ReDD-Observatory: Using the Web of Data for Evaluating the Research-Disease Disparity

The ReDD-Observatory is a project to evaluate the disparity between active areas of biomedical research and the global burden of disease using Linked Data and data-driven discovery.

Background

It is widely accepted that there is a large disparity between the availability of treatment options and the prevalence of diseases in the world, thus placing individuals in danger. This disparity is partially caused by the restricted access to information that would allow health- care and research policy makers to formulate more appropriate measures to mitigate this disparity. Specifically, this shortage of information is caused by the difficulty in reliably obtaining and integrating data regarding the disease burden for a given nation and the respective research investments.

In response to these challenges, the Linked Data paradigm provides a simple mechanism for publishing and interlinking structured information on the Web. In conjunction with the ever increasing data on diseases and healthcare research available as Linked Data, an opportunity is created to reduce this information gap that would allow for better policy in response to these disparities.

We present the ReDD-Observatory, an approach for evaluating the Research-Disease Disparity based on the interlinking and integrating of various biomedical data sources.

Methodology

The figure below provides a birds eye-view of the methodology involved in the ReDD-Observatory.

We first identified relevant datasets to be included that provided relevant information to evaluate the disparity. We not only consider the datasets already present as RDF but also those that are present in unstructured formats. These datasets are:

  1. LinkedCT - the RDF representation of ClinicalTrials.gov, which is the database of all clinical trials around the world.
  2. Bio2RDF's PubMed - the RDF representation of PubMed, which is a service of the US National Library of Medicine that includes bibliographic information and abstracts of over 19 million publications from MEDLINE and other life science journals.
  3. WHO's Global Health Observatory (GHO), which contains statistical information regarding the mortality and burden of disease classified according to the death and DALY (disability-adjusted life year) estimates grouped by countries and regions. However, since GHO is not available as Linked Data, as the next step we devised a method for representing unstructured data as RDF. We devised a plug-in in OntoWiki to represent statistical data from GHO as RDF. We used the Data Cube Vocabulary for this conversion. More information is present here. In order to ensure the completeness, conciseness and consistency for the selected datasets our next step is to assess the data quality of the datasets. The next challenging step is to interlink the datasets for a number of concepts such as (a) countries, (b) diseases and (c) publications. The assessment of the disparity is then performed with a number of parametrized SPARQL queries. We evaluate the results wrt. information quality and interlinking precision. As a consequence, we are, for the first time, able to provide reliable indicators for the extent of the research-disease disparity around the world in an semi- automated fashion, thus enabling healthcare professionals and policy makers to make more informed decisions.

Further Information

Current Team

Publications

by (Editors: ) [BibTex of ]

News

Highlights of the 1st Meetup on Question Answering Systems – Leipzig, November 21st ( 2014-11-24T10:09:09+01:00 by Ali Khalili)

2014-11-24T10:09:09+01:00 by Ali Khalili

On November 21st, AKSW group was hosting the 1st meetup on “Question Answering” (QA) systems. In this meeting, researchers from AKSW/University of Leipzig, CITEC/University of Bielefeld, Fraunhofer IAIS/University of Bon, DERI/National University of Ireland and the University of Passau presented the recent results of their work on QA systems. Read more about "Highlights of the 1st Meetup on Question Answering Systems – Leipzig, November 21st"

Announcing GERBIL: General Entity Annotator Benchmark Framework ( 2014-11-20T10:08:33+01:00 by Ricardo Usbeck)

2014-11-20T10:08:33+01:00 by Ricardo Usbeck

Dear all, We are happy to announce GERBIL – a General Entity Annotation Benchmark Framework, a demo can be found at! With GERBIL, we aim to establish a highly available, easy quotable and liable focal point for Named Entity Recognition and Named Entity Disambiguation (Entity Linking) evaluations: GERBIL provides persistent URLs for experimental settings. Read more about "Announcing GERBIL: General Entity Annotator Benchmark Framework"

@BioASQ challenge gaining momentum ( 2014-11-17T15:29:24+01:00 by Ricardo Usbeck)

2014-11-17T15:29:24+01:00 by Ricardo Usbeck

BioASQ is a series of challenges aiming to bring us closer to the vision of machines that can answer questions of biomedical professionals and researchers. The second BioASQ challenge started in February 2013. It comprised two different tasks: Large-scale biomedical semantic indexing (Task 2a), and biomedical semantic question answering (Task 2b). Read more about "@BioASQ challenge gaining momentum"

AKSW successful at #ISWC2014 ( 2014-10-28T17:03:42+01:00 by Ricardo Usbeck)

2014-10-28T17:03:42+01:00 by Ricardo Usbeck

Dear followers, 9 members of AKSW have been participating at the 13th International Semantic Web Conference (ISWC) at Riva del Garda, Italy. Read more about "AKSW successful at #ISWC2014"

AKSW internal group meeting @ Dessau ( 2014-10-23T02:07:29+02:00 EdgardMarx)

2014-10-23T02:07:29+02:00 EdgardMarx

Recently AKSW members were at the city of Dessau for an internal group meeting. The meeting took place between 8th and 10th of October, in the modern university of architecture of Bauhaus were we also stayed hosted. Bauhaus is located in the city of Dessau, about one hour from Leipzig. Read more about "AKSW internal group meeting @ Dessau"