Open Access Accredited Journals in South Africa: they do exist

Over the last few months I have been working with a digital deluge of spreadsheets and data. The purpose of this work was to put together a list of the accredited open access journals published in South Africa. By open access, I mean journals that are free to view and/or download and have an open license, usually a creative commons license. I also looked for those accredited journals which are available for users to read freely, but don't have an open license (in this case the publisher usually keeps the copyright and re-use is not allowed without permission from them)

Legal interoperability: making Open Government Data compatible with businesses and communities

Legal interoperability could be defined as the possibility of legally mixing data coming from different sources (including governmental data, data generated by online communities and data held by private parties). Legal interoperability is similar to technical interoperability, since it is a prerequisite for mixing data and create new knowledge or services. But it also has its own peculiarities, for instance because it could be achieved simply choosing the appropriate licensing scheme, but also because self-help mechanisms which could - at a certain price - guarantee technical interoperability to third parties cannot (lawfully) solve legal interoperability issues. In the mid/long run, legal interoperability could be achieved thorough the evolution of legal frameworks in order to harmonize the landscape of Government Data. In the short term, the shortcomings generated by diversified legal frameworks may be alleviated through the careful choice of copyright licenses. The presentation will focus on the latter aspects, discussing existing public licenses (such as the Creative Commons and Open Data Commons ones), representing a de facto standard in this domain, and the main open data licenses developed by European governments (e.g. the Open Government Licenses in the UK, the French License Ouverte or the Italian Open Data License

Lego Project Data: An Open Data Archive for Qualitative Video Research

This article introduces and documents the collection and processing of raw video and audio recordings of an experimental Lego puzzle team game, which led to the archiving of the audio-visual data and ancillary materials in an open format suitable for sharing and reuse. The primary motivation was for the data to be included in demonstration packages for immersive qualitative analysis and transcription software tools that work natively with 360-degree video data. The data is made available in an open data archive with a Creative Commons license

Correction to: Measured PET Data Characterization with the Negative Binomial Distribution Model

The article "Measured PET Data Characterization with the Negative Binomial Distribution Model", written by Maria Filomena Santarelli, Vincenzo Positano, Luigi Landini was originally published Online First without open access. After publication in volume [37], issue [3], page [299-312] the author decided to opt for Open Choice and to make the article an open access publication. Therefore, the copyright of the article has been changed to © The Author(s) [2018] and the article is forthwith distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made

Leaf venation networks of Bornean trees: images and hand-traced segmentations.

The data set contains images of leaf venation networks obtained from tree species in Malaysian Borneo. The data set contains 726 leaves from 295 species comprising 50 families, sampled from eight forest plots in Sabah. Image extents are approximately 1 × 1 cm, or 50 megapixels. All images contain a region of interest in which all veins have been hand traced. The complete data set includes over 30 billion pixels, of which more than 600 million have been validated by hand tracing. These images are suitable for morphological characterization of these species, as well as for training of machine-learning algorithms that segment biological networks from images. Data are made available under the Open Data Commons Attribution License. You are free to copy, distribute, and use the database; to produce works from the database; and to modify, transform, and build upon the database. You must attribute any public use of the database, or works produced from the database, in the manner specified in the license. For any use or redistribution of the database, or works produced from it, you must make clear to others the license of the database and keep intact any notices on the original database

Selected papers from the 16th Annual Bio-Ontologies Special Interest Group Meeting

Copyright @ 2014 Soldatova et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Over the 16 years, the Bio-Ontologies SIG at ISMB has provided a forum for vibrant discussions of the latest and most innovative advances in the research area of bio-ontologies, its applications to biomedicine and more generally in the organisation, sharing and re-use of knowledge in biomedicine and the life sciences. The six papers selected for this supplement span a wide range of topics including: ontology-based data integration, ontology-based annotation of scientific literature, ontology and data model development, representation of scientific results and gene candidate prediction

Measuring organisational readiness for patient engagement (MORE) : an international online Delphi consensus study

Date of Acceptance: 28/01/2015. © 2015 Oostendorp et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise statedWidespread implementation of patient engagement by organisations and clinical teams is not a reality yet. The aim of this study is to develop a measure of organisational readiness for patient engagement designed to monitor and facilitate a healthcare organisation’s willingness and ability to effectively implement patient engagement in healthcarePeer reviewedFinal Published versio

Diffusion of bedload particles in open-channel flows : distribution of travel times and second-order statistics of particle trajectories

Acknowledgments The authors are grateful to the reviewers for thorough reviews, constructive comments and useful suggestions that have been gratefully incorporated in the final manuscript. Funding for this research was provided in part by the Institute of Geophysics of the Polish Academy of Sciences through the Project for Young Scientists No. 16/IGF PAN/2011/Mł ‘‘Dynamics and topography of riverbed forms: an analysis of experimental data and modelling of sediment transport in the light of Einstein’s theory’’, by Ministry of Sciences and Higher Education within statutory activities No. 3841/E-41/S/2015, and by EPSRC, UK (EP/G056404/1) within the project ‘‘High-resolution numerical and experimental studies of turbulence-induced sediment erosion and near-bed transport.’’ Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Peer reviewedPublisher PD

Open Data, Open Source and Open Standards in chemistry: The Blue Obelisk five years on

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background The Blue Obelisk movement was established in 2005 as a response to the lack of Open Data, Open Standards and Open Source (ODOSOS) in chemistry. It aims to make it easier to carry out chemistry research by promoting interoperability between chemistry software, encouraging cooperation between Open Source developers, and developing community resources and Open Standards. Results This contribution looks back on the work carried out by the Blue Obelisk in the past 5 years and surveys progress and remaining challenges in the areas of Open Data, Open Standards, and Open Source in chemistry. Conclusions We show that the Blue Obelisk has been very successful in bringing together researchers and developers with common interests in ODOSOS, leading to development of many useful resources freely available to the chemistry community.Peer Reviewe

Visualization of Big Data Text Analytics in Financial Industry: A Case Study of Topic Extraction for Italian Banks

Textual data and analysis can derive new insights and bring valuable business insights. These insights can be further leveraged by making better future business decisions. Sources that are used for text analysis in financial industry vary from internal word documents, email to external sources like social media, websites or open data. The system described in this paper will utilize data from social media (Twitter) and tweets related to Italian banks, in Italian. This system is based on open source tools (R language) and topic extraction model was created to gather valuable information. This paper describes methods used for data ingestion, modelling, visualizations of results and insights. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p