A preprint of an invited submission to BioMedCentral Bioinformatics. This short manuscript is an overview or the current problems and opportunities in publishing chemical information. Full details of technology are given in the sibling manuscript http://www.dspace.cam.ac.uk/handle/1810/34579
The manuscript is the authors' preprint although it has been automatically transformed into this archived PDF by the submission system. The authors are not responsible for the formattingChemical information is now seen as critical for most areas
of life sciences. But unlike Bioinformatics, where data is
Openly available and freely re−usable, most chemical
information is closed and cannot be re−distributed without
permission. This has led to a failure to adopt modern
informatics and software techniques and therefore paucity of
chemistry in bioinformatics. New technology, however, offers
the hope of making chemical data (compounds and properties)
Free during the authoring process. We argue that the technology
is already available; we require a collective agreement to
enhance publication protocols

Mitchell, John B O

Murray-Rust, Peter

Rzepa, Henry S

BMC Bioinformatics

English

PubMed

Murray-Rust, P

Mitchell, JBO

Rzepa, HS

Spiral - Imperial College Digital Repository

BioMed CentralBMC BioinformaticsssOpen AcceChemistry in BioinformaticsPeter Murray-Rust†1, John BO Mitchell†1 and Henry S Rzepa*†2Address: 1Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge. CB2 1EW, UK. and 2Department of Chemistry, Imperial College London, SW7 2AY, UK.Email: Peter Murray-Rust - pm286@cam.ac.uk; John BO Mitchell - jbom1@cam.ac.uk; Henry S Rzepa* - rzepa@ic.ac.uk* Corresponding author    †Equal contributorsAbstract: Chemical information is now seen as critical for most areas of life sciences. But unlikeBioinformatics, where data is openly available and freely re-usable, most chemical information isclosed and cannot be re-distributed without permission. This has led to a failure to adopt moderninformatics and software techniques and therefore paucity of chemistry in bioinformatics. Newtechnology, however, offers the hope of making chemical data (compounds and properties) freeduring the authoring process. We argue that the technology is already available; we require acollective agreement to enhance publication protocols.IntroductionIn "Representation and Use of Chemistry in the GlobalElectronic Age” [1] we showed that new technology canprovide great increases in the quantity and quality ofaggregated chemical information published in the pri-mary literature. We also argued the benefits of OpenAccess and Open Data. The current invited overview anda parallel technical article extends the same methodologyto chemistry in bioinformatics to remove the loss and cor-ruption of data that occurs in current publishing. We arepleased that this article is an Open Access publication, andwe expect that bioinformatics, with its culture of OpenData, is more likely than mainstream chemistry to adoptnew approaches. The benefits of open access  includehigher quality, greater availability, and development ofthe Biochemical Semantic Web where robots mine textand data as a basis for knowledge-driven science. Weargue that funders, institutions, authors, editors, publish-ers and readers will all benefit.Biosciences now require large amounts of detailed chem-ical information, examples of which include the  occur-rence and role of small-molecules in biological processes;the mechanism of biochemical reactions and interactions;the structure and properties of biomolecules; reagents,protocols and classificatory tools for performing bio-science; chemistry in the ecosphere. Such information isonly available in a dispersed manner in the primary liter-ature and current mechanisms for its collection and dis-semination do not meet the needs of bioscience. Howeverif there is a communal will, modern chemical informaticstechnology can provide what is required. Several excellentmodels for the capture of macromolecular sequence andstructure data (e.g. the protein data bank) inform ourarchitecture.Data in published articles can include reference to chemi-cal compounds (often in free text), details of their synthe-sis (in vivo and in vitro), proof of their structure (spectraand analytical data), methods and reagents in bioscienceprotocols, the physical and biological properties and reac-tion of compounds both in enzymes and enzyme-free sys-tems. With the tools that we and others have developed,this information can now be automatically captured withhigh precision from primary publications, especially ifstructured authoring tools are widely used.Published: 07 June 2005BMC Bioinformatics 2005, 6:141 doi:10.1186/1471-2105-6-141Received: 11 May 2005Accepted: 07 June 2005This article is available from: http://www.biomedcentral.com/1471-2105/6/141© 2005 Murray-Rust et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Page 1 of 4(page number not for citation purposes)BMC Bioinformatics 2005, 6:141 http://www.biomedcentral.com/1471-2105/6/141Unlike bioinformaticists, who routinely  apply data- andtext-mining tools in their research, conventional chemistsappear culturally more suspicious of robotic data extrac-tion and continue to rely on manually curated secondarypublications whose philosophy has barely altered over120 years. Such sources are necessarily incomplete intime, coverage and coverage of information types. Forexample for 99+% of all newly synthesised compoundsthe papers report that Infra-red spectra have beenrecorded, but only a tiny fraction of this is available inelectronic form. We argue that even modest improvementin such a data capture rate would make an enormous dif-ference. Moreover the data would be of consistentlyhigher quality than manually re-keyed data. The mainchallenge is a cultural one. Thus biosciences and crystal-lography have communally convinced authors and pub-lishers of the value of author-based deposition of data,later aggregated in communally accessible databanks. Thislargely does not currently happen in chemistry, whereinformation is manually extracted from the primarily lit-erature, jealously guarded and sold back to the commu-nity. Mechanisms such as "supporting or supplementaldata deposition" are not widely used, and when they are,little care is given to enabling its re-use. One of the majorsecondary publishers has recently criticised the biosciencecommunity for aggregating chemical data. "It [PubChem] would not only injure us significantly, it wouldput information for free in the hands of world scientists and doit all with taxpayer money," Massie [CEO, Chemical AbstractService] said. "For me to wake up one morning and find I haveto compete with my own government is extraordinary.”[2]The attitude in chemistry to modern informatics (XML,ontologies, RDF, text-mining, metadata, etc.) [3] is largelyapathetic, with some data- or software-centric organisa-tions actively opposing interoperability for commercialreasons. This problem extends to mainstream chemicalsoftware, where there are no Open standards and wherealgorithms are closed and obscure. We have argued thatthe large data aggregators produce vendor-centric accesssystems to meet their needs rather than the community's.Another problem is that access is often only allowable ona per-item basis rather than to the data collection as awhole. This monopolistic "thought control" in chemistrystifles innovation in data-led science. However the Opens(Data, Source, Access, Standards) are changing the prac-tice of scientific informatics and chemistry is starting to beaffected.We therefore look to bioscience to take a lead in helpingrealise the following vision. We now believe that there arealready enough Open tools and Open resources whichcan make the vision attractive and cost-effective.A model for automatic capture of chemical informationMuch chemical data is largely context-free in that it can beunderstood and recreated independently of the locationor motivation. The primary data model, inspired by Kon-rad Beilstein in the 19th century, has three components:compound, properties and citations. A pure compound isdescribed by an immutable structural formula and hasprecisely reproducible properties. Current thinking assertsthat the biological action of a compound is, in principle,reproducible and predictable if the system is carefullyenough replicated and the components understood. Thisis the central dogma of the chemically-based pharmaceu-tical industry and the chemical information industry onwhich it relies.Chemistry has a tradition of ensuring quality throughreporting properties and analysis, so every new com-pound (and many re-synthesised ones) must have pub-lished measurements of properties to justify their identityand purity. These facts are available, in text form, in theprimary literature in which over a million new com-pounds are published annually. Because structure predictsproperties, and because drug discovery is so difficult, thepharmaceutical industry tests many compounds for bio-logical activity. The data in these public publications is amajor feedstock for the chemical information industry.The chemical bioscientist has almost all of the requiredinformation available in electronic form on their bench-top already! It could be deposited for the scientific com-munity with virtually no human intervention. We believethat, with the help of forward looking publishers, a work-ing protocol can be set up in bioscience, which will theninspire (or terrify) mainstream chemical informatics.Note that much of the information captured is additionalto that which the current abstracters collect.We argue that the key components to automatically cap-ture chemical information are already in place (and arediscussed in more detail in an accompanying technicalarticle). We envisage the chemistry which can be capturedusing such mechanisms includes (a) Chemical entitiesand names. Many compounds have no explicit structuresand are mentioned only by name or identifiers. Wherethese relate to specific compounds it is valuable to linkthem to a precise identification, such as PubChem. (b)Molecular structure, expressed as a compositional for-mula (e.g. CHaOH for methanol) and a graphical struc-tural formula ("2D diagram" or connection table). (c)Spectra and physical properties. Much such information isalready in digital form when produced by instruments(whose manufacturers are starting to create Openapproaches [4], but is largely destroyed by conventionalpublishing processes If a community-wide digital tem-plate for the submission of this information were availa-Page 2 of 4(page number not for citation purposes)BMC Bioinformatics 2005, 6:141 http://www.biomedcentral.com/1471-2105/6/141ble and encouraged by publishers it would be welcomedby many, would eliminate errors introduced by transcrip-tion, and enable machine-reviewing of data leading to ahigher standard of published data.The basis of our model involves conversion of experimen-tal data to XML and its merger with the conventional text(giving a “datument” [5]). The author uses a authoringtool which can manage structured XML documents andprovide normal textual support (spellchecks, etc.). Theresulting datument contains fine-grained markup of facts(molecules, measurements, properties, chemical names)and can automatically be used to create derivatives such asthe "full-text" or the "supplemental data". The completedatument, if Open, or the "data" if not is then repositedfor further harvesting. All compound/property data isavailable for datamining and computational re-use (e.g.for further in silico prediction.Realising the visionData repositing and maintenanceThe current dissemination of data through publishers islargely unsatisfactory.   Thus although many publishersallow the deposition of factual "supplementary data”,  ourexperience with most is that it is an unwelcome chore,poorly resourced and maintained. Moreover althoughreviewers are often do what they can to validate data, pub-lishers themselves do not. We believe that many publish-ers would welcome a model where they were no longerinvolved in data repositing. A few publishers such as theInternational Union of Crystallography are more commit-ted to the curation of data; others in the biosciences seethe value of semantically enhanced data.The crystallo-graphic experience has shown that expert computer pro-grams can act as powerful reviewers complementing thehuman; automatic curation enhances, rather than lowers,data quality.Our model is based on the availability of repositories, pri-marily Institutional, that accept data as well as full text.Already some academic institutions and an increasingnumber of funders mandate that research output shouldbe reposited and there are national initiatives to developthe infrastructure. The storage for XML-ised chemical datais modest (less than 1 mbyte per publication) and we haveshown that large numbers of molecules can be depositedin our own institutional repository [6] and recovered byundirected search engines such as Google [7]. Chemicaldata has required no semantic maintenance (e.g. throughchanges in meaning or use) over many decades and we seethis continuing, so that the maintenance costs are thosegeneral to any repository.         Components in a repository have a unique handle withwhich,  in principle, a Digital object or other identifier(DOI) [8] can be associated so that data can be cloned foraccess and preservation. The handle or DOI would bepublished in the "full text" and would bind the data to itmore effectively that at present and hopefully indefinitely.MetadataThrough the InChI (International Chemical Identifier)[8]and a controlled vocabulary of chemical properties,generic search engines can achieve a very high degree ofrecall. This means that discovery and aggregation can bebuilt on maintenance-free generic technology and can bemade completely automatic, Conventionalists wouldargue of course that human curation is essential for re-usa-ble chemical data. In a similar vein to much bioinfor-matic, we argue that robots can discover patterns in data,compounds and authors which are at least as powerful asmany current abstracting services. Where human evalua-tion is critical (e.g. in human medicine, patents, etc.) thenthe robots will provide the primary resources on which ajudgement can be based.RightsWe assume that most bioscience authors and publisherswill agree that whether or not a paper is Open Access thefacts (and thereby all "supplemental data") therein arenot copyrightable. XML resolves differences of interpreta-tion in that XML markup can be regarded as identifyingfactual information and this would be consistent with itsre-use under (say) the Budapest Open Access Initiative. Inthis way all published chemical data can be made imme-diately, completely and clearly available for indefinite sci-entific re-use.PotentialBecause the chemical information is structured we nowhave a biocheminformatics "cycle" where, for the firsttime, large scale robotic data analysis can take place. Thedata in the research (laboratory, in silico, or both) arepublished in a lossless manner. Molecules and their prop-erties have unique identifiers as described above and canbe integrated into mainstream bioinformatics in the samemanner as collections such as PubChem, the macromo-lecular stucture database (MSD at EBI), the Kyoto Encyclo-pedia of Genes and Genomes (KEGG) etc.  They will bringthe added value of consistently captured property dataand spectra. We also expect that many  in silico propertieswill then be systematically added.Author and publisher complianceThe introduction of structured authoring tools (e.g. Publi-con) [9] will help this process considerably. Templatescan be created for the chemical components describedabove and where the information exists in XML (connec-tion tables, spectra, properties) it should be as easy as forcommitted authors as using a semantically void tool (e.g.Page 3 of 4(page number not for citation purposes)BMC Bioinformatics 2005, 6:141 http://www.biomedcentral.com/1471-2105/6/141Publish with BioMed Central   and  every scientist can read your work free of charge"BioMed Central will be the most significant development for disseminating the results of biomedical research in our lifetime."Sir Paul Nurse, Cancer Research UKYour research papers will be:available free of charge to the entire biomedical communitypeer reviewed and published immediately upon acceptancecited in PubMed and archived on PubMed Central yours — you keep the copyrightSubmit your manuscript here:http://www.biomedcentral.com/info/publishing_adv.aspBioMedcentralWord). Where information needs to be converted fromlegacy formats, an increasing number of open Web Serv-ices,  which publishers (and authors) may clone and cus-tomise are becoming avilable. We expect authors to havea greater incentive (even if only through mandation) toreposit data and to disseminate research findings. Thisalso raises the vision of changing the "citation economy"(which values market perception) to a "reuse economy"where a the data in a paper are valued by how often theyare re-used.References1. Murray-Rust P, Rzepa H S, Tyrell S M, Zhang Y: Org Biomol Chem 2004,2:3192-3203.2. Government-funded Free Information for Chemists 'Unfair'Competition for Private Monopolies   [http://www.okfn.org/drn/node/56]3. World Wide Web consortium  [http://www.w3c.org/]4. Analytical Information Markup Language  [http://animl.sourceforge.net/]5. Murray-Rust P, Rzepa H S: The Next Big Thing: From Hyperme-dia to Datuments. J Digital Inf 2004, 5:.6. University decision to offer free online access to all research[http://www.jisc.ac.uk/index.cfm?name=free_access_to_university_research_news171204]7. Coles S J, Day N E, Murray-Rust P, Rzepa H S, Zhang Y: Enhance-ment of the Chemical Semantic Web through the use ofInChI Identifiers. Org Biomol Chem 2005, 3:1832-1834.8. Murray-Rust P, Rzepa H S, Stein S: The InChI as an LSID for mol-ecules in lifescience. W3C Workshop on Semantic Web for Life Sci-ences, 27-28 October 2004, Cambridge,  Massachusetts USA. 2004 [http://lists.w3.org/Archives/Public/public-swls-ws/2004Sep/att-0026/inchi.html].9. BioMed Central and Publicon  [http://www.biomedcentral.com/info/ifora/publicon/]Page 4 of 4(page number not for citation purposes)

Chemistry in Bioinformatics

Chemical information is now seen as critical for most areas
of life sciences. But unlike Bioinformatics, where data is
Openly available and freely re−usable, most chemical
information is closed and cannot be re−distributed without
permission. This has led to a failure to adopt modern
informatics and software techniques and therefore paucity of
chemistry in bioinformatics. New technology, however, offers
the hope of making chemical data (compounds and properties)
Free during the authoring process. We argue that the technology
is already available; we require a collective agreement to
enhance publication protocols

Apollo (Cambridge)

F R O N T M A T T E RChemistry in BioinformaticsPeter Murray−Rust,1  John B. O. Mitchell,1  and Henry S. Rzepa21 Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge. CB2 1EW, UK.2 Department of Chemistry, Imperial College London, SW7 2AY, UK.AbstractChemical information is now seen as critical for most areas    of life sciences. But unlike Bioinformatics, where data is    Openly available and freely re−usable, most chemical    information is closed and cannot be re−distributed without    permission. This has led to a failure to adopt modern    informatics and software techniques and therefore paucity of    chemistry in bioinformatics. New technology, however, offers    the hope of making chemical data (compounds and properties)    Free during the authoring process. We argue that the technology    is already available; we require a collective agreement to    enhance publication protocols.B O D YBackgroundIn "Representation and Use of Chemistry in the Global    Electronic Age"[1] we showed that new technology can    provide great increases in the quantity and quality of    aggregated chemical information published in the primary    literature. We also argued the benefits of Open Access and Open    Data. The current invited overview and a parallel technical    article extends the same methodology to chemistry in    bioinformatics to remove the loss and corruption of data that    occurs in current publishing. We are pleased that this is an    Open Access publication, and we expect that bioinformatics,    with its culture of Open Data, is more likely than mainstream    chemistry to adopt new approaches. Benefits include higher    quality, greater availability, and development of the    Biochemical Semantic Web where robots mine text and data as a    basis for knowledge−driven science. We argue that funders,    institutions, authors, editors, publishers and readers will  all    benefit  Biosciences now require large amounts of detailed chemical    information, examples of which include the  occurrence and    role of small−molecules in biological processes; the mechanism    of biochemical reactions and interactions; the structure and    properties of biomolecules; reagents, protocols and    classificatory tools for performing bioscience; chemistry in    the ecosphere. Such information is only available in a    dispersed manner in the primary literature and current    mechanisms for its collection and dissemination do not meet the    needs of bioscience. However if there is a communal will,    modern chemical informatics technology can provide what is    required. The excellent model for the capture of macromolecular    sequence and structure data inform our architecture.    Published data include mention of chemical compounds (often    in free text), details of their synthesis (in vivo and in    vitro), proof of their structure (spectra and analytical data),    methods and reagents in bioscience protocols, the physical and    biological properties and reaction of compounds both in enzymes    and enzyme−free systems. With the tools that we and others have    developed, this information can now be automatically    captured with high precision from primary publications,    especially if structured authoring tools are widely used.    Published data include mention of chemical compounds (often    in free text), details of their synthesis (in vivo and in    vitro), proof of their structure (spectra and analytical data),    methods and reagents in bioscience protocols, the physical and    biological properties and reaction of compounds both in enzymes    and enzyme−free systems. With the tools that we and others have    developed, this information can now be automatically    captured with high precision from primary publications,    especially if structured authoring tools are widely used.    Unlike bioscientists who develop data− and text−mining    tools, conventional chemists appear culturally more suspicious    of robotic data extraction and continue to rely on manually    curated secondary publications whose philosophy has barely    altered over 120 years. Such sources are necessarily incomplete    in time, coverage and coverage of information types. For    example for 99+% of all newly synthesised compounds the papers    report that Infra−red spectra have been recorded, but at most    1% of this is available in electronic form. We argue that even    modest improvement in such a data capture rate would make an    enormous difference. Moreover the data would be of consistently    higher quality than The main challenge is cultural. Biosciences    and crystallography have communally convinced authors and    publishers of the value of author−based eposition of data,    later aggregated in communally accessible databanks. This    largely does not currently happen in chemistry, where    information is manually extracted from the primarily    literature, jealously guarded and sold back to the community.    Mechanisms such as "supporting or supplemental data deposition"    are not widely used, and when they are, little care is given to    enabling its re−use. Regrettably one of the major secondary    publishers has recently criticised the bioscience community for    aggregating chemical data: "It [PubChem] would not only injure us significantly, it      would put information for free in the hands of world      scientists and do it all with taxpayer money," Massie [CEO,      CAS] said. "For me to wake up one morning and find I have to      compete with my own government is extraordinary."[2]The attitude in chemistry to modern informatics (XML,    ontologies, RDF, text−mining, metadata, etc.)[3] is    largely apathetic, with some data− or software−centric    organisations actively opposing interoperability for commercial    reasons. This problem extends to mainstream chemical software,    where there are no Open standards and where algorithms are    closed and obscure. We have argued that the large data    aggregators produce vendor−centric access systems to meet their    needs rather than the community’s. Another problem is that    access is often only allowable on a per−item basis rather than    to the data collection as a whole. This monopolistic "thought    control" in chemistry stifles innovation in data−led science.    However the Opens (Data, Source, Access, Standards) are changing    the practice of scientific informatics and chemistry is    starting to be affected.    We therefore look to bioscience to take a lead in helping    realise the following vision. We now believe that there are    already enough Open tools and Open resources which can make the    vision attractive and cost−effective.2Results A model for automatic capture of chemical information    Much chemical data is largely context−free in that it can be    understood and recreated independently of the location or    motivation. The primary data model, inspired by Konrad    Beilstein in the 19th century, has three components: compound,    properties and citations. A pure compound is described by an    immutable structural formula and has precisely reproducible    properties. Current thinking asserts that the biological action    of a compound is, in principle, reproducible and predictable if    the system is carefully enough replicated and the components    understood. This is the central dogma of the chemically−based    pharmaceutical industry and the chemical information industry    on which it relies.    Chemistry has a tradition of ensuring quality through    reporting properties and analysis, so every new compound (and    many re−synthesised ones) must have published measurements of    properties to justify their identity and purity. These facts    are available, in text form, in the primary literature in which    over a million new compounds are published annually. Because    structure predicts properties, and because drug discovery is so    difficult, the pharmaceutical industry tests many compounds for    biological activity. The data in these public publications is a    major feedstock for the chemical information industry.   The chemical bioscientist has almost all of the required    information available in electronic form on their benchtop    already! It could be deposited for the scientific community    with virtually no human intervention. We believe that, with the    help of forward looking publishers, a working protocol can be    set up in bioscience, which will  then inspire (or terrify)    mainstream chemical informatics. Note that much of the    information captured is additional to that which the current    abstracters collect.    We argue that the key components to automatically capture    chemical information are already in place (and are discussed in    more detail in an accompanying technical article). We envisage    the chemistry which can be captured using such mechanisms    includes (a) Chemical entities and names. Many compounds have    no explicit structures and are mentioned only by name or    identifiers. Where these relate to specific compounds it is    valuable to link them to a precise identification, such as    PubChem. (b) Molecular structure, expressed as a compositional    formula (e.g. CH3OH for methanol) and a graphical    structural formula ("2D diagram" or connection table). (c)    Spectra and physical properties. Much such information is    already in digital form when produced by instruments (whose    manufacturers are starting to create Open approaches[4],    but is largely destroyed by conventional publishing processes.    If a community−wide digital template for the submission of this    information were available and encouraged by publishers it    would be welcomed by many, would eliminate errors introduced by    transcription, and enable machine−reviewing of data leading to    a higher standard of published data.    The basis of our model involves conversion of experimental    data to XML and its merger with the conventional text (giving a    "datument"[5]). The author uses a authoring tool which    can manage structured XML documents and provide normal textual    support (spellchecks, etc.). The resulting datument contains    fine−grained markup of facts (molecules, measurements,    properties, chemical names) and can automatically be used to    create derivatives such as the "full−text" or the "supplemental    data". The complete datument, if Open, or the "data" if not is    then reposited for further harvesting. All  compound/property    data is available for datamining and computational re−use (e.g.    for further in silico prediction.3    The basis of our model involves conversion of experimental    data to XML and its merger with the conventional text (giving a    "datument"[5]). The author uses a authoring tool which    can manage structured XML documents and provide normal textual    support (spellchecks, etc.). The resulting datument contains    fine−grained markup of facts (molecules, measurements,    properties, chemical names) and can automatically be used to    create derivatives such as the "full−text" or the "supplemental    data". The complete datument, if Open, or the "data" if not is    then reposited for further harvesting. All  compound/property    data is available for datamining and computational re−use (e.g.    for further in silico prediction.    Realising the vision    Data repositing and Maintenance    The current dissemination of data through publishers is    largely unsatisfactory. Some, such as the International Union    of Crystallography, are committed; others in the biosciences    see the value of semantically enhanced data. Many publishers    allow the deposition of factual "supplementary data" but our    experience with most is that it is an unwelcome chore, poorly    resourced and maintained. Moreover although reviewers are often    do what they can to validate data, publishers themselves do    not. We believe that many publishers would welcome a model    where they were no longer involved in data repositing. The    crystallographic experience has shown that expert computer    programs can act as powerful reviewers complementing the human;    automatic curation enhances, rather than lowers, data    quality.    Our model is based on the availability of repositories,    primarily Institutional, that accept data as well as full text.    Already some academic institutions and an increasing number of    funders mandate that research output should be reposited and    there are national initiatives to develop the infrastructure.    The storage for XML−ised chemical data is modest (less than 1    mbyte per publication) and we have shown that large numbers of    molecules can be deposited in our own institutional repository[6]    and recovered by undirected search engines such as Google.[7]    Chemical data has required no semantic maintenance (e.g.    through changes in meaning or use) over many decades and we see    this continuing, so that the maintenance costs are those    general to any repository.    Components in a repository have a unique handle with which,    in principle, a Digital object or other identifier (DOI)[8] can    be associated so that data can be cloned for access and    preservation. The handle or DOI would be published in the "full    text" and would bind the data to it more effectively that at    present and hopefully indefinitely.4    MetadataThrough InChI[8]  and a controlled vocabulary of    chemical properties, generic search engines can achieve a very    high degree of recall. The means that discovery and aggregation    are built on maintenance−free generic technology and can be    made completely automatic, Conventionalists will  argue that    human curation is essential for re−usable chemical data. In    similar vein to much bioinformatics we argue that robots can    discover patterns in data, compounds and authors which are at    least as powerful as many current abstracting services. Where    human evaluation is critical (e.g. in human medicine, patents,    etc.) then the robots will  provide the primary resources on    which a judgement can be based.    RightsWe assume that most bioscience authors and publishers will    agree that whether or not a paper is Open Access the facts (and    thereby all "supplemental data") therein are not copyrightable.    XML resolves differences of interpretation in that all XML    markup is regarded as identifying factual information and    consistent with re−use under (say) the Budapest Open Access    Initiative. In this way all published chemical data can be made    immediately, completely and clearly available for indefinite    scientific re−use.    PotentialBecause the chemical information is structured we now have a    biocheminformatics "cycle" where, for the first time, large    scale robotic data analysis can take place. The data in the    research (laboratory, in silico, or both) are published    in a lossless manner. Molecules and their properties have    unique identifiers as described above and can be integrated    into mainstream bioinformatics in the same manner as    collections such as PubChem, MSD (at EBI), KEGG, etc. They will    bring the added value of consistently captured property data    and spectra. We also expect that many  in silico    properties will  then be systematically added.   Author and publisher compliance    The introduction of structured authoring tools (e.g.    Publicon)[9] will  help this process considerably.    Templates can be created for the chemical components described    above and where the information exists in XML (connection    tables, spectra, properties) it should be as easy as for    committed authors as using a semantically void tool (e.g.    Word). Where information needs to be converted from legacy    formats we have created Open Web Services which publishers (and    authors) may clone and customise. We expect authors to have a    greater incentive (even if only through mandation) to reposit    data and to disseminate research findings. This also raises the    vision of changing the "citation economy" (which values market    perception) to a "reuse economy" where a the data in a paper    are valued by how often they are re−used.B A C K M A T T E R5References1. Murray−Rust P, Rzepa HS, Tyrell SM , Zhang Y : Org. Biomol. Chem., 2004, 2:3192|3203.2. Heller S. Posted to CHMINF−L,   quoting the Columbus Despatch. PubChem: the NIH/NCBI collection of small molecules and properties. CAS: Chemical Abstracts, a Division of the American Chemical Society. https://listserv.indiana.edu/cgi−bin/wa−iub.exe?A2=ind0504&amp;L=CHMINF−L&amp;D=0&amp;H=0&amp;I=−3&amp;O=T&amp;T=0&amp;P=20446 3. For information on this infrastructure, see URL http://www.w3c.org/ 4. For information, see URL http://animl.sourceforge.net/ 5. Murray−Rust P, Rzepa HS: The Next Big Thing: From Hypermedia to Datuments. J. Digital Inf., 2004, 5.6. For an example of  institution making all its research public, see  http://www.jisc.ac.uk/index.cfm?name=free_access_to_university_research_news171204 7. Coles SJ, Day NE, Murray−Rust P, Rzepa HS, Zhang Y : Enhancement of the Chemical Semantic Web through the use of  InChI Identifiers. Org. Biomol. Chem., 2005, 3:1832|1834.8. Murray−Rust P, Rzepa HS, Stein S: The InChI as an LSID for molecules in lifescience. W3C Workshop on Semantic Web for Life Sciences, 27−28 October 2004, Cambridge,  Massachusetts USA., 2004. http://lists.w3.org/Archives/Public/public−swls−ws/2004Sep/att−0026/inchi.html 9. For further information, see  URL. http://www.biomedcentral.com/info/ifora/publicon/ 6

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Rzepa H S: The Next Big Thing: From Hypermedia to Datuments.

The InChI as an LSID for molecules in lifescience.

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Zhang Y: Enhancement of the Chemical Semantic Web through the use of InChI Identifiers. Org Biomol Chem

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