75,487 research outputs found
A Linked Data Approach to Sharing Workflows and Workflow Results
A bioinformatics analysis pipeline is often highly elaborate, due to the inherent complexity of biological systems and the variety and size of datasets. A digital equivalent of the ‘Materials and Methods’ section in wet laboratory publications would be highly beneficial to bioinformatics, for evaluating evidence and examining data across related experiments, while introducing the potential to find associated resources and integrate them as data and services. We present initial steps towards preserving bioinformatics ‘materials and methods’ by exploiting the workflow paradigm for capturing the design of a data analysis pipeline, and RDF to link the workflow, its component services, run-time provenance, and a personalized biological interpretation of the results. An example shows the reproduction of the unique graph of an analysis procedure, its results, provenance, and personal interpretation of a text mining experiment. It links data from Taverna, myExperiment.org, BioCatalogue.org, and ConceptWiki.org. The approach is relatively ‘light-weight’ and unobtrusive to bioinformatics users
Complex Systems Science: Dreams of Universality, Reality of Interdisciplinarity
Using a large database (~ 215 000 records) of relevant articles, we
empirically study the "complex systems" field and its claims to find universal
principles applying to systems in general. The study of references shared by
the papers allows us to obtain a global point of view on the structure of this
highly interdisciplinary field. We show that its overall coherence does not
arise from a universal theory but instead from computational techniques and
fruitful adaptations of the idea of self-organization to specific systems. We
also find that communication between different disciplines goes through
specific "trading zones", ie sub-communities that create an interface around
specific tools (a DNA microchip) or concepts (a network).Comment: Journal of the American Society for Information Science and
Technology (2012) 10.1002/asi.2264
Mapping cyberspace: visualising, analysing and exploring virtual worlds
In the past years, with the development of computer networks such as the Internet
and world wide web (WWW), cyberspace has been increasingly studied by
researchers in various disciplines such as computer sciences, sociology, geography,
and cartography as well. Cyberspace is mainly rooted in two computer technologies:
network and virtual reality. Cybermaps, as special maps for cyberspace, have been
used as a tool for understanding various aspects of cyberspace. As recognised,
cyberspace as a virtual space can be distinguished from the earth we live on in many
ways. Because of these distinctions, mapping it implies a big challenge for
cartographers with their long tradition of mapping things in clear ways. This paper,
by comparing it to traditional maps, addresses various cybermap issues such as
visualising, analysing and exploring cyberspace from different aspects
Lost in translation: data integration tools meet the Semantic Web (experiences from the Ondex project)
More information is now being published in machine processable form on the
web and, as de-facto distributed knowledge bases are materializing, partly
encouraged by the vision of the Semantic Web, the focus is shifting from the
publication of this information to its consumption. Platforms for data
integration, visualization and analysis that are based on a graph
representation of information appear first candidates to be consumers of
web-based information that is readily expressible as graphs. The question is
whether the adoption of these platforms to information available on the
Semantic Web requires some adaptation of their data structures and semantics.
Ondex is a network-based data integration, analysis and visualization platform
which has been developed in a Life Sciences context. A number of features,
including semantic annotation via ontologies and an attention to provenance and
evidence, make this an ideal candidate to consume Semantic Web information, as
well as a prototype for the application of network analysis tools in this
context. By analyzing the Ondex data structure and its usage, we have found a
set of discrepancies and errors arising from the semantic mismatch between a
procedural approach to network analysis and the implications of a web-based
representation of information. We report in the paper on the simple methodology
that we have adopted to conduct such analysis, and on issues that we have found
which may be relevant for a range of similar platformsComment: Presented at DEIT, Data Engineering and Internet Technology, 2011
IEEE: CFP1113L-CD
Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure
Big data research has attracted great attention in science, technology,
industry and society. It is developing with the evolving scientific paradigm,
the fourth industrial revolution, and the transformational innovation of
technologies. However, its nature and fundamental challenge have not been
recognized, and its own methodology has not been formed. This paper explores
and answers the following questions: What is big data? What are the basic
methods for representing, managing and analyzing big data? What is the
relationship between big data and knowledge? Can we find a mapping from big
data into knowledge space? What kind of infrastructure is required to support
not only big data management and analysis but also knowledge discovery, sharing
and management? What is the relationship between big data and science paradigm?
What is the nature and fundamental challenge of big data computing? A
multi-dimensional perspective is presented toward a methodology of big data
computing.Comment: 59 page
- …