scholarly journals BioAssay templates for the semantic web

2016 ◽  
Author(s):  
Alex M Clark ◽  
Nadia K Litterman ◽  
Janice E Kranz ◽  
Peter Gund ◽  
Kellan Gregory ◽  
...  
Keyword(s):  
Semantic Web ◽  
Degrees Of Freedom ◽  
Software Tool ◽  
Data Format ◽  
Content Creation ◽  
Software Algorithms ◽  
Pertinent Information ◽  
Low Degrees ◽  
Machine Readable ◽  
Community Input

Annotation of bioassay protocols using semantic web vocabulary is a way to make experiment descriptions machine-readable. Protocols are communicated using concise scientific English, which precludes most kinds of analysis by software algorithms. Given the availability of a sufficiently expressive ontology, some or all of the pertinent information can be captured by asserting a series of facts, expressed as semantic web triples (subject, predicate, object). With appropriate annotation, assays can be searched, clustered, tagged and evaluated in a multitude of ways, analogous to other segments of drug discovery informatics. The BioAssay Ontology (BAO) has been previously designed for this express purpose, and provides a layered hierarchy of meaningful terms which can be linked to. Currently the biggest challenge is the issue of content creation: scientists cannot be expected to use the BAO effectively without having access to software tools that make it straightforward to use the vocabulary in a canonical way. We have sought to remove this barrier by: (1) defining a bioassay template data model; (2) creating a software tool for experts to create or modify templates to suit their needs; and (3) designing a common assay template (CAT) to leverage the most value from the BAO terms. The CAT was carefully assembled by biologists in order to find a balance between the maximum amount of information captured vs. low degrees of freedom in order to keep the user experience as simple as possible. The data format that we use for describing templates and corresponding annotations is the native format of the semantic web (RDF triples), and we demonstrate some of the ways that generated content can be meaningfully queried using the SPARQL language. We have made all of these materials available as open source (http://github.com/cdd/bioassay-template), in order to encourage community input and use within diverse projects, including but not limited to our own commercial electronic lab notebook products.

scholarly journals BioAssay Templates for the semantic web

2016 ◽  
Vol 2 ◽  
pp. e61 ◽  
Author(s):  
Alex M. Clark ◽  
Nadia K. Litterman ◽  
Janice E. Kranz ◽  
Peter Gund ◽  
Kellan Gregory ◽  
...  
Keyword(s):  
Semantic Web ◽  
Degrees Of Freedom ◽  
Software Tool ◽  
Data Format ◽  
Content Creation ◽  
Software Algorithms ◽  
Pertinent Information ◽  
Low Degrees ◽  
Machine Readable ◽  
Community Input

Annotation of bioassay protocols using semantic web vocabulary is a way to make experiment descriptions machine-readable. Protocols are communicated using concise scientific English, which precludes most kinds of analysis by software algorithms. Given the availability of a sufficiently expressive ontology, some or all of the pertinent information can be captured by asserting a series of facts, expressed as semantic web triples (subject, predicate, object). With appropriate annotation, assays can be searched, clustered, tagged and evaluated in a multitude of ways, analogous to other segments of drug discovery informatics. The BioAssay Ontology (BAO) has been previously designed for this express purpose, and provides a layered hierarchy of meaningful terms which can be linked to. Currently the biggest challenge is the issue of content creation: scientists cannot be expected to use the BAO effectively without having access to software tools that make it straightforward to use the vocabulary in a canonical way. We have sought to remove this barrier by: (1) defining a BioAssay Template (BAT) data model; (2) creating a software tool for experts to create or modify templates to suit their needs; and (3) designing a common assay template (CAT) to leverage the most value from the BAO terms. The CAT was carefully assembled by biologists in order to find a balance between the maximum amount of information captured vs. low degrees of freedom in order to keep the user experience as simple as possible. The data format that we use for describing templates and corresponding annotations is the native format of the semantic web (RDF triples), and we demonstrate some of the ways that generated content can be meaningfully queried using the SPARQL language. We have made all of these materials available as open source (http://github.com/cdd/bioassay-template), in order to encourage community input and use within diverse projects, including but not limited to our own commercial electronic lab notebook products.

scholarly journals BioAssay templates for the semantic web

2016 ◽  
Author(s):  
Alex M Clark ◽  
Nadia K Litterman ◽  
Janice E Kranz ◽  
Peter Gund ◽  
Kellan Gregory ◽  
...  
Keyword(s):  
Semantic Web ◽  
Degrees Of Freedom ◽  
Software Tool ◽  
Data Format ◽  
Content Creation ◽  
Software Algorithms ◽  
Pertinent Information ◽  
Low Degrees ◽  
Machine Readable ◽  
Community Input

Annotation of bioassay protocols using semantic web vocabulary is a way to make experiment descriptions machine-readable. Protocols are communicated using concise scientific English, which precludes most kinds of analysis by software algorithms. Given the availability of a sufficiently expressive ontology, some or all of the pertinent information can be captured by asserting a series of facts, expressed as semantic web triples (subject, predicate, object). With appropriate annotation, assays can be searched, clustered, tagged and evaluated in a multitude of ways, analogous to other segments of drug discovery informatics. The BioAssay Ontology (BAO) has been previously designed for this express purpose, and provides a layered hierarchy of meaningful terms which can be linked to. Currently the biggest challenge is the issue of content creation: scientists cannot be expected to use the BAO effectively without having access to software tools that make it straightforward to use the vocabulary in a canonical way. We have sought to remove this barrier by: (1) defining a bioassay template data model; (2) creating a software tool for experts to create or modify templates to suit their needs; and (3) designing a common assay template (CAT) to leverage the most value from the BAO terms. The CAT was carefully assembled by biologists in order to find a balance between the maximum amount of information captured vs. low degrees of freedom in order to keep the user experience as simple as possible. The data format that we use for describing templates and corresponding annotations is the native format of the semantic web (RDF triples), and we demonstrate some of the ways that generated content can be meaningfully queried using the SPARQL language. We have made all of these materials available as open source (http://github.com/cdd/bioassay-template), in order to encourage community input and use within diverse projects, including but not limited to our own commercial electronic lab notebook products.

scholarly journals MMoOn Core – the Multilingual Morpheme Ontology

Semantic Web ◽  
2020 ◽  
pp. 1-29
Author(s):  
Bettina Klimek ◽  
Markus Ackermann ◽  
Martin Brümmer ◽  
Sebastian Hellmann
Keyword(s):  
Semantic Web ◽  
Linked Data ◽  
Semantic Model ◽  
Lexical Resources ◽  
Domain Specific ◽  
Word Forms ◽  
Language Data ◽  
Core Ontology ◽  
Machine Readable ◽  
Rapid Emergence

In the last years a rapid emergence of lexical resources has evolved in the Semantic Web. Whereas most of the linguistic information is already machine-readable, we found that morphological information is mostly absent or only contained in semi-structured strings. An integration of morphemic data has not yet been undertaken due to the lack of existing domain-specific ontologies and explicit morphemic data. In this paper, we present the Multilingual Morpheme Ontology called MMoOn Core which can be regarded as the first comprehensive ontology for the linguistic domain of morphological language data. It will be described how crucial concepts like morphs, morphemes, word forms and meanings are represented and interrelated and how language-specific morpheme inventories can be created as a new possibility of morphological datasets. The aim of the MMoOn Core ontology is to serve as a shared semantic model for linguists and NLP researchers alike to enable the creation, conversion, exchange, reuse and enrichment of morphological language data across different data-dependent language sciences. Therefore, various use cases are illustrated to draw attention to the cross-disciplinary potential which can be realized with the MMoOn Core ontology in the context of the existing Linguistic Linked Data research landscape.

scholarly journals PLATFORMIZING KNOWLEDGE: MESS AND MEANING IN WEB 3.0 INFRASTRUCTURES

2020 ◽  
Author(s):  
Andrew Iliadis ◽  
Wesley Stevens ◽  
Jean-Christophe Plantin ◽  
Amelia Acker ◽  
Huw Davies ◽  
...  
Keyword(s):  
Semantic Web ◽  
Information Exchange ◽  
Semantic Annotation ◽  
Data Access ◽  
Web 3.0 ◽  
Fine Grained ◽  
The Status ◽  
Nature Of Information ◽  
Data Portability ◽  
Machine Readable

This panel focuses on the way that platforms have become key players in the representation of knowledge. Recently, there have been calls to combine infrastructure and platform-based frameworks to understand the nature of information exchange on the web through digital tools for knowledge sharing. The present panel builds and extends work on platform and infrastructure studies in what has been referred to as “knowledge as programmable object” (Plantin, et al., 2018), specifically focusing on how metadata and semantic information are shaped and exchanged in specific web contexts. As Bucher (2012; 2013) and Helmond (2015) show, data portability in the context of web platforms requires a certain level of semantic annotation. Semantic interoperability is the defining feature of so-called "Web 3.0"—traditionally referred to as the semantic web (Antoniou et al, 2012; Szeredi et al, 2014). Since its inception, the semantic web has privileged the status of metadata for providing the fine-grained levels of contextual expressivity needed for machine-readable web data, and can be found in products as diverse as Google's Knowledge Graph, online research repositories like Figshare, and other sources that engage in platformizing knowledge. The first paper in this panel examines the international Schema.org collaboration. The second paper investigates the epistemological implications when platforms organize data sharing. The third paper argues for the use of patents to inform research methodologies for understanding knowledge graphs. The fourth paper discusses private platforms’ extraction and collection of user metadata and the enclosure of data access.

A Review on Semantic Text and Multimedia Retrieval and Recent Trends

2015 ◽  
Vol 6 (1) ◽  
pp. 54-74
Author(s):  
Oğuzhan Menemencioğlu ◽  
İlhami Muharrem Orak
Keyword(s):  
Semantic Web ◽  
Search Engine ◽  
Search Engines ◽  
Semantic Search ◽  
Multimedia Retrieval ◽  
Web Pages ◽  
The Face ◽  
Recent Trends ◽  
New Applications ◽  
Machine Readable

Semantic web works on producing machine readable data and aims to deal with large amount of data. The most important tool to access the data which exist in web is the search engine. Traditional search engines are insufficient in the face of the amount of data that consists in the existing web pages. Semantic search engines are extensions to traditional engines and overcome the difficulties faced by them. This paper summarizes semantic web, concept of traditional and semantic search engines and infrastructure. Also semantic search approaches are detailed. A summary of the literature is provided by touching on the trends. In this respect, type of applications and the areas worked for are considered. Based on the data for two different years, trend on these points are analyzed and impacts of changes are discussed. It shows that evaluation on the semantic web continues and new applications and areas are also emerging. Multimedia retrieval is a newly scope of semantic. Hence, multimedia retrieval approaches are discussed. Text and multimedia retrieval is analyzed within semantic search.

Representing and Sharing Tagging Data Using the Social Semantic Cloud of Tags

2010 ◽  
pp. 519-527
Author(s):  
Hak-Lae Kim ◽  
John G. Breslin ◽  
Stefan Decker ◽  
Hong-Gee Kim
Keyword(s):  
Semantic Web ◽  
Web 2.0 ◽  
Web Applications ◽  
Essential Element ◽  
Social Tagging ◽  
Social Software ◽  
Free Text ◽  
Content Creation ◽  
Software Applications ◽  
The Social

Social tagging has become an essential element for Web 2.0 and the emerging Semantic Web applications. With the rise of Web 2.0, websites that provide content creation and sharing features have become extremely popular. These sites allow users to categorize and browse content using tags (i.e., free-text keyword topics). However, the tagging structures or folksonomies created by users and communities are often interlocked with a particular site and cannot be reused in a different system or by a different client. This chapter presents a model for expressing the structure, features, and relations among tags in different Web 2.0 sites. The model, termed the Social Semantic Cloud of Tags (SCOT), allows for the exchange of semantic tag metadata and reuse of tags in various social software applications.

An Integrated Software Tool for High Fidelity Probabilistic Assessments of Metallic Aero-Engine Components

2016 ◽  
Author(s):  
R. Craig McClung ◽  
Paul Wawrzynek ◽  
Yi-Der Lee ◽  
Bruce J. Carter ◽  
Jonathan P. Moody ◽  
...  
Keyword(s):  
Crack Growth ◽  
Degrees Of Freedom ◽  
Software Tool ◽  
High Fidelity ◽  
Fatigue Lifetime ◽  
Turbine Engine ◽  
Engine Components ◽  
Integrated Software ◽  
Combined Work ◽  
Exchange Data

Most current tools and methodologies to predict the life and reliability of fracture critical gas turbine engine components rely on stress intensity factor solutions that assume highly idealized component and crack geometries, and this can lead to highly conservative results in some cases. This paper describes a new integrated methodology to perform these assessments that combines one software tool for creating high fidelity crack growth simulations (FRANC3D) with another software tool for performing probabilistic fatigue crack growth life assessments of turbine engine components (DARWIN). DARWIN employs finite element models of component stresses, while FRANC3D performs automatic adaptive re-meshing of these models to simulate crack growth. Modifications have been performed to both codes to allow them to share and exchange data and to enhance their shared computational capabilities. Most notably, a new methodology was developed to predict the shape evolution and the fatigue lifetime for cracks that are geometrically complex and not easily parameterized by a small number of degrees of freedom. This paper describes the integrated software system and the typical combined work flow, and it shows the results from a number of analyses that demonstrate the significant features of the system.

Semantic Metadata Interoperability and Inference-Based Querying in Digital Repositories

2009 ◽  
Vol 2 (4) ◽  
pp. 36-52 ◽  
Author(s):  
Dimitrios A. Koutsomitropoulos ◽  
Georgia D. Solomou ◽  
Andreas D. Alexopoulos ◽  
Theodore S. Papatheodorou
Keyword(s):  
Semantic Web ◽  
Semantic Interpretation ◽  
Dublin Core ◽  
Digital Resources ◽  
Metadata Standard ◽  
Digital Repositories ◽  
Semantic Metadata ◽  
Owl Ontology ◽  
Machine Readable ◽  
Metadata Interoperability

Metadata applications have evolved in time into highly structured “islands of information” about digital resources, often bearing a strong semantic interpretation. Scarcely, however, are these semantics being communicated in machine readable and understandable ways. At the same time, the process for transforming the implied metadata knowledge into explicit Semantic Web descriptions can be problematic and is not always evident. In this article we take upon the well-established Dublin Core metadata standard as well as other metadata schemata, which often appear in digital repositories set-ups, and suggest a proper Semantic Web OWL ontology. In this process the authors cope with discrepancies and incompatibilities, indicative of such attempts, in novel ways. Moreover, we show the potential and necessity of this approach by demonstrating inferences on the resulting ontology, instantiated with actual metadata records. The authors conclude by presenting a working prototype that provides for inference-based querying on top of digital repositories.

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