Making research findings visible – the future of the scientific paper Matthew Cockerill Publisher, BioMed Central.

Making research findings visible – the future of the

scientific paper

Matthew CockerillPublisher, BioMed Central

"There is nothing more amusing than watching business interests work themselves up into a righteous frenzy over a threat to their monopoly profits from a new technology or some upstart with a different business model. Invariably, the monopolists… try to present themselves as champions of the consumer, or defenders of a level playing field, as if they hadn't become ridiculously rich by sticking it to consumers and enjoying years in which the playing field was tilted to their advantage."

Steven Pearlstein in the Washington Post, July 19 2006

Status of open access publishing

Momentum for transition to OA

We are seeing action (not just words) from funding agencies and governments– Wellcome and several UK research councils now require OA

deposit as a condition of grants– Federal Research Public Access Act may do the same in US

OA journals continue to grow rapidly Impressive impact factors demonstrate OA and

quality are absolutely compatible Move to OA basically unstoppable

Growth of OARolling 28-day count of submissions to BioMed Central

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Submissions

Impact factors

Genome Biology – IF 9.71 BMC Bioinformatics – IF 4.96 BMC Genomics – IF 4.09

Genome Biology is: 10th of 124 in GENETICS & HEREDITY 4th of 139 in BIOTECHNOLOGY & APPLIED MICROBIOLOGY

What does this mean for the future of the scientific article?

Why did we start BioMed Central as an open access publisher?

Limited access to research articles makes further research needlessly inefficient

Barriers to access obstruct interdisciplinary cross-fertilization

It is in the interest of researchers for their research being read and cited as widely as possible

Traditional scientific publishing is not an effective market, and so high serials prices mean a poor deal for the scientific community

The main reason we started BioMed Central

Publications and data are a continuum Publications include data Publications are data To make sense of data and publications delivered by

post-genomic science, we need– The best possible tools– The widest possible collection of raw material

Open access stimulates the creation of tools by providing access to the raw material

The future of the scientific article

Computers will be at least as important as human readers

Text mining

Open access facilitates text mining BioMed Central XML corpus of full

text articles is freely downloadable The more semantics that are

captured in the XML, the richer the possibilities for mining

Existing examples of automated sifting of published research

Postgenomic

CiteULike

This is just bibliographic information –

but it's a start

Semantic enrichment Ensure that the rest of the knowledge

represented in scientific articles is structured to be computer-readable

Ideally capture semantics unambiguously at time of publication

Mining of free text is a stopgap/fall-back It is not just articles that need semantic

enrichment, but data sets too Appropriate standards are now emerging

RDF

Useful common technical standard for expressing semantics

Subject-predicate-object triples BioMed Central already exposes

bibliographic RDF for all articles Tools like the PiggyBank can

capture RDF and then store it in triple-stores (local or networked)

Semantic Laundry List Scientific stuff

– Genes– Proteins– Anatomy– Taxonomy– Small molecules/drugs– Macromolecules– Diseases– Experimental methodologies– Experimental data types

General stuff– People, Places, Organizations, Relationships

NCBO

e.g. of enriched research

Neurocommons.org

A ScienceCommons project Working with open access articles

from BioMed Central and PLoS Attempting to define best

practices/gold standard for semantic enrichment of articles

Text mining and enhanced authoring tools both have role

The role of wikis

The challenge: Ontologies, to be useful, must stay up-to-date and receive ongoing maintenance and curation

Scope of problem is enormous - every entity and relationship of relevance to science

Wikis provide a promising approach - perhaps the only viable approach

e.g. AuthorIDs

Projects at BioMed Central to capture structured info

Case reportsClinical trialsBiological processesChemical structuresTaxonomic descriptions

Publishing research articles in a more structured form allows the results to be treated as a database

Structured authoring

Publicon – an experiment in structured authoring

Benefits of structure

Live maths in articles

Live maths in articles

Problem – adding structure is a hassle

Incentivize authors

Ideally, create structured authoring tools that remove work rather than add it (e.g. EndNote)

If you do create extra work for authors, find a way to provide the author with an immediate return on investment

Reduce work - smart authoring e.g. auto suggest

Standard way to disambiguate contacts Why not chemicals, genes, species too?

– Unambiguously capture semantics– Increase accuracy, save time, encourage uptake

Return on investment

Automatic update of meta-analysis based on clinical trial data

Automatic list of closely-related case reports from database

Automatic deposit of taxonomic information in registry (Zoobank)

Q & A