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Linked Data and Cochrane Reviews A report from the ‘Star Trek’ Crew Chris Mavergames Web Operations Manager/Information Architect Cochrane Collaboration.

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Presentation on theme: "Linked Data and Cochrane Reviews A report from the ‘Star Trek’ Crew Chris Mavergames Web Operations Manager/Information Architect Cochrane Collaboration."— Presentation transcript:

1 Linked Data and Cochrane Reviews A report from the ‘Star Trek’ Crew Chris Mavergames Web Operations Manager/Information Architect Cochrane Collaboration Web Team

2 Structure of this talk Intro to linked data and what it means for Cochrane "Star Trek" stream of work so far What's possible now and in the future * Acknowledgements to Lorne Becker and the entire Star Trek crew. Their input was invaluable in the preparation of this talk.

3 Cochrane Reviews are fantastic BUT… There are problems that limit their use by some people ◦Difficult to wade through all of the text ◦Difficult to understand the figures, terminology, and other bits of the Review ◦Hard to compare interventions without reading multiple Reviews ◦Can be difficult to find the Review you seek

4 Searching The Cochrane Library Search for “Prozac” – no reviews Search for “fluoxetine” – 25 reviews

5 Ideally we’d restructure our content for different users Beginning to do this now: ◦Summaries.Cochrane.org for consumers ◦Cochrane Clinical for clinicians BUT ◦Takes a lot of work to reformulate reviews & authors, CRGs, etc are busy Wouldn’t it be nice if we could automate or partially automate this?

6 How did Bing read 3 different weather sites & bring me the data I need?

7 Could we do similar magic with our Cochrane reviews? If so, what might we be able to accomplish?

8 Linked data

9 What is linked data? Semantic Web is made up of: Linked Data & Web of Data Which all together comprise Web 3.0

10 Current web = Web of documents

11 Docs are linked not data in docs

12 Machines aren‘t good at reading web pages Data on the web is meant for human consumption Machines need the data to be structured Once structured, information can be more easily shared within datasets and across web pages

13 Cochrane Reviews and Linked data

14 Cochrane Reviews XML........ XML........

15 Fortunately, Cochrane Reviews are structured – but we still need to teach the machines how to read them, where to find data within them and how the data is related.

16 Cochrane Reviews Data point Data point Data point Data point Data point Data point Data point Data point Data point Data point Data point

17 Cochrane Register of Studies

18 Links to the CRS Lack of unique study IDs a real problem CRS solves this by providing a unique ID for all studies that can be referenced Better linking of data about trials and possibilities with linking to external sources such as PubMed (example later)

19 Linked data technologies OWL (Web Ontology Language) RDF (Resource Description Framework) SPARQL (RDF query language) Model Cochrane Reviews in OWL Transform them into RDF and add to triple store Query them with SPARQL OR, simply...

20 Use the gears!

21 Triple store = Way we think! Subject -> Property -> Object has-role works-in

22 Using “the gears” All Reviews in Archie A Copy of the Review XML A Model of the Data A Machine Readable “Triple Store” Standard tools have been developed to facilitate this process

23 Using “the gears” A Question A Machine Generated Answer A Machine Readable “Triple Store”

24 Star Trek

25 Insert witty Star Trek reference here!

26 Cochrane Review ontology

27 Lots of work still needed from people with a deep understanding of Cochrane content in order to get the data model and ontology right

28 Cochrane Review ontology

29

30

31 Findings ontology from Lorne

32 What sorts of things could we do with this? A Question A Machine Generated Answer A Machine Readable “Triple Store”

33 Gears!

34 We can… Ask questions that use data from several different reviews Enhance the experience of our users by including data from the triple stores of others Improve search Make it easier for people to find Cochrane Reviews

35 Ask questions that use data from several different reviews Enhancing the User Experience

36 A question using multiple reviews I’ve done a search for trials on a particular intervention for dementia. I want to know which of the trials have been included in a Cochrane Review.

37 Finding the answer the old way Search for the relevant Reviews Read the reference lists to find included trials Compare with my trial search Eliminate the new references that are additional publications from trials already included in a Review. OR…

38 The “Star Trek” Way My list of trials A Machine Generated list of trials not yet included in a review The Cochrane Review “Triple Store” A ”studified” list from the CRS

39 Links to the relevant Review for those trials that were included

40 INSERT IMAGE FOR QUESTION 1 HERE Question 1: SPARQL query and partial list of results

41 Another question using multiple Reviews What are the risks of bias for the entire set of trials assessing the effectiveness of a particular intervention?

42 Finding the answer the old way Search for the relevant reviews (there may be more than one) Read the tables of included studies to find risk of bias assessments for each trial Combine them * (in some cases review authors may have done this for all of the trials in a single review)

43 The “Star Trek” Way A Machine generated summary of the Risk of Bias assessments for the relevant trials The Cochrane Review “Triple Store”

44 Question 2 visualized These figures summarize Risks of Bias from the trials included in the reviews in your search RoB Summary for Cochrane Reviews on dementia

45 Cochrane Reviews XML........ XML........

46 Make search work better Enhancing the User Experience

47 You Say “Paracetamol” I Say “Acetaminophen” Or, one could say any of these: Abenol (CA), Acephen, Anadin Paracetamol (UK), Apo-Acetaminophen (CA), Aspirin Free Anacin, Atasol (CA), Calpol (UK), Cetaphen, Children's Tylenol Soft Chews, Disprol (UK), Exdol (CA), Feverall, Galpamol (UK), Genapap, Genebs, Infant's Pain Reliever, Mandanol (UK), Nortemp, Pain Eze, Panadol (UK), Robigesic (CA), Silapap, Tycolene, Tylenol 8 Hour, Tylenol, Tylenol Arthritis, Uni- Ace, Valorin

48 LinkedLifeData.com

49 LinkedLifeData.com

50 DrugBank

51 Cochrane Reviews XML........ XML........

52 Cochrane Reviews XML........ XML........

53 Make it easier for people to find Cochrane Reviews Enhancing the User Experience

54 Enhancing news content

55 Cochrane Reviews marked up in semantic markup can be linked to news publishers For example, BBC Health writers could be suggested related Cochrane evidence for a particular story they are writing And, could include a link to primary source material such as a Cochrane Review Thus driving traffic to our Reviews

56 Super Star Trek

57 How applicable is this Review in my part of the world?

58 Geographical relevance A list of the drugs in comparisons of malaria in Reviews and the geographic extent of their effectiveness

59

60 Map of Artemisin Resistance

61 The future

62 Making our content nimble Structured and linked data can help make our content “nimble” Nimble content can: Travel Freely Retain Context Meaning Create New Products - R. Lovinger, Razorfish

63 Structured data "Structured data allows you to preserve your value proposition over a longer distance to a much wider audience." - Martin Hepp, creator of the Good Relations ontology

64 Incremental development Implementing semantic and linked data technologies should be: Non-invasive Agile Low impact (on staff – hopefully, high impact on users!)

65 Looking to the future What would Cochrane data “look like” outside of it’s container, the Review?

66 Risk of Bias in PubMed For example: someone who is looking at a study in PubMed might be interested in seeing Cochrane’s Risk of Bias assessment of this study, regardless of whether they are interested in the overall Cochrane Review that includes that study.

67 RoB assessment in PubMed

68 Summary Linked Data or Web 3.0 is here How can we leverage these tools to further our mission Requires that we think differently about the “container“ of the Review Our data needs to become “nimble“ to meet future user needs We should proceed slowly, incrementally What are the “quick wins“ – Links to CRS? Across-Review queries? Links to external datasets

69 EbHC Semantic Platform CDSR CRS/ CENTRAL DARE HTAs CMR

70 EbHC Semantic Platform CDSR CRS/ CENTRAL DARE HTAs CMR Drug Bank UMLS Diseasome Symptom Ontology * BBC Health Ontology * Not yet created

71 Cochrane and EbHC ontology?

72 Will Cochrane have a bubble here someday?

73 Muchas Gracias!


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