

User’s Guide to ADMB2R: A Set of AD Model Builder Output Routines Compatible with the R Statistics Language

ADMB2R is a collection of AD Model Builder routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 ADMB2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the ADMB2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer ADMB2R to others in the hope that they will find it useful. (PDF contains 30 pages)

User’s Guide to C2R: A Set of C Language Output Routines Compatible with the R Statistics Language

C2R is a collection of C routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 C2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the C2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer C2R to others in the hope that they will find it useful. (PDF contains 27 pages)

User’s Guide to For2R: A Module of Fortran 95 Output Routines Compatible with the R Statistics Language

For2R is a collection of Fortran routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 For2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the For2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer For2R to others in the hope that they will find it useful. (PDF contains 31 pages)

Blackburn College: DIY! College departments catalogue their own technologies on Library Management System for loan

Blackburn College is making use of its Heritage Library Management System (LMS) for a wide variety of loans beyond that of books; this has enabled them to better manage the growing numbers and types of technologies that are being used in teaching and learning. In an additional pilot development, they have taken the bold step of training college departments in cataloguing their own technologies to add to the LMS for loan. This has enabled the departments to keep track of their own equipment easily, and provided a more consistent approach to equipment loan within the College.

Good practice guidance for library and information professionals - moving towards accessible e-book platforms

Good practice guidance for publishers and procurers of e-book platforms based on the benefits and barriers identified by robust testing using real people with disabilities

Authority files: Breaking out of the library silo to become signposts for research information

Authority files serve to uniquely identify real world ‘things’ or entities like documents, persons, organisations, and their properties, like relations and features. Already important in the classical library world, authority files are indispensable for adequate information retrieval and analysis in the computer age. This is because, even more than humans, computers are poor at handling ambiguity. Through authority files, people tell computers which terms, names or numbers refer to the same thing or have the same meaning by giving equivalent notions the same identifier. Thus, authority files signpost the internet where these identifiers are interlinked on the basis of relevance. When executing a query, computers are able to navigate from identifier to identifier by following these links and collect the queried information on these so-called ‘crosswalks’. In this context, identifiers also go under the name controlled access points. Identifiers become even more crucial now massive data collections like library catalogues or research datasets are releasing their till-now contained data directly to the internet. This development is coined Open Linked Data. The concatenating name for the internet is Web of Data instead of the classical Web of Documents.

KE Useage Statistics Guidelines

A Knowledge Exchange workshop took place in March 2010 to bring together technical experts working in partner projects collecting usage statistics including PIRUS2, OAstatistik and SURFsure projects. Experts from other related projects (RePec and NeeO) were also involved. Following the workshop, experts came to the conclusion that it would be valuable for institutions in all four Knowledge Exchange partner countries as well as countries outside of KE, to have an agreed set of guidelines which could be used when collecting and comparing data on usage statistics. This work connects with work already planned in projects already funded in three of the countries. Together they have set up a set of guidelines which will be tested and refined by Autumn 2010. An element in these guidelines is an agreed robotlist. This list extends on the COUNTER list of robots which should be excluded when counting downloads.

Combined useage statistics as a basis for Research intelligence

Knowledge Exchange hosted a workshop in March 2010 with the aim to bring together technical experts working in partner projects collecting usage statistics including PIRUS2, OAstatistik and SURFsure projects. Experts from other related projects (RePec and NeeO) were also involved. The workshop produced a briefing paper on combined usage statistics as a basis for research intelligence. In this paper, the experts make a cause for collecting and exchanging usage statistics as this can provide valuable insight in how research is being used, not only by the research community, but also by business and society in general. This would provide a basis for 'Research Intelligence', an intelligent use of reliable numerical data which can be used as a basis for decision making in higher education and research. Usage statistics are a clear example of data which can offer a valuable contribution to the information required to make informed decisions. To allow for the meaningful collection, exchange and analysis of usage statistics, a number of challenges and opportunities need to be addressed and further steps need to be taken.