19,051 research outputs found
Web archives: the future
T his report is structured first, to engage in some speculative thought about the possible futures of the web as an exercise in prom pting us to think about what we need to do now in order to make sure that we can reliably and fruitfully use archives of the w eb in the future. Next, we turn to considering the methods and tools being used to research the live web, as a pointer to the types of things that can be developed to help unde rstand the archived web. Then , we turn to a series of topics and questions that researchers want or may want to address using the archived web. In this final section, we i dentify some of the challenges individuals, organizations, and international bodies can target to increase our ability to explore these topi cs and answer these quest ions. We end the report with some conclusions based on what we have learned from this exercise
Invest to Save: Report and Recommendations of the NSF-DELOS Working Group on Digital Archiving and Preservation
Digital archiving and preservation are important areas for research and development, but there is no agreed upon set of priorities or coherent plan for research in this area. Research projects in this area tend to be small and driven by particular institutional problems or concerns. As a consequence, proposed solutions from experimental projects and prototypes tend not to scale to millions of digital objects, nor do the results from disparate projects readily build on each other. It is also unclear whether it is worthwhile to seek general solutions or whether different strategies are needed for different types of digital objects and collections. The lack of coordination in both research and development means that there are some areas where researchers are reinventing the wheel while other areas are neglected.
Digital archiving and preservation is an area that will benefit from an exercise in analysis, priority setting, and planning for future research. The WG aims to survey current research activities, identify gaps, and develop a white paper proposing future research directions in the area of digital preservation. Some of the potential areas for research include repository architectures and inter-operability among digital archives; automated tools for capture, ingest, and normalization of digital objects; and harmonization of preservation formats and metadata. There can also be opportunities for development of commercial products in the areas of mass storage systems, repositories and repository management systems, and data management software and tools.
VisIVOWeb: A WWW Environment for Large-Scale Astrophysical Visualization
This article presents a newly developed Web portal called VisIVOWeb that aims
to provide the astrophysical community with powerful visualization tools for
large-scale data sets in the context of Web 2.0. VisIVOWeb can effectively
handle modern numerical simulations and real-world observations. Our
open-source software is based on established visualization toolkits offering
high-quality rendering algorithms. The underlying data management is discussed
with the supported visualization interfaces and movie-making functionality. We
introduce VisIVOWeb Network, a robust network of customized Web portals for
visual discovery, and VisIVOWeb Connect, a lightweight and efficient solution
for seamlessly connecting to existing astrophysical archives. A significant
effort has been devoted for ensuring interoperability with existing tools by
adhering to IVOA standards. We conclude with a summary of our work and a
discussion on future developments
AUGUR: Forecasting the Emergence of New Research Topics
Being able to rapidly recognise new research trends is strategic for many stakeholders, including universities, institutional funding bodies, academic publishers and companies. The literature presents several approaches to identifying the emergence of new research topics, which rely on the assumption that the topic is already exhibiting a certain degree of popularity and consistently referred to by a community of researchers. However, detecting the emergence of a new research area at an embryonic stage, i.e., before the topic has been consistently labelled by a community of researchers and associated with a number of publications, is still an open challenge. We address this issue by introducing Augur, a novel approach to the early detection of research topics. Augur analyses the diachronic relationships between research areas and is able to detect clusters of topics that exhibit dynamics correlated with the emergence of new research topics. Here we also present the Advanced Clique Percolation Method (ACPM), a new community detection algorithm developed specifically for supporting this task. Augur was evaluated on a gold standard of 1,408 debutant topics in the 2000-2011 interval and outperformed four alternative approaches in terms of both precision and recall
Intrinsically Dynamic Network Communities
Community finding algorithms for networks have recently been extended to
dynamic data. Most of these recent methods aim at exhibiting community
partitions from successive graph snapshots and thereafter connecting or
smoothing these partitions using clever time-dependent features and sampling
techniques. These approaches are nonetheless achieving longitudinal rather than
dynamic community detection. We assume that communities are fundamentally
defined by the repetition of interactions among a set of nodes over time.
According to this definition, analyzing the data by considering successive
snapshots induces a significant loss of information: we suggest that it blurs
essentially dynamic phenomena - such as communities based on repeated
inter-temporal interactions, nodes switching from a community to another across
time, or the possibility that a community survives while its members are being
integrally replaced over a longer time period. We propose a formalism which
aims at tackling this issue in the context of time-directed datasets (such as
citation networks), and present several illustrations on both empirical and
synthetic dynamic networks. We eventually introduce intrinsically dynamic
metrics to qualify temporal community structure and emphasize their possible
role as an estimator of the quality of the community detection - taking into
account the fact that various empirical contexts may call for distinct
`community' definitions and detection criteria.Comment: 27 pages, 11 figure
Methodologies for the Automatic Location of Academic and Educational Texts on the Internet
Traditionally online databases of web resources have been compiled by a human editor, or though the submissions of authors or interested parties. Considerable resources are needed to maintain a constant level of input and relevance in the face of increasing material quantity and quality, and much of what is in databases is of an ephemeral nature. These pressures dictate that many databases stagnate after an initial period of enthusiastic data entry. The solution to this problem would seem to be the automatic harvesting of resources, however, this process necessitates the automatic classification of resources as ‘appropriate’ to a given database, a problem only solved by complex text content analysis.
This paper outlines the component methodologies necessary to construct such an automated harvesting system, including a number of novel approaches. In particular this paper looks at the specific problems of automatically identifying academic research work and Higher Education pedagogic materials. Where appropriate, experimental data is presented from searches in the field of Geography as well as the Earth and Environmental Sciences. In addition, appropriate software is reviewed where it exists, and future directions are outlined
Methodologies for the Automatic Location of Academic and Educational Texts on the Internet
Traditionally online databases of web resources have been compiled by a human editor, or though the submissions of authors or interested parties. Considerable resources are needed to maintain a constant level of input and relevance in the face of increasing material quantity and quality, and much of what is in databases is of an ephemeral nature. These pressures dictate that many databases stagnate after an initial period of enthusiastic data entry. The solution to this problem would seem to be the automatic harvesting of resources, however, this process necessitates the automatic classification of resources as ‘appropriate’ to a given database, a problem only solved by complex text content analysis.
This paper outlines the component methodologies necessary to construct such an automated harvesting system, including a number of novel approaches. In particular this paper looks at the specific problems of automatically identifying academic research work and Higher Education pedagogic materials. Where appropriate, experimental data is presented from searches in the field of Geography as well as the Earth and Environmental Sciences. In addition, appropriate software is reviewed where it exists, and future directions are outlined
Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines
A cross-disciplinary examination of the user behaviours involved in seeking
and evaluating data is surprisingly absent from the research data discussion.
This review explores the data retrieval literature to identify commonalities in
how users search for and evaluate observational research data. Two analytical
frameworks rooted in information retrieval and science technology studies are
used to identify key similarities in practices as a first step toward
developing a model describing data retrieval
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