1. Altmetrics: a primer Where does the data come from? Can it be gamed? Buy in or build your own? Mike Taylor Research Specialist http://orcid.org/0000-0002-8534-5985 mi.taylor@elsevier.com

2. Alternative metrics, altmetrics, article data, usage data, assessments, metrics, impact, understanding, attention, reach… If this seems confusing… Altmetrics is at the big bang stage – this universe has not yet cooled down and coalesced Some words on terms

3. A set of altmetric data is about a common document and represents usage, recommendation, shares, re-usage Identified by DOI, URL, shortened URL, other ID (eg Arxiv, Pubmed) It does not show common intent: a tweet is not the same as a Mendeley share is not the same as a Data Dryad data download is not the same as mass media coverage or a blog What is the data?

4. Altmetric.com Kudos Plum Analytics PLOS / PLOS code Impactstory.org Altmetrics is not Altmetric.com Each has strengths and weaknesses, no canonical source Various providers…

5. Scopus donut Sciencedirect Scival and Pure We’re looking to improve the ‘donut’ “Altmetric.com score” can probably be more useful Elsevier uses Altmetric.com

6. Altmetrics isn’t one thing, so attempting to express it as one thing will fail. We favour intelligent clusters of data: social activity, mass media, scholarly activity, scholarly comment, re-use Elsevier believes that more research is needed, and that best indicators are scholarly activity and scholarly comment Bringing together sources…

7. The more data we can see The bigger the picture

8. If people take this data seriously, will they cheat? Eg, Brazilian citation scandal, strategies used by people to increase IF of journals Expertise in detecting fraudulent downloads (eg, SSRN), self-tweeting – when is ‘normal’ corrupt? One thing to buy 1000 tweets, another to buy 10 blogs, or mass media coverage Do those twitter accounts have scholarly followers? Pattern analysis, usage analysis, network analysis Public data = public analysis = public response Gaming / cheating

9. Biggest criticisms are when people try and conflate all the data into a single thing Easy point of attack – tweets are all about “sex and drugs and rock ‘n’ roll papers”* Using clusters is more intelligible to academic community – eg, re-use, scholarly activity, scholarly comment (blogs, reviews, discussions) * this isn’t true anyway Other criticisms

10. Altmetrics has got where it is today on the basis of standards Without ISSNs and DOIs, the world is a harder place x 1000 Elsevier is supporting research to discover scholarly impact in areas that don’t use DOIs (Other standards exist: PubMed IDs, Arxiv IDs) Making altmetrics work

11. Increasingly, we’re seeing altmetrics being used to describe objects other than articles, but also institutions, books, journals, data and people For institutions, Snowball Metrics has recently adopted the same formulation for grouping altmetrics as Elsevier (www.snowballmetrics.com)www.snowballmetrics.com Expanding views of altmetrics

12. More funders are insisting on open data And the way to understand whether its being used … is data metrics – combining altmetrics and traditional (web-o-)metrics Downloads, citations, shares, re-uses… Downside: data repository is fragmented, 600+ repositories registered at databib.org Upside: Datacite, ODIN, ORCID, DOI, RDA, Draft Declaration of Data Citation Principles Draft Declaration of Data Citation Principles Making data count

13. Governments don’t operate like scholars Rhetoric, argument, polemics Personal reputation is important Laws don’t contain citations The relationship is fuzzy – less a chain of evidence, more a miasma of influence Elsevier is sponsoring work to understand this relationship Measuring the effect of research on society

14. Being deployed across our platforms Engaging with thought leadership Promoting open metrics Acceptance research Academic research Sponsoring research in cutting-edge technology LibraryConnect, www.researchtrends.com Elsevier and alternative metrics