In looking over the past recipients, few would argue that the award has not been given out to major contributors to the open source/open access movements in biology. In thinking about who might be appropriate to add to this list, two people sprang to mind who I’ve had the good fortune to work with in the past, both of whom have made a major impresion on my (and many others’) thinking and working practices in computational biology.  So without further ado, here are my nominations for the 2012 Benjamin Franklin Award for Open Access in the Life Sciences (in chronological order of my interaction with them)…

Suzanna Lewis

Suzanna Lewis (Lawrence Berkeley National Laboratory) is one of the pioneers of developing open standards and software for genome annotation and ontologies. She led the team repsonsible for the systematic annotation of the Drosophila melanogaster genome, which included development of the Gadfly annotation pipeline and database framework, and the annotation curation/visualization tool Apollo. Lewis’ work in genome annotation also includes playing instrumental roles in the GASP community assessement exercises to evaluate the state of the art in genome annotation, development of the Gbrowser genome browser, and the data coordination center for modENCODE project. In addition to her work in genome annotation, Lewis has been a leader in the development of open biological ontologies (OBO, NCBO), contributing to the Gene Ontology, Sequence Ontology, and Uberon anatomy ontologies, and developing open software for editing and navigating ontologies (AmiGO, OBO-Edit, and Phenote).

Carole Goble

Carole Goble (University of Manchester) is widely recognized as a visionary in the development of software to support automated workflows in biology. She has been a leader of the myGrid and Open Middleware Infrastructure Institute consortia, which have generated a large number of highly innovative open resources for e-research in the life sciences including the Taverna Workbench for developing and deploying workflows, the BioCatalogue registry of bioinformatics web services, and the social-networking inspired myExperiment workflow repository. Goble has also played an instrumental role in the development of semantic-web tools for constructing and analyzing life science ontologies, the development of ontologies for describing bioinformatics resources, as well as ontology-based tools such as RightField for managing life science data.

I hope others join me in acknowledging the outputs of these two open innovators as being more than worthy of the Franklin Award, support their nomination, and cast votes in their favor this year and/or in years to come!

However, from a text-miner’s perspective author-deposited manuscripts in PMC are closed access since, while they can be downloaded and read individually, virtually none (<200) are available from the PMC’s Open Access subset that includes all articles that are free (libre) to download in bulk and text/data mine. This includes ~99% of the author deposited manuscripts from the journal Nature, despite a clear statement from 2009 entitled “Nature Publishing Group allows data- and text-mining on self-archived manuscripts”. In short, funder mandates only make manuscripts public but not open, and thus whether the RWA is passed or not is actually moot from a text/data-mining perspective.

Why is this important? The simple reason is that there are currently only ~400,000 articles in the PMC Open Access subset, and therefore author-deposited manuscripts are only two-fold less abundant than all articles currently available for text/data-mining. Thus what could be a potentially rich source of data for large-scale information extraction remains locked away from programmatic analysis. This is especially tragic considering the fact that at the point of manuscript acceptance, publishers have invested little-to-nothing into the publication process and their claim to copyright is most tenuous.

So instead of discussing whether we should support the status quo of weak funder mandates by working to block the RWA or expand NIH-like mandates (e.g. as under the Federal Research Public Access Act, FRPAA), the real discussion that needs to be had is how to make funder mandates stronger to insist (at a minimum) that author-deposited manuscripts be available for text/data-mining research. More-of-the same, not matter how much, only takes us half the distance towards the ultimate goals of the Open Access movement, and doesn’t permit the crucial text/data mining research that is needed to make sense of the deluge of information in the scientific literature.

Credits: Max Haussler for making me aware of the lack of author manuscripts in PMC a few years back, and Heather Piwowar for recently jump-starting the key conversation on how to push for improved text/data mining rights in future funder mandates.

Related Posts:

• Be openly accessible or be obscure - A taxonomy of articles in PubMed Central

@David_S_Bristol @caseybergman You're free to reproduce personal evaluations on institutional&personal blogs if you clearly reference F1000.—
Faculty of 1000 (@F1000) January 06, 2012

As such, I am delighted to be able to repost here an Open Archive of my F1000 contributions. Additionally, this post acts in a second capacity as my first contribution to the Research Blogging Network. Hopefully these commentraies will be of interest to some, and should add support to the Altmetrics profiles for these papers through systems like Total Impact.

Nelson CE, Hersh BM, & Carroll SB (2004). The regulatory content of intergenic DNA shapes genome architecture. Genome biology, 5 (4) PMID: 15059258

My review: This article reports that genes with complex expression have longer intergenic regions in both D. melanogaster and C. elegans, and introduces several innovative and complementary approaches to quantify the complexity of gene expression in these organisms. Additionally, the structure of intergenic DNA in genes with high complexity (e.g. receptors, specific transcription factors) is shown to be longer and more evenly distributed over 5′ and 3′ regions in D. melanogaster than in C. elegans, whereas genes with low complexity (e.g. metabolic genes, general transcription factors) are shown to have similar intergenic lengths in both species and exhibit no strong differences in length between 5′ and 3′ regions. This work suggests that the organization of noncoding DNA may reflect constraints on transcriptional regulation and that gene structure may yield insight into the functional complexity of uncharacterized genes in compact animal genomes. (@F1000: http://f1000.com/1032936)

Li R, Ye J, Li S, Wang J, Han Y, Ye C, Wang J, Yang H, Yu J, Wong GK, & Wang J (2005). ReAS: Recovery of ancestral sequences for transposable elements from the unassembled reads of a whole genome shotgun. PLoS computational biology, 1 (4) PMID: 16184192

My review: This paper presents a novel method for automating the laborious task of constructing libraries of transposable element (TE) consensus sequences. Since repetitive TE sequences confound whole-genome shotgun (WGS) assembly algorithms, sequence reads from TEs are initially screened from WGS assemblies based on overrepresented k-mer frequencies. Here, the authors invert the same principle, directly identifying TE consensus sequences from those same reads containing high frequency k-mers. The method was shown to identify all high copy number TEs and increase the effectiveness of repeat masking in the rice genome. By circumventing the inherent difficulties of TE consensus reconstruction from erroneously assembled genome sequences, and by providing a method to identify TEs prior to WGS assembly, this method provides a new strategy to increase the accuracy of WGS assemblies as well as our understanding of the TEs in genome sequences. (@F1000: http://f1000.com/1031746)

Rifkin SA, Houle D, Kim J, & White KP (2005). A mutation accumulation assay reveals a broad capacity for rapid evolution of gene expression. Nature, 438 (7065), 220-3 PMID: 16281035

My review: This paper reports empirical estimates of the mutational input to gene expression variation in Drosophila, knowledge of which is critical for understanding the mechanisms governing regulatory evolution. These direct estimates of mutational variance are compared to gene expression differences across species, revealing that the majority of genes have lower expression divergence than is expected if evolving solely by mutation and genetic drift. Mutational variances on a gene-by-gene basis range over several orders of magnitude and are shown to vary with gene function and developmental context. Similar results in C. elegans [1] provide strong support for stabilizing selection as the dominant mode of gene expression evolution. (@F1000: http://f1000.com/1040157)

References: 1. Denver DR, Morris K, Streelman JT, Kim SK, Lynch M, & Thomas WK (2005). The transcriptional consequences of mutation and natural selection in Caenorhabditis elegans. Nature genetics, 37 (5), 544-8 PMID: 15852004

Caspi A, & Pachter L (2006). Identification of transposable elements using multiple alignments of related genomes. Genome research, 16 (2), 260-70 PMID: 16354754

My review: This paper reports an innovative strategy for the de novo detection of transposable elements (TEs) in genome sequences based on comparative genomic data. By capitalizing on the fact that bursts of TE transposition create large insertions in multiple genomic locations, the authors show that detection of repeat insertion regions (RIRs) in alignments of multiple Drosophila genomes has high sensitivity to identify both individual instances and families of known TEs. This approach opens a new direction in the field of repeat detection and provides added value to TE annotations by placing insertion events in a phylogenetic context. (@F1000 http://f1000.com/1049265)

Simons C, Pheasant M, Makunin IV, & Mattick JS (2006). Transposon-free regions in mammalian genomes. Genome research, 16 (2), 164-72 PMID: 16365385

My review: This paper presents an intriguing analysis of transposon-free regions (TFRs) in the human and mouse genomes, under the hypothesis that TFRs indicate genomic regions where transposon insertion is deleterious and removed by purifying selection. The authors test and reject a model of random transposon distribution and investigate the properties of TFRs, which appear to be conserved in location across species and enriched for genes (especially transcription factors and micro-RNAs). An alternative mutational hypothesis not considered by the authors is the possibility for clustered transposon integration (i.e. preferential insertion into regions of the genome already containing transposons), which may provide a non-selective explanation for the apparent excess of TFRs in the human and mouse genomes. (@F1000: http://f1000.com/1010399)

Wheelan SJ, Scheifele LZ, Martínez-Murillo F, Irizarry RA, & Boeke JD (2006). Transposon insertion site profiling chip (TIP-chip). Proceedings of the National Academy of Sciences of the United States of America, 103 (47), 17632-7 PMID: 17101968

My review: This paper demonstrates the utility of whole-genome microarrays for the high-throughput mapping of eukaryotic transposable element (TE) insertions on a genome-wide basis. With an experimental design guided by first computationally digesting the genome into suitable fragments, followed by linker-PCR to amplify TE flanking regions and subsequent hybridization to tiling arrays, this method was shown to recover all detectable TE insertions with essentially no false positives in yeast. Although limited to species with available genome sequences, this approach circumvents inefficiencies and biases associated with the alternative of whole-genome shotgun resequencing to detect polymorphic TEs on a genome-wide scale. Application of this or related technologies (e.g. [1]) to more complex genomes should fill gaps in our understanding of the contribution of TE insertions to natural genetic variation. (@F1000: http://f1000.com/1088573)

References: 1. Gabriel A, Dapprich J, Kunkel M, Gresham D, Pratt SC, & Dunham MJ (2006). Global mapping of transposon location. PLoS genetics, 2 (12) PMID: 17173485

Haag-Liautard C, Dorris M, Maside X, Macaskill S, Halligan DL, Houle D, Charlesworth B, & Keightley PD (2007). Direct estimation of per nucleotide and genomic deleterious mutation rates in Drosophila. Nature, 445 (7123), 82-5 PMID: 17203060

My review: This paper presents the first direct estimates of nucleotide mutation rates across the Drosophila genome derived from mutation accumulation experiments. By using DHPLC to scan over 20 megabases of genomic DNA, the authors obtain several fundamental results concerning mutation at the molecular level in Drosophila: SNPs are more frequent than indels; deletions are more frequent than insertions; mutation rates are similar across coding, intronic and intergenic regions; and mutation rates may vary across genetic backgrounds. Results in D. melanogaster contrast with those obtained from mutation accumulation experiments in C. elegans (see [1], where indels are more frequent than SNPs, and insertions are more frequent than deletions), indicating that basic mutation processes may vary across metazoan taxa. (@F1000: http://f1000.com/1070688)

References: 1. Denver DR, Morris K, Lynch M, & Thomas WK (2004). High mutation rate and predominance of insertions in the Caenorhabditis elegans nuclear genome. Nature, 430 (7000), 679-82 PMID: 15295601

Katzourakis A, Pereira V, & Tristem M (2007). Effects of recombination rate on human endogenous retrovirus fixation and persistence. Journal of virology, 81 (19), 10712-7 PMID: 17634225

My review: This study shows that the persistence, but not the integration, of long-terminal repeat (LTR) containing human endogenous retroviruses (HERVs) is associated with local recombination rate, and suggests a link between intra-strand homologous recombination and meiotic exchange. This inference about the mechanisms controlling the transposable element (TE) abundance is obtained by demonstrating that total HERV density (full-length elements plus solo LTRs) is not correlated with recombination rate, whereas the ratio of full-length HERVs relative to solo LTRs is. This work relies critically on advanced computational methods to join TE fragments, demonstrating the need for such algorithms to make accurate inferences about the evolution of mobile DNA and to reveal new insights into genome biology. (@F1000: http://f1000.com/1091037)

Giordano J, Ge Y, Gelfand Y, Abrusán G, Benson G, & Warburton PE (2007). Evolutionary history of mammalian transposons determined by genome-wide defragmentation. PLoS computational biology, 3 (7) PMID: 17630829

My review: This article reports the first comprehensive stratigraphic record of transposable element (TE) activity in mammalian genomes based on several innovative computational methods that use information encoded in patterns of TE nesting. The authors first develop an efficient algorithm for detecting nests of TEs by intelligently joining TE fragments identified by RepeatMasker, which (in addition to providing an improved genome annotation) outputs a global “interruption matrix” that can be used by a second novel algorithm which generates a chronological ordering of TE activity by minimizing the nesting of young TEs into old TEs. Interruption matrix analysis yields results that support previous phylogenetic analyses of TE activity in humans but are not dependent on the assumption of a molecular clock. Comparison of the chronological orders of TE activity in six mammalian genomes provides unique insights into the ancestral and lineage-specific record of global TE activity in mammals. (@F1000: http://f1000.com/1089045)

Schuemie MJ, & Kors JA (2008). Jane: suggesting journals, finding experts. Bioinformatics (Oxford, England), 24 (5), 727-8 PMID: 18227119

My review: This paper introduces a fast method for finding related articles and relevant journals/experts based on user input text and should help improve the referencing, review and publication of biomedical manuscripts. The JANE (Journal/Author Name Estimator) method uses a standard word frequency approach to find similar documents, then adds the scores in the top 50 records to produce a ranked list of journals or authors. Using either the abstract or full-text, JANE suggested quite sensible journals and authors in seconds for a manuscript we have in press, while the related eTBLAST method [1] failed to complete while I wrote this review. JANE should prove to be a very useful text mining tool for authors and editors alike. (@F1000: http://f1000.com/1101037)

References: 1. Errami M, Wren JD, Hicks JM, & Garner HR (2007). eTBLAST: a web server to identify expert reviewers, appropriate journals and similar publications. Nucleic acids research, 35 (Web Server issue) PMID: 17452348

Pask AJ, Behringer RR, & Renfree MB (2008). Resurrection of DNA function in vivo from an extinct genome. PloS one, 3 (5) PMID: 18493600

My review: This paper reports the first transgenic analysis of a cis-regulatory element cloned from an extinct species. Although no differences were seen in the expression pattern of the collagen (Col2A1) enhancer from the extinct Tasmanian tiger and extant mouse, this work is an important proof of principle for using ancient DNA in the evolutionary analysis of gene regulation. (@F1000: http://f1000.com/1108816)

Ginsberg J, Mohebbi MH, Patel RS, Brammer L, Smolinski MS, & Brilliant L (2009). Detecting influenza epidemics using search engine query data. Nature, 457 (7232), 1012-4 PMID: 19020500

My review: A landmark paper in health bioinformatics demonstrating that Google searches can predict influenza trends in the United States. Predicting infectious disease outbreaks currently relies on patient reports gathered through clinical settings and submitted to government agencies such as the CDC. The possible use of patient “self-reporting” through internet search queries offers unprecedented real-time access to temporal and regional trends in infectious diseases. Here, the authors use a linear modeling strategy to learn which Google search terms best correlate with regional trends in influenza-related illness. This model explains flu trends over a 5 year period with startling accuracy, and was able to predict flu trends during 2007-2008 with a 1-2 week lead time ahead of CDC reports. The phenomenal use of crowd-based predictive health informatics revolutionizes the role of the internet in biomedical research and will likely set an important precedent in many areas of natural sciences. (@F1000: http://f1000.com/1127181)

Taher L, & Ovcharenko I (2009). Variable locus length in the human genome leads to ascertainment bias in functional inference for non-coding elements. Bioinformatics (Oxford, England), 25 (5), 578-84 PMID: 19168912

My review: This paper raises the important observation that differences in the length of genes can bias their functional classification using the Gene Ontology, and provides a simple method to correct for this inherent feature of genome architecture. A basic observation of genome biology is that genes differ widely in their size and structure within and between species. Understanding the causes and consequences of this variation in gene structure is an open challenge in genome biology. Previously, Nelson and colleagues [1] have shown, in flies and worms, that the length of intergenic regions is correlated with the regulatory complexity of genes and that genes from different Gene Ontology (GO) categories have drastically different lengths. Here, Taher and Ovcharenko confirm this observation of functionally non-random gene length in the human genome, and discuss the implications of this feature of genome organization on analyses that employ the GO for functional inference. Specifically, these authors show that random selection of noncoding DNA sequences from the human genome leads to the false inference of over- and under-representation of specific GO categories that preferentially contain longer or shorter genes, respectively. This finding has important implications for the large number of studies that employ a combination of gene expression microarrays and GO enrichment analysis, since gene expression is largely controlled by noncoding DNA. The authors provide a simple method to correct for this bias in GO analyses, and show that previous reports of the enrichment of “ultraconserved” noncoding DNA sequences in vertebrate developmental genes [2] may be a statistical artifact. (@F1000: http://f1000.com/1157594)

References: 1. Nelson CE, Hersh BM, & Carroll SB (2004). The regulatory content of intergenic DNA shapes genome architecture. Genome biology, 5 (4) PMID: 15059258

2. Bejerano G, Pheasant M, Makunin I, Stephen S, Kent WJ, Mattick JS, & Haussler D (2004). Ultraconserved elements in the human genome. Science (New York, N.Y.), 304 (5675), 1321-5 PMID: 15131266

Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, Collins FS, & Manolio TA (2009). Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proceedings of the National Academy of Sciences of the United States of America, 106 (23), 9362-7 PMID: 19474294

My review: This article introduces results from human genome-wide association studies (GWAS) into the realm of large-scale functional genomic data mining. These authors compile the first curated database of trait-associated single-nucleotide polymorphisms (SNPs) from GWAS studies (http://www.genome.gov/gwastudies/) that can be mined for general features of SNPs underlying phenotypes in humans. By analyzing 531 SNPs from 151 GWAS studies, the authors discover that trait-associated SNPs are predominantly in non-coding regions (43% intergenic, 45% intronic), but that non-synonymous and promoter trait-associated SNPs are enriched relative to expectations. The database is actively maintained and growing, and currently contains 3943 trait-associated SNPs from 796 publications. This important resource will facilitate data mining and integration with high-throughput functional genomics data (e.g. ChIP-seq), as well as meta-analyses, to address important questions in human genetics, such as the discovery of loci that affects multiple traits. While the interface to the GWAS catalog is rather limited, a related project (http://www.gwascentral.org/) [1] provides a much more powerful interface for searching and browsing data from the GWAS catalog. (@F1000: http://f1000.com/8408956)

References: 1. Thorisson GA, Lancaster O, Free RC, Hastings RK, Sarmah P, Dash D, Brahmachari SK, & Brookes AJ (2009). HGVbaseG2P: a central genetic association database. Nucleic acids research, 37 (Database issue) PMID: 18948288

Tamames J, & de Lorenzo V (2010). EnvMine: a text-mining system for the automatic extraction of contextual information. BMC bioinformatics, 11 PMID: 20515448

My review: This paper describes EnvMine, an innovative text-mining tool to obtain physico-chemical and geographical information about environmental genomics samples. This work represents a pioneering effort to apply text-mining technologies in the domain of ecology, providing novel methods to extract the units and variables of physico-chemical entities, as well as link the location of samples to worldwide geographic coordinates via Google Maps. Application of EnvMine to full-text articles in the environmental genomics database envDB {1} revealed very high system performance, suggesting that information extracted by EnvMine will be of use to researchers seeking meta-data about environmental samples across different domains of biology. (@F1000: http://f1000.com/3502956)

References: 1. Tamames J, Abellán JJ, Pignatelli M, Camacho A, & Moya A (2010). Environmental distribution of prokaryotic taxa. BMC microbiology, 10 PMID: 20307274

However the most recent reply I received from Dr. Herbet Macgregor troubled me (below), since I think it reveals many of the misconceptions and challenges (see points 2 and 9 especially) that we are up against in terms of getting our peers and colleagues to understand the principles of the Open Access movement. Nevertheless, it is clear that my refusal to review in this case has made some small progress — with Springer’s Open Access policy being more clearly displayed on the Chromosome Research home page, and internal dialogue about the Open Access issue being raised by the journal staff.

I will continue to post similar refusual replies, so that the dialogue on this issue is made more transparent for those involved in the Open Access movement.

And remember to keep the closed access reviewer boycott alive after the SOPA/PIPA/RWA madness is behind us!

– CMB

From: Herbert Macgregor <herbert.macgregor@xxx.xxx>
Date: 19 January 2012 18:34:18 GMT
To: <casey.bergman@xxx.xxx>
Cc: <conlyrieder@xxx.xxx>, Walther Traut <traut@xxx.xxx>, “Butler, Peter, Springer SBM NL” <Peter.Butler@xxx.xxx>
Subject: Fw: CR

Dear Dr. Bergman,

Professor Walther Traut, one of our Associate Editors has passed your comments on reviewing and Open Access journals to me for comment.

I have the impression that you have joined the current movement in the USA to persuade major science publishers that science should be free for all rather than for sale: a principle that I and my colleagues on Chromosome Research strongly uphold, of course.  I would, however, like to make the following points about your comments to Professor Traut.

(1) How do we manage to get up to 700 downloads of individual papers in just one month if nobody is supposed to be reading them because they’re not OA? look at our website and frequently downloaded papers.

(2)  Where do authors get the money to pay $3000 to pay for OA?  Answer – the taxpayer or the chariity!  Publication in CR is FREE.

(3)  CR does offer Open Choice at the same cost as it would charge for Open Access (too much, I agree, but we’re working on that) – so why do only about 5% of our authors opt for this?

(4) All our authors are recommended to place their papers in their Institutional Repositories and most do (many are required to do so).  They are then freely available world-wide through any of the major search engines – and nobody has to pay anything at all!

(5)  The publication programme for CR is currently incompatible with OA, mainly on account of our Special Issues – which happen to be freely downloadable, courtesy of our publisher.

(6)  The matter of OA for CR is currently under discussion between ourselves (editors) and Springer sbm, with the interests of our authors, readers and chromosome science very much at heart. We are very well aware of all the pros and cons and moral principles and I am confident that our future policy will be very much in keeping with all that is best in modern science publishing.

(7) We are constantly watching the OA debate and we are able to direct Chromosome Research within the framework of modern trends in science publishing.

(8) Although  some of the major science publishers may seem to be profiting from their publication of taxpayer funded science, they nonetheless perform an extremely  valuable and important role and are currently working hard with editors and scientists to adjust to the opportunities and demands of the internet age.

(9) I would suggest that to use the crusade for OA as an excuse for refusing to review is in denial of the responsibilties of a publicly or charitably funded academic and scientist.  OA or not, peer review is at the very epicentre of scientific progress amd we should uphold it, come what may.

(10) We, the editors of CR, would welcome further debate with you, although we would naturally prefer that you devote your valuable time and expertise to helping us with the assessment of manuscripts submitted to our journal.

(11) You may not know that BMC is now owned by Springer, so you can be confident that the incentive to “modernise” is strong!

We are grateful to you for alerting us to the fact that we nowhere declare publicly our journal’s policy with regard to OA.  This we should do without delay.  The essence of it is that we offer authors Open Choice and we encourage them to place their  papers on their institution’s repository. The only restriction on the latter is that they may not use the publisher’s final pdf, which I am sure you will agree is fair enough.  All our Special Issue papers are freely downloadable.

Lastly and from am entirely personal standpoint, you should understand that for/against OA is not a simple black/white issue. I have been publishing in science journals for 53 years and editing them for 40 years and I would ask you to give persons like myself credit for understanding and acting in the best interests of our profession.

With best wishes

Herbert Macgregor
Editor-in-Chief
Chromosome Research

cc Conly Rieder
Co-Editor-in-Chief

cc Prof. Walther Traut
Associate Editor

Over the last two years I have been targetting scientific society’s whose journal’s are not in the tiny fraction of the scientific literature in the PubMed Central Open Access subset, hoping to encourage them to release their content for text-mining research projects in my group (e.g. http://www.text2genome.org). My attitude has been that Society’s are the ones to go after, since they often hold the copyrights and are typically run by colleagues who I can directly appeal to. After productive (yet rather protracted) communication with The Genetics Society of America, the UK Genetics Society and the Society for Molecular Biology and Evolution, we’ve been able to obtain back-content for Genetics, Heredity and Molecular Biology and Evolution for our projects.* Heredity has gone far enough to announce that their content is now open for text-mining research on their home page (victory!)

In stark contrast, a similar line of inquiry with the Ecological Society of America has led to a very sour and unproductive experience which I will summarize here to demonstrate the the ESA’s recent response letter to the OSTP is consistent with a general attitude of protecting their journal content. This narrative echoes Peter Murray-Rust’s painful story of his years negotiating with Elsevier for access to content, which likewise has no positive conclusion.

While Katherine McCarter is true in saying that the ESA publishes a subset of their content under OA licenses, it is not true that this content in is in any meaningful way “open” in a 21st-century, linked-data, remix-and-reuse context. Why? Because like virtually all of the ecological, agricultural and environmental literature, ESA OA content is not deposited in a public archive like PubMed Central, and can only be accessed via the ESA journal website.  However, this content is not accessible to text-mining since the ESA journal permissions clearly state:

Altering, recompiling, systematic or programmatic copying, or reselling of text or other information from ESA Journals in any form or medium is prohibited. Systematic or programmatic downloading, service bureau redistribution services, printing for fee-for-service purposes and/or the systematic making of print or electronic copies for transmission to non-subscribing institutions are prohibited.

Since I have been burned in the past by aggressive closed-access publishers shutting down my office IP for naively downloading content that my univeristy has a site license for, I dutifully went down the proper channel of requesting permissions to automatically download ESA content from the Permissions Editor, Dr. Cliff Duke. For the record, I can say that Dr. Duke has been faultlessly professional throughout the process and was positive about my initial request, an excerpt of which follows:

From: Cliff Duke <CSDuke@xxx.xxx>
Date: 28 June 2011 14:19:18 GMT+01:00
To: Casey Bergman <casey.bergman@xxx.xxx>
Subject: RE: request for permission to use ESA content in text-mining research

Casey,

In answer to your question — not that I recall, but I also don’t recall any previous similar requests, and I’ve been the permissions editor for about seven years. However, I doubt your request will be the last such, given the increasing interest in this kind of research.

Cliff

—–Original Message—–
From: Casey Bergman [mailto:casey.bergman@xxx.xxx]
Sent: Tuesday, June 28, 2011 9:14 AM
To: Cliff Duke
Subject: Re: request for permission to use ESA content in text-mining research

Dear Dr. Duke -

Many thanks for the very quick reply.  I appreciate your efforts in bringing this to the attention of the ESA leadership and I fully understand that this may take some time to sort out (it took several months with GSA).

One quick question at this stage: is there any precedent at ESA for permitting bulk access for text mining research?

Best regards,
Casey

—–Original Message—–
On 28 Jun 2011, at 13:48, Cliff Duke wrote:

Dr. Bergman,

I will discuss your request with our executive director and editors and get back to you as soon as I can. Our director is on travel this week, and I am on vacation next week, so it may be a couple of weeks before you hear back from us. Let me know if you have any questions meanwhile.

Regards,
Cliff Duke

Clifford S. Duke, Ph.D.
Permissions Editor

Ecological Society of America
1990 M Street NW, Suite 700
Washington, DC 20036
Phone: (202) 833-8773
Fax: (202) 833-8775
E-mail: csduke [at] esa.org

—–Original Message—–
From: Casey Bergman [mailto:casey.bergman@xxx.xxx]
Sent: Tuesday, June 28, 2011 8:34 AM
To: Cliff Duke
Subject: request for permission to use ESA content in text-mining research

Dear Dr. Duke -

Greetings, I am a researcher at the University of Manchester, with an interest in application of text and data mining to biological problems at the interface of computational and evolutionary biology. I am writing to request permission to use ESA journal content in text-mining research project that I am developing to submit as proposal to the UK Natural Environment Research Council. Specifically, I would like to request permission to automate download of the entire/the open-access subset of all ESA titles, which I understand is not permitted under the standard ESA policy (http://www.esapubs.org/esapubs/permissions.htm).

[SNIP]

Dr Duke then put me in touch with the Managing Editor of the ESA journals, David Baldwin who promptly ignored my request for several months, despite repeated emails and phone calls on e.g. 6 September 2011, 27 September 2011, 13 October 2011.  I finally received one email from David Baldwin on 20 October 2011, where he promised (but failed) to get back to me a few days later:

From: Casey Bergman <casey.bergman@xxx.xxx>
Date: 20 October 2011 12:42:01 GMT+01:00
To: J David Baldwin <jdb27@xxx.xxx>
Cc: Cliff Duke <csduke@xxx.xxx>
Bcc: Casey Bergman <casey.bergman@xxx.xx>
Subject: Re: request for permission to use ESA content in text-mining research

Dear David -

Many thanks for replying. I fully understand that nonstandard requests can take some time. My previous interactions with Genetics and Heredity have also taken many months to lead to positive decisions on releasing content for text mining research.

All that is required in the short term is explicit permission to execute automated downloads on the www.esajournals.org site that abide by the limits of your systems (<50 sessions in 10 minutes).  No other technical issues need to be addressed on your side.

Also, I am happy in the first instance to restrict automated downloads to the Open Access subset of ESA publications, if a decision to permit access to the entirety of ESA content is more difficult.

Best regards,
Casey

On 20 Oct 2011, at 12:03, J David Baldwin wrote:

Dear Dr. Bergman–

I know you are keen to discuss this, but I’m afraid you have picked a particularly bad week for contacting me. Today (Thursday, 20 October) won’t be any better than the past two days, and tomorrow (Friday) I’ll be out of town. I’ll look over your request before Monday, 24 October, and will e-mail you again by then. I’m afraid I get handed off the nonstandard requests (“the buck stops here”), and yet I have my own priorities (i.e., working to keep the journal issues on schedule).

Cheers,
David

—–Original Message—–
From: Casey Bergman [mailto:casey.bergman@xxx.xxx]
Sent: Thursday, October 13, 2011 9:01 AM
To: J David Baldwin
Cc: Cliff Duke
Subject: Re: request for permission to use ESA content in text-mining research

Dear David -

Would there be a convenient time for you sometime in the next week or so to discuss how we might be able to access ESA content programmatically?  I am +5 hrs to you, so late afternoon for me = morning for you is typically the best timeline to arrange a call.

Best regards,
Casey

Well I can report that as of 6 January 2012, the buck certain has stopped with David Baldwin on this issue, since he still refuses to respond to the most minimal request for permission to automatically download only the Open Access subset of the ESA content. Since no effort is required on his part other than to say “yes”, I take his inaction to speak for the ESA that they have no interest in supporting text and data mining research on their content — even their OA content — which is fully consistent with their specious arguments for protectionism of society subsidies through closed access publishing put forward in their response letter to the OSTP. Given the undeniable importance of data in the ecological literature for science and society, the ESA should be ashamed for locking away this precious resource from the world and being adamant in their position that this is in any way morally or ethically justified.

I look forward to David Baldwin’s response on this request, and hope the the ESA is more progressive in their outlook toward open access publishing and text/data mining in the coming years….

* Credits to Tracey DePellegrin Connelly, Scott Hawley and Lauren McIntrye for helping to free Genetics content;  Roger Butlin for helping free Heredity content; and Ken Wolfe, Soojin Yi and the SMBE council for helping to free MBE content.

Related Posts:

• James and the Giant Corn – Open Access and Ecologists
• Phylogenomics – YHGTBFKM: Ecological Society of America letter regarding #OpenAccess is disturbing
• Legislation in the United States seeks to keep research findings behind paywalls

In the children’s story The Sneetches, Dr. Suess’ presents a world where certain members of society are marked by an arbitrary badge of distinction, and a canny opportunist uses this false basis of prestige for his financial gain*. What does this morality tale have to do with the scientific article recommendation service Faculty of 1000?  Read on…

Currently ~3000 papers are published each day in the biosciences**. Navigating this sea of information to find articles relevant to your work is no small matter. Researchers can either sink or swim with the aid of (i) machine-based technologies based on search or text-mining tools or (ii) human-based technologies like blogs or social networking services that highlight relevant work through expert recommendation.

One of the first expert recommendation services was Faculty of 1000, a service launched in 2002 with the aim of “identifying and evaluating the most significant articles from biomedical research publications” though a peer-nominated “Faculty” of experts in various subject domains. Since the launch of F1000, several other mechanisms for expert literature recommendation have also come to the foreground, including academic social bookmarking tools like citeulike or Mendeley, the rise of Research Blogging, and new F1000-like services such as annotatr, The Third Reviewer PaperCritic and TiNYARM.

Shortly after I started my group at the University of Manchester in 2005 I was invited to join the F1000 Faculty, which I gratefully accepted. At the time, I felt that it was a mark of distinction to be invited into this select club, since I felt that it would be a good platform to voice my opinions on what work I thought was notable. I was under no illusion that my induction was based only on merit, since this invitation came from my former post-doc mentor Michael Ashburner. I overlooked this issue at the time, since when you are invited to join the “in-club” as a junior faculty member, it is very tempting since you think things like this will play a positive role in your career progression. [Whether being in F1000 has helped my career I can't say, but certainly it can't have hurt, and I (sheepishly) admit to using it on grant and promotion applications in the past.]

Since then, I’ve tried to contribute to F1000 when I can [PAYWALL], but since it is not a core part of my job, I’ve only contributed ~15 reviews in 5 years. My philosophy has been only to contribute reviews on articles I think are of particular note and might be missed otherwise, not to review major papers in Nature/Science that everyone is already aware of. As time has progressed and it has become harder to commit time to non-essential tasks, I’ve contributed less and less, and the F1000 staff has pestered me frequently with reminders and phone calls to submit reviews. At times the pestering has been so severe that I have considered resigning just to get them off my back. And I’ve noticed that some colleagues I have a lot of respect for have also resigned from F1000, which made me wonder if they were likewise fed up with F1000′s nagging.

This summer, while reading a post on the Tree of Life blog, Jonathan Eisen made a parenthetical remark about quitting F1000, which made me more aware of why their nagging was really getting to me:

I even posted a “dissent” regarding one of [Paul Hebert's] earlier papers on Faculty of 1000 (which I used to contribute to before they become non open access).

This comment made me realize that the F1000 recommendation service is just another closed-access venture for publishers to make money off a product generated for free by the goodwill and labor of academics. Like closed access journals, my University pays twice to get F1000 content — once for my labor and once for the subscription to the service. But unlike a normal closed-access journal, in the case of F1000 there is not even a primary scientific publication to justify the arrangement. So by contributing to F1000, essentially I take time away from my core research and teaching activities to allow a company to commercialize my IP and pay someone to nag me! What’s even more strange about this situation is that there is no rational open-access equivalent of literature review services like F1000. By analogy with the OA publishing of the primary literature, for “secondary” services I would pay a company to post one of my reviews on someone else’s article. (Does Research Blogging for free sound like a better option to anyone?)

Thus I’ve come to realize that is unjustified to contribute secondary commentary to F1000 on Open Access grounds, in the same way it is unjustified to submit primary papers to closed-access journals. If I really support Open Access publishing, then to contribute to F1000 I must either must either be a hypocrite or make an artificial distinction between the primary and secondary literature. But this gets to the crux of the matter: to the extent that recommendation services like F1000 are crucial for researchers to make sense of the onslaught of published data, then surely these critical reviews should be Open for all, just as the primary literature should be. On the other hand, if such services are not crucial, why am I giving away my IP for free to a company to capitalize on?

Well, this question has been on my mind for a while and I have looked into whether there might be evidence that F1000 evaluations have a real scientific worth in terms of highlighting good publications that might provide a reason to keep contributing to the system. On this point the evidence is scant and mixed. An analysis by the Wellcome Trust finds a very weak correlation between F1000 evaluations and the evaluations of an internal panel of experts (driven almost entirely by a few clearly outstanding papers), with the majority of highly cited papers being missed by F1000 reviewers. An analysis by the MRC shows a ~2-fold increase in the median number of citations (from 2 to 4) for F1000 reviewed articles relative to other MRC-funded research. Likewise, an analysis of the Ecology literature shows similar trends, with marginally higher citation rates for F1000 reviewed work, but with many high impact papers being missed. Therefore the available evidence indicates that F1000 reviews do not capture the majority of good work being published, and the work that is reviewed is only of marginally higher importance (in terms of citation) than unreviewed work.

So if (i) it goes against my OA principles, (ii) there is no evidence (on average) that my opinion matters quantitatively much more than anyone else’s, and (iii) there are equivalent open access systems to use, why should I continue contributing to F1000? The only answer I can come up with is that by being a F1000 reviewer, I gain a certain prestige for being in the “in club,” as well as by some prestige-by-association for aligning myself with publications or scientists I perceive to be important. When stripped down like this, being a member of F1000 seems pretty close to being a Sneetch with a star, and that the F1000 business model is not too different than that used by Sylvester McMonkey McBean. Realizing this has made me feel more than a bit ashamed for letting the allure of being in the old-boys club and my scientific ego trick me into something I cannot rationally justify.

So, needless to say I have recently decided to resign from F1000. I will instead continue to contribute my tagged articles to citeulike (as I have for several years) and contribute more substantial reviews to this blog via the Research Blogging portal and push the use of other Open literature recommendation systems like PaperCritic, who have recently made their user-supplied content available under a Creative Commons license. (Thanks for listening PaperCritic!).

By supporting these Open services rather than the closed F1000 system (and perhaps convincing others to do the same) I feel more at home among the ranks of the true crowd-sourced “Faculty of 1,000,000″ that we need to help filter the onslaught of publications. And just as Sylvester McMonkey McBean’s Star-On machine provided a disruptive technology for overturning perceptions of prestige by giving everyone a star in The Sneetches, I’m hopeful that these open-access web 2.0 systems will also do some good towards democratizing personal recommendation of the scientific literature.

* Note: This post should in no way be taken as an ad hominem against F1000 or its founder Vitek Tracz, who I respect very much as a pioneer of Open Access biomedical publishing

** This number is an estimate based on the real figure of ~2.5K papers/day in deposited in MEDLINE, extrapolated to the large number of non-biomedical journals that are not indexed by MEDLINE.  If any has better data on this, please comment below.

A response strategy [Francis] Crick adopted in the 1960s to cope with an enormous post and to make a serious point playfully was the occasional use of a pre-printed postcard offering a number of reply options. The seventeen listed (see Figure 3) are a faithful reflection of the requests he regularly received.

Francis Crick's all-purpose reply card.

While I don’t expect to have opportunity to use many of these myself in the future, and there are some that I don’t agree with rejecting outright (e.g. read your manuscript), this list serves as a checklist for non-core academic activities and a useful reminder of what we didn’t go into science for in the first place.

Enjoy!

Nevertheless, I have steadily adopted most of the policies of the open letter, especially as my group has gotten more heavily involved in text-mining research over the years. This became especially true after a nasty encounter with one publisher in 2008 caused campus IT to shutdown my office IP for downloading articles from a journal for which our University has a site license, which radicalized me into more of an open access evangelist. After discussing this event at the time with Ashburner, he reminded me of the manifesto and one of its most powerful tools for changing the landscape of scholarly publishing – refusing to reviewing for journals/publishers who do not submit their content to PubMed Central (see the white-list of journals here).

I have dug this letter out countless times since then and used versions of it when asked to review for non-PMC journals, as it expresses the principles in plain and powerful language. I had another call to dig it out today and thought that I’d post the “Ashburner response” so others have a model to follow if they chose this path.

Enjoy!

From: “Michael Ashburner” <michael.ashburner@xxx.xxx>
Date: 30 August 2008 13:48:03 GMT+01:00
To: “Casey Bergman” <casey.bergman@xxx.xxx>
Subject: Just say No

Dear Editor,

Thank you for your invitation to review for your journal. Because it is not open access and does not provide its back content to PubMed Central, or any similar resource, I regret that I am unwilling to do this.

I would urge you to seriously reconsider both policies and would ask that you send this letter to your co-editors and publisher. In the event that you do change your policy, even to the extent of providing your back content to PubMed Central, or a similar resource, then I will be happy to review for you.

The scientific literature is at present the most significant resource available to researchers. Without access to the literature we cannot do science in any scholarly manner. Your journal refuses to embrace the idea that the purpose of the scientific literature is to communicate knowledge, not to make a profit for publishers. Without the free input of manuscripts and referees’ time your journal would not exist. By and large, the great majority of the work you publish is paid for by taxpayers. We now, either as individuals or as researchers whose grants are top-sliced, have to pay to read our own work and that of our colleagues, either personally or through our institutes’ libraries. I find that, increasingly, literature that is not available by open access is simply being ignored. Moreover, I am very aware that, increasingly, discovering information from the literature relies on some sort of computational analysis. This can only be effective if the entire content of primary research papers is freely available. Finally, by not being an open access journal you are disenfranchising both scientists who cannot afford (or whose institutions cannot afford) to pay for access and the general public.

There are now several good models for open access publication, and I would urge your journal to adopt one of these. There is an extensive literature on open access publishing, and its economic implications. I would be pleased to send you references to this literature.

Yours sincerely,

Michael Ashburner

Related Posts:

• Times Higher Education – Peers, review your actions.
• Sauropod Vertebra Picture of the Week – Researchers! Stop doing free work for non-open journals!
• From the Bottom of the Heap – I’m on peer review strike!
• Bishop Blog – Time for academics to withdraw free labour 
• Gower’s Weblog - Elsevier — my part in its downfall
• Jabberwocky Blog - Why I will no longer review for your journal 
• Reciprocal Space – Why I chose to decline an invitation to review by Elsevier
• Azimuth – Ban Elsevier
• Depth-First – Five Things to Do Instead of Protesting the Research Works Act (HR 3699)
• Impact of Social Sciences – Comfort is the death knell of academia: why I’m standing down as a journal referee

First, the authors make an artificial distinction between the supporting online materials associated with a paper and the contents of the paper itself. Clearly the most important data in a scientific report is in the full text of the article, and thus if making data in supporting online materials “maximally available” is a goal, surely so must be making data in full-text article itself. Second, in the context of the wider discussion on “big data” in which these points are made, it must be noted that maximal availability is only one step towards maximal utility, the other being maximal access. As the entire content of Science magazine is not available for unrestricted download and re-use from PubMed Central‘s Open Access repository, maximal utility of data in the full text or supplemental materials of articles published in Science is currently fettered because it is not available for bulk text mining or data mining. Amazingly, this is true even for Author-deposited manuscripts in PubMed Central, which are not currently included in the PubMed Central Open Access subset and therefore not available for bulk download and re-use.

Therefore it seems imperative that, in addition to making a clarion call for the improved availability of data, code and references in supplemental materials, the Editors of Science should issue a clear policy statement about the use of full-text articles and supplemental online materials that are published in Science for text and data mining research. At a minimum, Science should join with other high profile journals such as Nature [5] in clarifying the use of Author-deposited manuscripts in PubMed Central for text and data mining that are required to be deposited under funding body mandates for these very purposes. Additionally, Science should make a clear statement about the copyright and re-use policies for supporting online materials of all published articles, which are freely available for download without a Science subscription, and currently fall in the grey area between restricted and open access.

As we move firmly into the era of big data where issues of access and re-use of data becoming increasingly acute, Science, as the representative publication of the world’s largest general scientific society, should take the lead in opening its content for text and data mining, to the mutual benefit of authors, researchers and the AAAS.

References:

1. Hanson et al. (2011) Making Data Maximally Available. Science 331:649
2. Santos et al. (2005) Supplementary data need to be kept in public repositories. Nature 438:738
3. Anderson et al. (2006) On the persistence of supplementary resources in biomedical publications. BMC Bioinformatics 7:260
4. Journal of Neuroscience policy on Supplemental Material
5. Nature Press release on data- and text-mining of self-archived manuscripts

Related Posts:

• Watts Up with That – An Open Letter to Bruce Alberts of Science Magazine
• Stoat – Nah, don’t believe it
• Kitware Blog – AAAS: Your Paper MUST include Data, MUST include Code.
• NIF Blog – Supplementary material: Can NIF bring order to the netherworld of publishing?
• The Tree of Life - Calling on AAAS to Deposit all Archives of Science in Pubmed Central 
• NeuroDojo – Occupy Science (the journal)