1,771 research outputs found
DRIVER Technology Watch Report
This report is part of the Discovery Workpackage (WP4) and is the third report out of four deliverables. The objective of this report is to give an overview of the latest technical developments in the world of digital repositories, digital libraries and beyond, in order to serve as theoretical and practical input for the technical DRIVER developments, especially those focused on enhanced publications. This report consists of two main parts, one part focuses on interoperability standards for enhanced publications, the other part consists of three subchapters, which give a landscape picture of current and surfacing technologies and communities crucial to DRIVER. These three subchapters contain the GRID, CRIS and LTP communities and technologies. Every chapter contains a theoretical explanation, followed by case studies and the outcomes and opportunities for DRIVER in this field
Research and Development Workstation Environment: the new class of Current Research Information Systems
Against the backdrop of the development of modern technologies in the field
of scientific research the new class of Current Research Information Systems
(CRIS) and related intelligent information technologies has arisen. It was
called - Research and Development Workstation Environment (RDWE) - the
comprehensive problem-oriented information systems for scientific research and
development lifecycle support. The given paper describes design and development
fundamentals of the RDWE class systems. The RDWE class system's generalized
information model is represented in the article as a three-tuple composite web
service that include: a set of atomic web services, each of them can be
designed and developed as a microservice or a desktop application, that allows
them to be used as an independent software separately; a set of functions, the
functional filling-up of the Research and Development Workstation Environment;
a subset of atomic web services that are required to implement function of
composite web service. In accordance with the fundamental information model of
the RDWE class the system for supporting research in the field of ontology
engineering - the automated building of applied ontology in an arbitrary domain
area, scientific and technical creativity - the automated preparation of
application documents for patenting inventions in Ukraine was developed. It was
called - Personal Research Information System. A distinctive feature of such
systems is the possibility of their problematic orientation to various types of
scientific activities by combining on a variety of functional services and
adding new ones within the cloud integrated environment. The main results of
our work are focused on enhancing the effectiveness of the scientist's research
and development lifecycle in the arbitrary domain area.Comment: In English, 13 pages, 1 figure, 1 table, added references in Russian.
Published. Prepared for special issue (UkrPROG 2018 conference) of the
scientific journal "Problems of programming" (Founder: National Academy of
Sciences of Ukraine, Institute of Software Systems of NAS Ukraine
Analysing Scientific Collaborations of New Zealand Institutions using Scopus Bibliometric Data
Scientific collaborations are among the main enablers of development in small
national science systems. Although analysing scientific collaborations is a
well-established subject in scientometrics, evaluations of scientific
collaborations within a country remain speculative with studies based on a
limited number of fields or using data too inadequate to be representative of
collaborations at a national level. This study represents a unique view on the
collaborative aspect of scientific activities in New Zealand. We perform a
quantitative study based on all Scopus publications in all subjects for more
than 1500 New Zealand institutions over a period of 6 years to generate an
extensive mapping of scientific collaboration at a national level. The
comparative results reveal the level of collaboration between New Zealand
institutions and business enterprises, government institutions, higher
education providers, and private not for profit organisations in 2010-2015.
Constructing a collaboration network of institutions, we observe a power-law
distribution indicating that a small number of New Zealand institutions account
for a large proportion of national collaborations. Network centrality concepts
are deployed to identify the most central institutions of the country in terms
of collaboration. We also provide comparative results on 15 universities and
Crown research institutes based on 27 subject classifications.Comment: 10 pages, 15 figures, accepted author copy with link to research
data, Analysing Scientific Collaborations of New Zealand Institutions using
Scopus Bibliometric Data. In Proceedings of ACSW 2018: Australasian Computer
Science Week 2018, January 29-February 2, 2018, Brisbane, QLD, Australi
Software Citation Implementation Challenges
The main output of the FORCE11 Software Citation working group
(https://www.force11.org/group/software-citation-working-group) was a paper on
software citation principles (https://doi.org/10.7717/peerj-cs.86) published in
September 2016. This paper laid out a set of six high-level principles for
software citation (importance, credit and attribution, unique identification,
persistence, accessibility, and specificity) and discussed how they could be
used to implement software citation in the scholarly community. In a series of
talks and other activities, we have promoted software citation using these
increasingly accepted principles. At the time the initial paper was published,
we also provided guidance and examples on how to make software citable, though
we now realize there are unresolved problems with that guidance. The purpose of
this document is to provide an explanation of current issues impacting
scholarly attribution of research software, organize updated implementation
guidance, and identify where best practices and solutions are still needed
Active Learning for Computationally Efficient Distribution of Binary Evolution Simulations
Binary stars undergo a variety of interactions and evolutionary phases,
critical for predicting and explaining observed properties. Binary population
synthesis with full stellar-structure and evolution simulations are
computationally expensive requiring a large number of mass-transfer sequences.
The recently developed binary population synthesis code POSYDON incorporates
grids of MESA binary star simulations which are then interpolated to model
large-scale populations of massive binaries. The traditional method of
computing a high-density rectilinear grid of simulations is not scalable for
higher-dimension grids, accounting for a range of metallicities, rotation, and
eccentricity. We present a new active learning algorithm, psy-cris, which uses
machine learning in the data-gathering process to adaptively and iteratively
select targeted simulations to run, resulting in a custom, high-performance
training set. We test psy-cris on a toy problem and find the resulting training
sets require fewer simulations for accurate classification and regression than
either regular or randomly sampled grids. We further apply psy-cris to the
target problem of building a dynamic grid of MESA simulations, and we
demonstrate that, even without fine tuning, a simulation set of only
the size of a rectilinear grid is sufficient to achieve the same classification
accuracy. We anticipate further gains when algorithmic parameters are optimized
for the targeted application. We find that optimizing for classification only
may lead to performance losses in regression, and vice versa. Lowering the
computational cost of producing grids will enable future versions of POSYDON to
cover more input parameters while preserving interpolation accuracies.Comment: 20 pages (16 main text), 10 figures, submitted to Ap
Building scalable digital library ingestion pipelines using microservices
CORE, a harvesting service offering access to millions of open access research papers from around the world, has shifted its harvesting process from following a monolithic approach to the adoption of a microservices infrastructure. In this paper, we explain how we rearranged and re-scheduled our old ingestion pipeline, present CORE's move to managing microservices and outline the tools we use in a new and optimised ingestion system. In addition, we discuss the ineffciencies of our old harvesting process, the advantages, and challenges of our new ingestion system and our future plans. We conclude that via the adoption of microservices architecture we managed to achieve a scalable and distributed system that would assist with CORE's future performance
and evolution
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