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  • The Future of the Journal? Integrating research data with scientific discourse, Anita de Waard, Nature Precedings 2010, hdl:10101/npre.2010.4742.1:
    Snippet: To advance the pace of scientific discovery we propose a conceptual format that forms the basis of a truly new way of publishing science. In our proposal, all scientific communication objects (including experimental workflows, direct results, email conversations, and all drafted and published information artifacts) are labeled and stored in a great, big, distributed data store (or many distributed data stores that are all connected). Each item has a set of metadata attached to it, which includes (at least) the person and time it was created, the type of object it is, and the status of the object including intellectual property rights and ownership. Every researcher can (and must) deposit every knowledge item that is produced in the lab into this repository. With this deposition goes an essential metadata component that states who has the rights to see, use, distribute, buy or sell this item. Into this grand (and system-wise distributed, cloud-based) architecture, all items produced by a single lab, or several labs, are stored, labeled and connected.

  • Will a Biological Database Be Different from a Biological Journal? Phil Bourne, PLoS Comput Biol 1(3): e34. doi:10.1371/journal.pcbi.0010034:
    Snippet: My vision is that a traditional biological journal will become just one part of various biological data resources as the scientific knowledge in published papers is stored and used more like a database. Conversely, the scientific literature will seamlessly provide annotation of records in the biological databases. Imagine reading a description of an active site of a biological molecule in a paper, being able to access immediately the atomic coordinates specifically for that active site, and then using a tool to explore the intricate set of hydrogen-bonding interactions described in the paper. Not only are the data generated by the experiment immediately available within the context of what you are reading, but specific tools for interpreting these data are provided by the journal. Alternatively, if you are starting with the data, for example, viewing the chromosome location of a human single-nucleotide polymorphism associated with a neurological disorder, you can immediately access a variety of papers ranked in order of relevance to your profile, not just through links to abstracts but also by pinpointing the reference to the single-nucleotide polymorphism in the full-text article.

  • AO: An Open Annotation Ontology for Science on the Web. Paolo Ciccarese, Marco Ocana, Sudeshna Das and Tim Clark. Bio Ontologies 2010, Boston MA, July 9-10, 2010.     pdf slidesgoogle code, ontology   
Snippet: The AO ontology provides essential abilities for scientific web communities and publishers, including 
support for:
(1) building position-aligned term enrichment into documents regardless of whether or not one controls
                the original text;
          (2) linking content across web communities and communities of scientific users, with shared metadata;
          (3) constructing searchable semantic metadata stores linked to documents in a standard way;
          (4) curation, with provenance, authoring and versioning of all annotations; and
          (5) human, algorithmic, and human-reviewed algorithmic annotation.

This model of web document annotation permits users including journal or web community editorial staff, individual scientists, and computational web agents to construct and persist scientific document annotation as RDF, linking text strings within the document to term URIs in scientific – particularly biomedical – ontologies. It supports multiple methods for linking terms to specific locations in documents, and depending upon the method used, can be stored entirely independently of the target document, which itself can remain unchanged.