- The document discusses OpenFlyData, a project that integrates biological data from multiple sources using Semantic Web technologies like RDF and SPARQL. It describes applications that allow searching gene expression data across databases.
- Key challenges addressed are that biological data is scattered across sites and integration requires mapping heterogeneous identifiers. The architecture uses a SPARQL endpoint and mappings to expose data from sources like FlyBase, BDGP and FlyAtlas.
- Performance testing showed good query times for real-time user interaction, though some queries took seconds and text matching had issues without custom solutions. Future work aims to add sources and develop more applications.
May 2012 JaxDUG presentation by Zachary Gramana on using the Lucene.NET library to add search functionality to .NET applications. Contains an overview of search/information retrieval concepts and highlights some common use-cases.
Eureka Research Workbench: A Semantic Approach to an Open Source Electroni...Stuart Chalk
Scientists are looking for ways to leverage web 2.0 technologies in the research laboratory and as a consequence a number of approaches to web-based electronic notebooks are being evaluated. In this presentation I discuss the Eureka Research Workbench, an electronic laboratory notebook built on semantic technology and XML. Using this approach the context of the information recorded in the laboratory can be captured and searched along with the data itself. A discussion of the current system is presented along with the next planned development of the framework and long-term plans relative to linked open data. Presented at the 246th American Chemical Society Meeting in Indianapolis, IN, USA on September 12th, 2013.
May 2012 JaxDUG presentation by Zachary Gramana on using the Lucene.NET library to add search functionality to .NET applications. Contains an overview of search/information retrieval concepts and highlights some common use-cases.
Eureka Research Workbench: A Semantic Approach to an Open Source Electroni...Stuart Chalk
Scientists are looking for ways to leverage web 2.0 technologies in the research laboratory and as a consequence a number of approaches to web-based electronic notebooks are being evaluated. In this presentation I discuss the Eureka Research Workbench, an electronic laboratory notebook built on semantic technology and XML. Using this approach the context of the information recorded in the laboratory can be captured and searched along with the data itself. A discussion of the current system is presented along with the next planned development of the framework and long-term plans relative to linked open data. Presented at the 246th American Chemical Society Meeting in Indianapolis, IN, USA on September 12th, 2013.
Toward Semantic Representation of Science in Electronic Laboratory Notebooks ...Stuart Chalk
An electronic laboratory Notebook (ELN) can be characterized as a system that allows scientists to capture the data and resources used in performing scientific experiments. This allows users to easily organize and find their data however, little information about the scientific process is recorded.
In this paper we highlight the current status of progress toward semantic representation of science in ELNs.
Often information is spread among
several data sources, such as hospital databases, lab databases,
spreadsheets, etc. Moreover, the complexity of each of these data sources
might make it difficult for end-users to access them, and even
more, to query all of them at the same time.
A new solution that has been proposed to this problem is
ontology-based data access (OBDA).
OBDA is a popular paradigm, developed since the mid 2000s, to query
various types of data sources
using a common vocabulary familiar to the end-users. In a nutshell
OBDA separates the user
from the data sources (relational databases, CVS files, etc.) by means
of an ontology, which is a common terminology that provides the user with a
convenient query vocabulary, hides the structure of the data sources,
and can enrich incomplete data with background knowledge. About a
dozen OBDA systems have been implemented in both academia and
industry.
In this tutorial we will give an overview of OBDA, and our system -ontop-
which is currently being used in the context of the European project
Optique. We will discuss how to use -ontop- for data integration,
in particular concentrating on:
– How to create an ontology (common vocabulary) for a life science domain.
– How to map available data sources to this ontology.
– How to query the database using the terms in the ontology.
– How to check consistency of the data sources w.r.t. the ontology
Quickly re-publish CSV/TSV files from existing repositories as FAIR Data with just a few mouse clicks!
You select the columns to "project" as Linked Data, and the associated ontology terms. The FAIR Projector Builder will create a FAIR Projector for you: a Triple Pattern Fragment server to provide the Linked Data; a published DCAT Distribution containing metadata about those triples and their source; and an RML model (syntactic and semantic of the triples, to aid in third-party discovery of this novel projection.
(current status - first prototype, not ready for public consumption)
-------
Thanks to the NBDC/DBCLS for sponsoring the hackathon series.
MDW also funded by Ministerio de Economía y Competitividad grant number TIN2014-55993-RM
A tutorial on how to create mappings using ontop, how inference (OWL 2 QL and RDFS) plays a role answering SPARQL queries in ontop, and how ontop's support for on-the-fly SQL query translation enables scenarios of semantic data access and data integration.
Tech. session : Interoperability and Data FAIRness emerges from a novel combi...Mark Wilkinson
My presentation to OAI10 - CERN - UNIGE Workshop on Innovations in Scholarly Communication, 21-23 June 2017
University of Geneva.
https://indico.cern.ch/event/405949/contributions/2487823/
A description of the FAIR Accessor and FAIR Projector technologies: REST-compliant approaches to publishing FAIR Metadata and FAIR Data (respectively)
Spanish Ministerio de Economía y Competitividad TIN2014-55993-R
Ontology-based data access: why it is so cool!Josef Hardi
A brief introduction about ontology-based data access (shortly OBDA) and its core implementation. I presented too a recent simple benchmark between -ontop- and Semantika---two most available software for OBDA framework---in term of query performance (including details in the appendix section). The slides were presented for Friday Research Meeting in Stanford Center for Biomedical Informatics Research (BMIR).
License: Creative Commons by Attribution 3.0
Toward Semantic Representation of Science in Electronic Laboratory Notebooks ...Stuart Chalk
An electronic laboratory Notebook (ELN) can be characterized as a system that allows scientists to capture the data and resources used in performing scientific experiments. This allows users to easily organize and find their data however, little information about the scientific process is recorded.
In this paper we highlight the current status of progress toward semantic representation of science in ELNs.
Often information is spread among
several data sources, such as hospital databases, lab databases,
spreadsheets, etc. Moreover, the complexity of each of these data sources
might make it difficult for end-users to access them, and even
more, to query all of them at the same time.
A new solution that has been proposed to this problem is
ontology-based data access (OBDA).
OBDA is a popular paradigm, developed since the mid 2000s, to query
various types of data sources
using a common vocabulary familiar to the end-users. In a nutshell
OBDA separates the user
from the data sources (relational databases, CVS files, etc.) by means
of an ontology, which is a common terminology that provides the user with a
convenient query vocabulary, hides the structure of the data sources,
and can enrich incomplete data with background knowledge. About a
dozen OBDA systems have been implemented in both academia and
industry.
In this tutorial we will give an overview of OBDA, and our system -ontop-
which is currently being used in the context of the European project
Optique. We will discuss how to use -ontop- for data integration,
in particular concentrating on:
– How to create an ontology (common vocabulary) for a life science domain.
– How to map available data sources to this ontology.
– How to query the database using the terms in the ontology.
– How to check consistency of the data sources w.r.t. the ontology
Quickly re-publish CSV/TSV files from existing repositories as FAIR Data with just a few mouse clicks!
You select the columns to "project" as Linked Data, and the associated ontology terms. The FAIR Projector Builder will create a FAIR Projector for you: a Triple Pattern Fragment server to provide the Linked Data; a published DCAT Distribution containing metadata about those triples and their source; and an RML model (syntactic and semantic of the triples, to aid in third-party discovery of this novel projection.
(current status - first prototype, not ready for public consumption)
-------
Thanks to the NBDC/DBCLS for sponsoring the hackathon series.
MDW also funded by Ministerio de Economía y Competitividad grant number TIN2014-55993-RM
A tutorial on how to create mappings using ontop, how inference (OWL 2 QL and RDFS) plays a role answering SPARQL queries in ontop, and how ontop's support for on-the-fly SQL query translation enables scenarios of semantic data access and data integration.
Tech. session : Interoperability and Data FAIRness emerges from a novel combi...Mark Wilkinson
My presentation to OAI10 - CERN - UNIGE Workshop on Innovations in Scholarly Communication, 21-23 June 2017
University of Geneva.
https://indico.cern.ch/event/405949/contributions/2487823/
A description of the FAIR Accessor and FAIR Projector technologies: REST-compliant approaches to publishing FAIR Metadata and FAIR Data (respectively)
Spanish Ministerio de Economía y Competitividad TIN2014-55993-R
Ontology-based data access: why it is so cool!Josef Hardi
A brief introduction about ontology-based data access (shortly OBDA) and its core implementation. I presented too a recent simple benchmark between -ontop- and Semantika---two most available software for OBDA framework---in term of query performance (including details in the appendix section). The slides were presented for Friday Research Meeting in Stanford Center for Biomedical Informatics Research (BMIR).
License: Creative Commons by Attribution 3.0
Presentation slides of a talk explaining the business model canvas and giving an introduction to the customer development process.
This talk was given during the first StartUpQ8.Com event on Wednesday 26/9/2012.
This presentation suggests some strategies and tactics for marketing KTH University around the world. The aim is to get the full house in 2012.
This presentation was selected the best at Leadership for Operational Development Course.
Use of logos or any other sign with legal responsibility is only for educational purposes. It should be considered as a school assignment and not something official.
Finding knowledge, data and answers on the Semantic Webebiquity
Web search engines like Google have made us all smarter by providing ready access to the world's knowledge whenever we need to look up a fact, learn about a topic or evaluate opinions. The W3C's Semantic Web effort aims to make such knowledge more accessible to computer programs by publishing it in machine understandable form.
<p>
As the volume of Semantic Web data grows software agents will need their own search engines to help them find the relevant and trustworthy knowledge they need to perform their tasks. We will discuss the general issues underlying the indexing and retrieval of RDF based information and describe Swoogle, a crawler based search engine whose index contains information on over a million RDF documents.
<p>
We will illustrate its use in several Semantic Web related research projects at UMBC including a distributed platform for constructing end-to-end use cases that demonstrate the semantic web’s utility for integrating scientific data. We describe ELVIS (the Ecosystem Location Visualization and Information System), a suite of tools for constructing food webs for a given location, and Triple Shop, a SPARQL query interface which searches the Semantic Web for data relevant to a given query ELVIS functionality is exposed as a collection of web services, and all input and output data is expressed in OWL, thereby enabling its integration with Triple Shop and other semantic web resources.
Building your own search engine with Apache SolrBiogeeks
Andrew Clegg : Building your own search engine with Apache Solr
Apache Solr (http://lucene.apache.org/solr/) is an open-source search
engine based on the popular Lucene library with a huge variety of
features. In this talk, Andrew describes how he used it to build a
high-performance search tool for protein and domain structures at
CATH, and talks about some of the suprisingly cool things you can do
with it beyond simple searching.
247th ACS Meeting: The Eureka Research WorkbenchStuart Chalk
Academic scientists need a tool to capture the science they do so that it can be shared in open science, integrated with linked data, and shared/searched. Eureka is an evolving platform to do this.
ParlBench: a SPARQL-benchmark for electronic publishing applications.Tatiana Tarasova
Slides from the workshop on Benchmarking RDF Systems co-located with the Extended Semantic Web Conference 2013. The presentation is about an on-going work on building the benchmark for electronic publishing applications. The benchmark provides real-world data sets, the Dutch parliamentary proceedings and a set of analytical SPARQL queries that were built on top of these data sets. The queries were grouped into micro-benchmarks according to their analytical aims. This allows one to perform better analysis of RDF stores behaviors with respect to a certain SPARQL feature used in a micro-benchmark/query.
Preliminary results of running the benchmark on the Virtuoso native RDF store are presented, as well as references to the on-line material including the data sets, queries and the scripts that were used to obtain the results.
ACS 248th Paper 146 VIVO/ScientistsDB Integration into EurekaStuart Chalk
Development of plugins for access to researchers identified in VIVO on the ScientistsDB website. Also developed a plugin to access Elasticsearch from within Eureka.
1. OpenFlyData: the way to go for biological data integration Dr Jun Zhao Image Bioinformatics Research Group Department of Zoology University of Oxford
8. System architecture SPARQL endpoint Web browser FlyUI application FlyUI widget HTTP Client side SPARQL server (SPARQLite, Tomcat, Apache) RDF cache (Jena TDB) FlyBase BDGP FlyTED FlyAtlas Server side
9.
10. The heterogeneous Drosophila gene names DATA SOURCE POSSIBLE GENE IDENTIFIERS EXAMPLES FlyBase symbol schuy full name schumacher-levy annotation symbol CG17736 Unique FlyBase id FBgn0036925 Curated synonyms CG17736, schuy, etc BDGP FlyBase id FBgn0036925 Annotation symbol CG17736 FlyAtlas Affy microarray probe id 16166608_a_at FlyTED Uncontrolled gene name schuy, CG17736/schuy
11.
12. SPARQL queries PREFIX chado: <http://purl.org/net/chado/schema> PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> PREFIX xs: <http://www.w3.org/2001/XML_Schema#> SELECT ?flybaseID WHERE { ?feature rdf:type chado:Feature ; chado:name “schuy”^^xs:string ; chado:uniquename ?flybaseID . } SELECT ?feature.uniquename AS flybaseID FROM feature WHERE feature.name = “schuy” SPARQL SQL
13. SPARQL protocol GET /query/flybase?query=[URL encoded query] HTTP/1.1 Host: openflydata.org Accept: application/sparql-results+json POST /query/flybase HTTP/1.1 Host: openflydata.org Accept: application/sparql-results+json Content-Type: application/x-www-form-urlencoded Content-Length: 456 query=[URL encoded query] HTTP GET HTTP POST
Note that the thumbnail images are retrieved from the original web sites
FlyUI: a library of Javascript widgets as front ends to SPARQL data sources Built on Yahoo User Interface (YUI) library Widgets are composed in a browser to create the complete application Each widget provides: A Service that implements SPARQL queries A Model encapsulating SPARQL query results A Renderer
Initially hoped to use D2R server's SPARQL query rewriting, but some queries would kill the server, so went for SPARQLite alternative Different techniques for generating RDF applied to different kinds of data source Resulting RDF is loaded into the Jena TDB triple store.
This is mostly based on available off-the-shelf software Choice of triple store is influenced significantly by speed of loading ~10 million triples Also performed some experiments with OpenLink Virtuoso – performance looks pretty good Amazon EC2/EBS has worked well for us