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Towards mainstreaming of biodiversity data publishing: recommendations of the GBIF Data Publishing Framework Task Group  [cached]
Moritz Tom,Krishnan S,Roberts Dave,Ingwersen Peter
BMC Bioinformatics , 2011, DOI: 10.1186/1471-2105-12-s15-s1
Abstract: Background Data are the evidentiary basis for scientific hypotheses, analyses and publication, for policy formation and for decision-making. They are essential to the evaluation and testing of results by peer scientists both present and future. There is broad consensus in the scientific and conservation communities that data should be freely, openly available in a sustained, persistent and secure way, and thus standards for 'free' and 'open' access to data have become well developed in recent years. The question of effective access to data remains highly problematic. Discussion Specifically with respect to scientific publishing, the ability to critically evaluate a published scientific hypothesis or scientific report is contingent on the examination, analysis, evaluation - and if feasible - on the re-generation of data on which conclusions are based. It is not coincidental that in the recent 'climategate' controversies, the quality and integrity of data and their analytical treatment were central to the debate. There is recent evidence that even when scientific data are requested for evaluation they may not be available. The history of dissemination of scientific results has been marked by paradigm shifts driven by the emergence of new technologies. In recent decades, the advance of computer-based technology linked to global communications networks has created the potential for broader and more consistent dissemination of scientific information and data. Yet, in this digital era, scientists and conservationists, organizations and institutions have often been slow to make data available. Community studies suggest that the withholding of data can be attributed to a lack of awareness, to a lack of technical capacity, to concerns that data should be withheld for reasons of perceived personal or organizational self interest, or to lack of adequate mechanisms for attribution. Conclusions There is a clear need for institutionalization of a 'data publishing framework' that can address sociocultural, technical-infrastructural, policy, political and legal constraints, as well as addressing issues of sustainability and financial support. To address these aspects of a data publishing framework - a systematic, standard approach to the formal definition and public disclosure of data - in the context of biodiversity data, the Global Biodiversity Information Facility (GBIF, the single inter-governmental body most clearly mandated to undertake such an effort) convened a Data Publishing Framework Task Group. We conceive this data publishing framework as an envir
Indicators for the Data Usage Index (DUI): an incentive for publishing primary biodiversity data through global information infrastructure  [cached]
Ingwersen Peter,Chavan Vishwas
BMC Bioinformatics , 2011, DOI: 10.1186/1471-2105-12-s15-s3
Abstract: Background A professional recognition mechanism is required to encourage expedited publishing of an adequate volume of 'fit-for-use' biodiversity data. As a component of such a recognition mechanism, we propose the development of the Data Usage Index (DUI) to demonstrate to data publishers that their efforts of creating biodiversity datasets have impact by being accessed and used by a wide spectrum of user communities. Discussion We propose and give examples of a range of 14 absolute and normalized biodiversity dataset usage indicators for the development of a DUI based on search events and dataset download instances. The DUI is proposed to include relative as well as species profile weighted comparative indicators. Conclusions We believe that in addition to the recognition to the data publisher and all players involved in the data life cycle, a DUI will also provide much needed yet novel insight into how users use primary biodiversity data. A DUI consisting of a range of usage indicators obtained from the GBIF network and other relevant access points is within reach. The usage of biodiversity datasets leads to the development of a family of indicators in line with well known citation-based measurements of recognition.
Engaging the broader community in biodiversity research: the concept of the COMBER pilot project for divers in ViBRANT  [cached]
Christos Arvanitidis,Sarah Faulwetter,Georgios Chatzigeorgiou,Lyubomir Penev
ZooKeys , 2011, DOI: 10.3897/zookeys.150.2149
Abstract: This paper discusses the design and implementation of a citizen science pilot project, COMBER (Citizens’ Network for the Observation of Marine BiodivERsity, http://www.comber.hcmr.gr), which has been initiated under the ViBRANT EU e-infrastructure. It is designed and implemented for divers and snorkelers who are interested in participating in marine biodiversity citizen science projects. It shows the necessity of engaging the broader community in the marine biodiversity monitoring and research projects, networks and initiatives. It analyses the stakeholders, the industry and the relevant markets involved in diving activities and their potential to sustain these activities. The principles, including data policy and rewards for the participating divers through their own data, upon which this project is based are thoroughly discussed. The results of the users analysis and lessons learned so far are presented. Future plans include promotion, links with citizen science web developments, data publishing tools, and development of new scientific hypotheses to be tested by the data collected so far.
The Biodiversity Informatics Potential Index  [cached]
Ari?o Arturo H,Chavan Vishwas,King Nick
BMC Bioinformatics , 2011, DOI: 10.1186/1471-2105-12-s15-s4
Abstract: Background Biodiversity informatics is a relatively new discipline extending computer science in the context of biodiversity data, and its development to date has not been uniform throughout the world. Digitizing effort and capacity building are costly, and ways should be found to prioritize them rationally. The proposed 'Biodiversity Informatics Potential (BIP) Index' seeks to fulfill such a prioritization role. We propose that the potential for biodiversity informatics be assessed through three concepts: (a) the intrinsic biodiversity potential (the biological richness or ecological diversity) of a country; (b) the capacity of the country to generate biodiversity data records; and (c) the availability of technical infrastructure in a country for managing and publishing such records. Methods Broadly, the techniques used to construct the BIP Index were rank correlation, multiple regression analysis, principal components analysis and optimization by linear programming. We built the BIP Index by finding a parsimonious set of country-level human, economic and environmental variables that best predicted the availability of primary biodiversity data accessible through the Global Biodiversity Information Facility (GBIF) network, and constructing an optimized model with these variables. The model was then applied to all countries for which sufficient data existed, to obtain a score for each country. Countries were ranked according to that score. Results Many of the current GBIF participants ranked highly in the BIP Index, although some of them seemed not to have realized their biodiversity informatics potential. The BIP Index attributed low ranking to most non-participant countries; however, a few of them scored highly, suggesting that these would be high-return new participants if encouraged to contribute towards the GBIF mission of free and open access to biodiversity data. Conclusions The BIP Index could potentially help in (a) identifying countries most likely to contribute to filling gaps in digitized biodiversity data; (b) assisting countries potentially in need (for example mega-diverse) to mobilize resources and collect data that could be used in decision-making; and (c) allowing identification of which biodiversity informatics-resourced countries could afford to assist countries lacking in biodiversity informatics capacity, and which data-rich countries should benefit most from such help.
Scratchpads: a data-publishing framework to build, share and manage information on the diversity of life  [PDF]
Smith Vincent S,Rycroft Simon D,Harman Kehan T,Scott Ben
BMC Bioinformatics , 2009, DOI: 10.1186/1471-2105-10-s14-s6
Abstract: Background Natural History science is characterised by a single immense goal (to document, describe and synthesise all facets pertaining to the diversity of life) that can only be addressed through a seemingly infinite series of smaller studies. The discipline's failure to meaningfully connect these small studies with natural history's goal has made it hard to demonstrate the value of natural history to a wider scientific community. Digital technologies provide the means to bridge this gap. Results We describe the system architecture and template design of "Scratchpads", a data-publishing framework for groups of people to create their own social networks supporting natural history science. Scratchpads cater to the particular needs of individual research communities through a common database and system architecture. This is flexible and scalable enough to support multiple networks, each with its own choice of features, visual design, and constituent data. Our data model supports web services on standardised data elements that might be used by related initiatives such as GBIF and the Encyclopedia of Life. A Scratchpad allows users to organise data around user-defined or imported ontologies, including biological classifications. Automated semantic annotation and indexing is applied to all content, allowing users to navigate intuitively and curate diverse biological data, including content drawn from third party resources. A system of archiving citable pages allows stable referencing with unique identifiers and provides credit to contributors through normal citation processes. Conclusion Our framework http://scratchpads.eu/ currently serves more than 1,100 registered users across 100 sites, spanning academic, amateur and citizen-science audiences. These users have generated more than 130,000 nodes of content in the first two years of use. The template of our architecture may serve as a model to other research communities developing data publishing frameworks outside biodiversity research.
A framework for publishing primary biodiversity data  [cached]
Roberts Dave,Moritz Tom
BMC Bioinformatics , 2011, DOI: 10.1186/1471-2105-12-s15-i1
Abstract:
Data sharing and publishing in the field of neuroimaging
Janis L Breeze, Jean-Baptiste Poline, David N Kennedy
GigaScience , 2012, DOI: 10.1186/2047-217x-1-9
Abstract: One crucial issue is how producers of shared data can and should be acknowledged and how this important component of science will benefit individuals in their academic careers. While we encourage the field to make use of these opportunities for data publishing, it is critical that standards for metadata, provenance, and other descriptors are used. This commentary outlines the efforts of the International Neuroinformatics Coordinating Facility Task Force on Neuroimaging Datasharing to coordinate and establish such standards, as well as potential ways forward to relieve the issues that researchers who produce these massive, reusable community resources face when making the data rapidly and freely available to the public. Both the technical and human aspects of data sharing must be addressed if we are to go forward.With the worldwide push for more open science and data sharing [1], it is an ideal time to consider the current state of data sharing in neuroscience, and in particular neuroimaging research. A huge amount of neuroimaging data has been acquired around the world; a recent literature search on PubMed led to an estimate of 12 000 datasets or 144 000 scans (around 55 petabytes of data) over the past 10?years, but only a few percent of such data is available in public repositories. Over the past two years, the International Neuroinformatics Coordinating Facility (http://www.incf.org webcite) has investigated barriers to data sharing through task force working groups and public workshops, and has identified a number of roadblocks, many of which are readily addressable, that impede researchers from both sharing and making use of existing shared data. These include a lack of simple tools for finding, uploading, and downloading shared data; uncertainty about how to best organize and prepare data for sharing, and concerns about data attribution. Many researchers are also wary of data sharing because of confusion institutional human research subject protection and the
PRIVACY IN MEDICAL DATA PUBLISHING  [PDF]
Lila Ghemri,Raji Kannah
International Journal of Cyber-Security and Digital Forensics , 2012,
Abstract: Privacy in data publishing concerns itself with the problem of releasing data to enable its study and analysis while protecting the privacy of the people or the subjects whose data is being released. The main motivation behind this work is the need to comply with HIPAA (Health Insurance Portability and Accountability Act) requirements on preserving patienta€ s privacy before making their data public. In this work, we present a policy-aware system that detects HIPAA privacy rule violations in medical records in textual format and takes remedial steps to mask the attributes that cause the violation to make them HIPAA-compliant.
Publishing without Publishers: a Decentralized Approach to Dissemination, Retrieval, and Archiving of Data  [PDF]
Tobias Kuhn,Christine Chichester,Michael Krauthammer,Michel Dumontier
Computer Science , 2014,
Abstract: Making available and archiving scientific results is for the most part still considered the task of classical publishing companies, despite the fact that classical forms of publishing centered around printed narrative articles no longer seem well-suited in the digital age. In particular, there exist currently no efficient, reliable, and agreed-upon methods for publishing scientific datasets, which have become increasingly important for science. Here we propose to design scientific data publishing as a Web-based bottom-up process, without top-down control of central authorities such as publishing companies. Based on a novel combination of existing concepts and technologies, we present a server network to decentrally store and archive data in the form of nanopublications, an RDF-based format to represent scientific data. We show how this approach allows researchers to publish, retrieve, verify, and recombine datasets of nanopublications in a reliable and trustworthy manner, and we argue that this architecture could be used for the Semantic Web in general. Evaluation of the current small network shows that this system is efficient and reliable.
Darwin Core: An Evolving Community-Developed Biodiversity Data Standard  [PDF]
John Wieczorek, David Bloom, Robert Guralnick, Stan Blum, Markus D?ring, Renato Giovanni, Tim Robertson, David Vieglais
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0029715
Abstract: Biodiversity data derive from myriad sources stored in various formats on many distinct hardware and software platforms. An essential step towards understanding global patterns of biodiversity is to provide a standardized view of these heterogeneous data sources to improve interoperability. Fundamental to this advance are definitions of common terms. This paper describes the evolution and development of Darwin Core, a data standard for publishing and integrating biodiversity information. We focus on the categories of terms that define the standard, differences between simple and relational Darwin Core, how the standard has been implemented, and the community processes that are essential for maintenance and growth of the standard. We present case-study extensions of the Darwin Core into new research communities, including metagenomics and genetic resources. We close by showing how Darwin Core records are integrated to create new knowledge products documenting species distributions and changes due to environmental perturbations.
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