163 research outputs found
CiTO, the Citation Typing Ontology
CiTO, the Citation Typing Ontology, is an ontology for describing the nature of reference citations in scientific research articles and other scholarly works, both to other such publications and also to Web information resources, and for publishing these descriptions on the Semantic Web. Citation are described in terms of the factual and rhetorical relationships between citing publication and cited publication, the in-text and global citation frequencies of each cited work, and the nature of the cited work itself, including its publication and peer review status. This paper describes CiTO and illustrates its usefulness both for the annotation of bibliographic reference lists and for the visualization of citation networks. The latest version of CiTO, which this paper describes, is CiTO Version 1.6, published on 19 March 2010. CiTO is written in the Web Ontology Language OWL, uses the namespace http://purl.org/net/cito/, and is available from http://purl.org/net/cito/. This site uses content negotiation to deliver to the user an OWLDoc Web version of the ontology if accessed via a Web browser, or the OWL ontology itself if accessed from an ontology management tool such as Protégé 4 (http://protege.stanford.edu/). Collaborative work is currently under way to harmonize CiTO with other ontologies describing bibliographies and the rhetorical structure of scientific discourse
Adventures in Semantic Publishing: Exemplar Semantic Enhancements of a Research Article
Scientific innovation depends on finding, integrating, and re-using the products of
previous research. Here we explore how recent developments in Web technology,
particularly those related to the publication of data and metadata, might assist that
process by providing semantic enhancements to journal articles within the mainstream
process of scholarly journal publishing. We exemplify this by describing semantic
enhancements we have made to a recent biomedical research article taken from
PLoS Neglected Tropical Diseases, providing enrichment to its
content and increased access to datasets within it. These semantic enhancements
include provision of live DOIs and hyperlinks; semantic markup of textual terms, with
links to relevant third-party information resources; interactive figures; a
re-orderable reference list; a document summary containing a study summary, a tag
cloud, and a citation analysis; and two novel types of semantic enrichment: the
first, a Supporting Claims Tooltip to permit “Citations in
Context”, and the second, Tag Trees that bring together semantically
related terms. In addition, we have published downloadable spreadsheets containing
data from within tables and figures, have enriched these with provenance information,
and have demonstrated various types of data fusion (mashups) with results from other
research articles and with Google Maps. We have also published machine-readable RDF
metadata both about the article and about the references it cites, for which we
developed a Citation Typing Ontology, CiTO (http://purl.org/net/cito/). The
enhanced article, which is available at http://dx.doi.org/10.1371/journal.pntd.0000228.x001, presents a
compelling existence proof of the possibilities of semantic publication. We hope the
showcase of examples and ideas it contains, described in this paper, will excite the
imaginations of researchers and publishers, stimulating them to explore the
possibilities of semantic publishing for their own research articles, and thereby
break down present barriers to the discovery and re-use of information within
traditional modes of scholarly communication
OpenCitations: an Open e-Infrastructure to Foster Maximum Reuse of Citation Data
OpenCitations is an independent not-for-profit infrastructure organization for open scholarship dedicated to the publication of open bibliographic and citation data by the use of Semantic Web (Linked Data) technologies. OpenCitations collaborates with projects that are part of the Open Science ecosystem and complies with the UNESCO founding principles of Open Science, the I4OC recommendations, and the FAIR data principles that data should be Findable, Accessible, Interoperable and Reusable. Since its data satisfies all the Reuse guidelines provided by FAIR in terms of richness, provenance, usage licenses and domain-relevant community standards, OpenCitations provides an example of a successful open e-infrastructure in which the reusability of data is integral to its mission
OpenCitations Meta
OpenCitations Meta is a new database that contains bibliographic metadata of
scholarly publications involved in citations indexed by the OpenCitations
infrastructure. It adheres to Open Science principles and provides data under a
CC0 license for maximum reuse. The data can be accessed through a SPARQL
endpoint, REST APIs, and dumps. OpenCitations Meta serves three important
purposes. Firstly, it enables disambiguation of citations between publications
described using different identifiers from various sources. For example, it can
link publications identified by DOIs in Crossref and PMIDs in PubMed. Secondly,
it assigns new globally persistent identifiers (PIDs), known as OpenCitations
Meta Identifiers (OMIDs), to bibliographic resources without existing external
persistent identifiers like DOIs. Lastly, by hosting the bibliographic metadata
internally, OpenCitations Meta improves the speed of metadata retrieval for
citing and cited documents. The database is populated through automated data
curation, including deduplication, error correction, and metadata enrichment.
The data is stored in RDF format following the OpenCitations Data Model, and
changes and provenance information are tracked. OpenCitations Meta and its
production. OpenCitations Meta currently incorporates data from Crossref,
DataCite, and the NIH Open Citation Collection. In terms of semantic publishing
datasets, it is currently the first in data volume.Comment: 26 pages, 7 figure
Outlier detection of vital sign trajectories from COVID-19 patients
There is growing interest in continuous wearable vital sign sensors for
monitoring patients remotely at home. These monitors are usually coupled to an
alerting system, which is triggered when vital sign measurements fall outside a
predefined normal range. Trends in vital signs, such as an increasing heart
rate, are often indicative of deteriorating health, but are rarely incorporated
into alerting systems. In this work, we present a novel outlier detection
algorithm to identify such abnormal vital sign trends. We introduce a
distance-based measure to compare vital sign trajectories. For each patient in
our dataset, we split vital sign time series into 180 minute, non-overlapping
epochs. We then calculated a distance between all pairs of epochs using the
dynamic time warp distance. Each epoch was characterized by its mean pairwise
distance (average link distance) to all other epochs, with large distances
considered as outliers. We applied this method to a pilot dataset collected
over 1561 patient-hours from 8 patients who had recently been discharged from
hospital after contracting COVID-19. We show that outlier epochs correspond
well with patients who were subsequently readmitted to hospital. We also show,
descriptively, how epochs transition from normal to abnormal for one such
patient.Comment: 4 pages, 4 figures, 1 table. Submitted to IEEE BHI 2022, decision
pendin
Method of Manufacturing a Light Emitting, Photovoltaic or Other Electronic Apparatus and System
The present invention provides a method of manufacturing an electronic apparatus, such as a lighting device having light emitting diodes (LEDs) or a power generating device having photovoltaic diodes. The exemplary method includes depositing a first conductive medium within a plurality of channels of a base to form a plurality of first conductors; depositing within the plurality of channels a plurality of semiconductor substrate particles suspended in a carrier medium; forming an ohmic contact between each semiconductor substrate particle and a first conductor; converting the semiconductor substrate particles into a plurality of semiconductor diodes; depositing a second conductive medium to form a plurality of second conductors coupled to the plurality of semiconductor diodes; and depositing or attaching a plurality of lenses suspended in a first polymer over the plurality of diodes. In various embodiments, the depositing, forming, coupling and converting steps are performed by or through a printing process
Causality and the semantics of provenance
Provenance, or information about the sources, derivation, custody or history
of data, has been studied recently in a number of contexts, including
databases, scientific workflows and the Semantic Web. Many provenance
mechanisms have been developed, motivated by informal notions such as
influence, dependence, explanation and causality. However, there has been
little study of whether these mechanisms formally satisfy appropriate policies
or even how to formalize relevant motivating concepts such as causality. We
contend that mathematical models of these concepts are needed to justify and
compare provenance techniques. In this paper we review a theory of causality
based on structural models that has been developed in artificial intelligence,
and describe work in progress on a causal semantics for provenance graphs.Comment: Workshop submissio
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