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Chitty taxonomy boot camp best practices final 2017 oct
1. Taxonomy for
Emerging Technologies:
Mary Chitty, MSLS, Library Director & Taxonomist, Knowledge & Information Services
Cambridge Healthtech, Needham MA | www.healthtech.com
mchitty@healthtech.com 781 972-5416 | www.genomicglossaries.com
TODAY’S SCIENCE FICTION CAN BE TOMORROW’S SCIENCE
A Division of Cambridge Innovation Institute
2. In-house database
taxonomy
Home-grown SQL database
1991 CEO created structure for
keywords – Still involved with
identifying and creating new terms
2011 Major reorganization into 25 top
level categories
2017 Nearly 1,600 concepts and
synonyms
Database 2.0 in planning
Looking into new software options
Public website www.genomicglossaries.com
SharePoint intranet
2015 Company migrated
to SharePoint intranet
2017 Summer Knowledge &
Information Services portal
launched
Developing resources on using and
training about in-house keywords
and database
All very technical complex
terminology
1999 Started as a small glossary based on content from in-house taxonomy
2000 Launched as website
2001 Renamed Glossaries & Taxonomies
June Reviewed by Science magazine – a nice surprise!
MyTaxonomies
3. CaseStudy
Search works best IF:
1. You know what to call what you're looking for AND
2. You know what you're looking for exists.
Often neither one is certain for my topics. So …
1999, created glossaries on DNA and proteins for new market research products.
Really interested in poly-hierarchical and non-hierarchical relationships
-- not easily curated!
2000, when websites were still new, realized this could be a solution to update and
share my terms. This website could be valuable to others.
My company is in the information overload business, but we get overloaded too.
In 2017, major Updates including Ontologies & Taxonomies.
http://www.genomicglossaries.com/content/ontologies.asp
www.GenomicsGlossaries.com
4. Start small
Because you’re going to make changes
Call projects prototype/s or proof/s of concept as long as possible
Break daunting project revisions and updates into small
manageable chunks
Look for quick wins
Maximum effect with limited effort
More complicated projects can
come later
Knowledge and credibility gained by
rapid prototyping
Seek metrics feedback
anywhere and everywhere
Qualitative and quantitative
Google Analytics for usage metrics
Welcome questions and emails
from users
Look for reviews and accolades
BestPractices
to Start
5. Both NIH through the Big Data to Knowledge Program and the
European Commission with Horizon 2020 have allocated
considerable resources to making data FAIRer.
FAIR DATA
FAIR Data Principles, 2017 short with link to long version
https://www.force11.org/group/fairgroup/fairprinciples
FAIR Guiding Principles for scientific data management and
stewardship Sci Data. 2016; 3: 160018. Published online 2016
Mar15. doi: 10.1038/sdata.2016.18
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4792175/
Opportunities
fortaxonomists
&ontologists
Findable
Accessible
Interoperable
Reusable
6. LessonsLearned
USEFUL INSIGHTS
Take advantage of modularity & reusability. Don’t re-invent the wheel.
Descriptive not prescriptive definitions, if any.
Packaging and labels matter. Taxonomies or ontologies sound sexier than
thesauri or controlled vocabularies
Taxonomies inherently get more and more granular. Keep editing!
REMEMBER
Don't try to boil the ocean.
80/20 rule or the Pareto principal
Focus on 20% of effort with 80% of usage – not the other way around.
Relevance is inherently subjective. What do your users value most?
7. MyOngoing
Challenges
in2017
even after years of experience!
MAINTENANCE AND UPKEEP
Integration
Topics morph in new directions & into new disciplines
Interoperability & reusability
Huge challenges still
Scalability
Balance short term & long term needs & goals
RETURN ON INVESTMENT
Complexity and information overload trade-offs
Out-of-the-Box vs. Configurability vs. Customization
More programming = more $ - Choose software wisely
People can’t buy your products if they don’t know they exist,
or where to find them.
8. TakeHome
Messages
Choose challenging – but not impossible projects.
Look for allies and buy-in to help make sustainable
progress.
Use metrics and feedback to measure progress, so you
know when you've made some.
Share best practices, lessons learned and ongoing
challenges. Acknowledge issues nobody has resolved
yet, so you don't get discouraged.
Focus
Notas del editor
Hello and welcome. I'm Mary Chitty and have been the Knowledge Information Services Director at Cambridge Healthtech since it was founded in 1992.
My company produces meetings on new and emerging technologies and informatics for pharmaceuticals and biotechnology
Ones with commercial potential – often early or seed stage, but beyond basic research.
My Public website is the taxonomy I’m talking about today.
It and the in-house versions are based on the same content
Use similar, and highly technical terms and concepts.
Am not talking much about my specific subject matter, since that wouldn’t be relevant for some, perhaps many of you.
But the challenges of addressing a variety of users, with varying depth of knowledge about a topic may well be of interest. I
I want to tell you my own taxonomy story
When I started working on my glossaries I used Word documents to collect terms and definitions and wanted to share these.Websites were pretty new and I wanted and got one.I thought things would be changing so fast a website would be the only way to keep up. Very little became “wrong” or obsolete, things just got more and more granular. To this day I still refer to some of my original content. But pruning and editing content is a major challenge. I have over 5000 terms , relationships and cross references to manage. My taxonomies inform my own search strategies and helps me offer advice on product titles and SEO.Found I could have longer better conversations with PhD scientists and not run out of things to say after 30 second.. Can ask better questions.
Taxonomies are important wayfinding guides for elusive information, and one way to keep up with “synonyms” and variant terms . My taxonomy helps inform my own search strategies and helps me offer advice on product titles and SEO.
Trying to understand and coordinate all this technical material... What starts out in one direction and then launch into unexpected directions
Found with my taxonomy work I could talk to PhD scientists – both in-house experts and customers, without running out of ideas after 30 seconds. Can ask better questions and understand nuanced relationships.Examples of non-intuitively related terms – personalized medicine, molecular diagnostics, cancer moonshot etc. Still trying to figure out how to categorize microbiomes and how they fit into oncology as well as gut health and antibiotic drug resistance.
I’m very interested in how individual concepts change in unexpected ways.
The science I’m working with is not textbook science, but rather cutting edge to bleeding edge science. But would be happy to have individual discussions about the challenges of highly technical and inter-disciplinary subject taxonomies and ontologies.
I learned about FAIR data this spring, when Ontoforce, a Belgian semantic search engine company I’ve been collaborating with helped my company organize a FAIR Data hackathon in BostonI love the idea of making data – and content – more Findable, Accessible, Interoperable and Reusable. The European Commission estimates €2 billion in Horizon 2020 funding will be allocated The NIH Data Commons Pilot Phase has an estimated total budget of approximately $55.5 MillionRecent estimates of open repositories include “41% of their data are findable and 76% are accessible, but only 38% are interoperable and 18% reusable”. https://www.force11.org/fairprinciples Ontologies – and taxonomies are ways of bridging the data and content in existing {sometimes competing] databases to enable creative reuse of existing data. The reproducibility crisis in science and medicine has made interoperability and reusability challenges more pressing than ever.
Taxonomist or ontologist may not be in specific job titles, but our skills are needed. One of the ironies of big data is that we need even more of it. We also need increased attention to data quality and integrity. Some data is so poor it should be discarded. And free-text text-mining offers some of the greatest challenges of all.
I’m grateful for organizations that try to create prescriptive definitions, but they usually take years to produce results. What I’m working on needs to be categorized RIGHT NOW. Those categories may change. I’m still trying to fully understand microbiomes, which started out in the context of microbes inhabiting our gut and skin and their health effects, but have recently started showing up in cancer research. Labels matter. When I renamed my glossaries "glossaries and taxonomies" our IT guy said “You have real content – not just that marketing fluff!” I love the 80/20 rule. Don’t let the perfect be the enemy of the good. And don’t spend too much time on the 20% no matter how interesting it may be,
Maintenance and scalability are huge and often underestimated issues.Many decisions involve complex trade-offs. Gardeners know the lure of wanting fast growing plants that look great quickly as you begin your work. But in the long run some plants or trees become invasive and too big – and expensive or impossible to remove. Reusing existing taxonomies or ontologies Often none of them will precisely fit your individual needs. You can use parts of them and learn from them.
Not just about technologies. But how people use and implement technologies
Don’t try to do this all by yourself.
Less is more, even though it can take longer to shorten content -- and in some cases threatens to break the moving parts of an existing system. Thank you for your time and attention. My name is Mary Chitty. I will be here the rest of today and all day Tuesday and look forward to talking with you. I’m here to learn and figure out what to do next. Please take one of my cards with my information and links to more about FAIR data.