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Amy West

PLoS Computational Biology: Defrosting the Digital Library: Bibliographic Tools for the... - 0 views

  • Presently, the number of abstracts considerably exceeds the number of full-text papers,
  • full papers that are available electronically are likely to be much more widely read and cited
  • Since all of these libraries are available on the Web, increasing numbers of tools for managing digital libraries are also Web-based. They rely on Uniform Resource Identifiers (URIs [25] or “links”) to identify, name, and locate resources such as publications and their authors.
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  • We often take URIs for granted, but these humble strings are fundamental to the way the Web works [58] and how libraries can exploit it, so they are a crucial part of the cyberinfrastructure [59] required for e-science on the Web.
  • link to data (the full-text of a given article),
  • To begin with, a user selects a paper, which will have come proximately from one of four sources: 1) searching some digital library, “SEARCH” in Figure 4; 2) browsing some digital library (“BROWSE”); 3) a personal recommendation, word-of-mouth from colleague, etc., (“RECOMMEND”); 4) referred to by reading another paper, and thus cited in its reference list (“READ”)
  • There is no universal method to retrieve a given paper, because there is no single way of identifying publications across all digital libraries on the Web
  • Publication metadata often gets “divorced” from the data it is about, and this forces users to manage each independently, a cumbersome and error-prone process.
  • There is no single way of representing metadata, and without adherence to common standards (which largely already exist, but in a plurality) there never will be.
  • Where DOIs exist, they are supposed to be the definitive URI. This kind of automated disambiguation, of publications and authors, is a common requirement for building better digital libraries
  • Publication metadata are essential for machines and humans in many tasks, not just the disambiguation described above. Despite their importance, metadata can be frustratingly difficult to obtain.
  • So, given an arbitrary URI, there are only two guaranteed options for getting any metadata associated with it. Using http [135], it is possible to for a human (or machine) to do the following.
  • This technique works, but is not particularly robust or scalable because every time the style of a particular Web site changes, the screen-scraper will probably break as well
  • This returns metadata only, not the whole resource. These metadata will not include the author, journal, title, date, etc., of
  • As it stands, it is not possible to perform mundane and seemingly simple tasks such as, “get me all publications that fulfill some criteria and for which I have licensed access as PDF” to save locally, or “get me a specific publication and all those it immediately references”.
  • Having all these different metadata standards would not be a problem if they could easily be converted to and from each other, a process known as “round-tripping”.
  • many of these mappings are non-trivial, e.g., XML to RDF and back again
  • more complex metadata such as the inbound and outbound citations, related articles, and “supplementary” information.
  • Personalization allows users to say this is my library, the sources I am interested in, my collection of references, as well as literature I have authored or co-authored. Socialization allows users to share their personal collections and see who else is reading the same publications, including added information such as related papers with the same keyword (or “tag”) and what notes other people have written about a given publication.
  • CiteULike normalizes bookmarks before adding them to its database, which means it calculates whether each URI bookmarked identifies an identical publication added by another user, with an equivalent URI. This is important for social tagging applications, because part of their value is the ability to see how many people (and who) have bookmarked a given publication. CiteULike also captures another important bibliometric, viz how many users have potentially read a publication, not just cited it.
  • Connotea uses MD5 hashes [157] to store URIs that users bookmark, and normalizes them after adding them to its database, rather than before.
  • he source code for Connotea [159] is available, and there is an API that allows software engineers to build extra functionality around Connnotea, for example the Entity Describer [160].
  • Personalization and socialization of information will increasingly blur the distinction between databases and journals [175], and this is especially true in computational biology where contributions are particularly of a digital nature.
  • This is usually because they are either too “small” or too “big” to fit into journals.
  • As we move in biology from a focus on hypothesis-driven to data-driven science [1],[181],[182], it is increasingly recognized that databases, software models, and instrumentation are the scientific output, rather than the conventional and more discursive descriptions of experiments and their results.
  • In the digital library, these size differences are becoming increasingly meaningless as data, information, and knowledge become more integrated, socialized, personalized, and accessible. Take Postgenomic [183], for example, which aggregates scientific blog posts from a wide variety of sources. These posts can contain commentary on peer-reviewed literature and links into primary database sources. Ultimately, this means that the boundaries between the different types of information and knowledge are continually blurring, and future tools seem likely to continue this trend.
  • he identity of people is a twofold problem because applications need to identify people as users in a system and as authors of publications.
  • Passing valuable data and metadata onto a third party requires that users trust the organization providing the service. For large publishers such as Nature Publishing Group, responsible for Connotea, this is not necessarily a problem.
  • business models may unilaterally change their data model, making the tools for accessing their data backwards incompatible, a common occurrence in bioinformatics.
  • Although the practice of sharing raw data immediately, as with Open Notebook Science [190], is gaining ground, many users are understandably cautious about sharing information online before peer-reviewed publication.
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    Yes, but Alexandria was also a lot smaller; not totally persuaded by analogy here...
Amy West

Liveblog: BRDI: Author Deposit Mandates for Federal Research Grantees : Gavin Baker - 0 views

  • DC Principles Coalition: We believe in free access to science, within the constraints of our business models.
  • The public doesn’t need access to the full articles
  • The problem is that consumers want everything for free.
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  • Repositories can do all the functions of journals except quality control, and we don’t want government doing that.
  • Social sciences often left out of discussions about data curation, open access, etc.
  • We could argue that taxpayers paid for the research in general, not necessarily each publication.
  • But the Public Access Policy requires the peer-reviewed manuscript, not the one after which the publishers add value. The America COMPETES model, for un-peer-reviewed grant proposals, is almost useless to the public. In health, you want the refereed results, not the grantee’s report to the agency.
  • If journals can’t survive, from an economic perspective, that’s not harm — it’s just a failure to adapt.
  • Journal growth trends with funding for researchers. As universities want to be more prestigious, they aim to publish more. Trying to have access to everything requires too much money — you have to prioritize.
Lisa Johnston

GSA Publications - Data Repository - 0 views

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    data repository linking data to publications.
Lisa Johnston

Open Science Data Initiative (OSDI) - 0 views

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    he Open Science Data Initiative is an initiative led by Oak Ridge National Laboratory in partnership with Microsoft's Public Sector Developer Evangelism team. OSDI is based on OGDI which in turn uses the Azure Services Platform to make it easier to publish and use a wide variety of scientific data from government agencies. OSDI is an sample of OGDI's open source 'starter kit' (coming soon) with code that can be used to publish data on the Internet in a Web-friendly format with easy-to-use, open API's. OSDI-based web API's can be accessed from a variety of client technologies such as Silverlight, Flash, JavaScript, PHP, Python, Ruby, mapping web sites, etc. Whether you are a researcher wishing to use scientific data, a hobyist developer, or a "budding scientist", these open API's will enable you to build innovative applications, visualizations and mash-ups that empower people through access to scientific information. This site is built using the OGDI starter kit software assets and provides interactive access to some publicly-available data sets along with sample code and resources for writing applications using the OSDI APIs.
Lisa Johnston

Scientists Embrace Openness - Science Careers - Biotech, Pharmaceutical, Faculty, Postd... - 0 views

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    At first glance, going "open" would seem like a serious career risk -- years of work could be for nothing if a competitor uses your work to beat you to publication -- but many practitioners of openness say the benefits outweigh those risks
Lisa Johnston

nsf.gov - National Science Foundation (NSF) News - NSF Releases Open Government Plan - ... - 0 views

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    National Science Foundation (NSF) is finding ways to make its work more accessible to the general public. 
Amy West

National Patterns of R and D Resources - 0 views

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    Describes and analyzes current patterns of research and development (R&D) in the US. In years when the full report is not published, the Division of Science Resources Statistics makes available "data update tables" to provide public access to the most c
Lisa Johnston

Open science at web-scale: Optimising participation and predictive potential : JISC - 0 views

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    This report has attempted to draw together and synthesise evidence and opinion associated with data-intensive open science from a wide range of sources. The potential impact of data-intensive open science on research practice and research outcomes, is both substantive and far-reaching. There are implications for funding organisations, for research and information communities and for higher education institutions.
Amy West

In case you can't read…. | Prof-Like Substance - 1 views

  • When I am putting a talk together it would never occur to me not to include a health dose of unpublished data. The only times in my career that I have talked about mostly published data have been when I first started as a postdoc and in the early days of being a PI, when I didn't have enough new data to even make a coherent story, but that accounts for maybe three professional talks out of man
  • s it a fear of being scooped or a penchant for keeping one's ideas close to the chest that promotes the Summary Talk?
  • I think it's field dependent. Personally, I can rarely get enough information from a talk to know whether to believe a result or not. This means that unpublished data usually ends up with me thinking "maybe, maybe not".
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  • (A good talk like this has enough of a citation on the slide that I can jot down where to go if I want to know details on any particular result.)
  • I'm in a highly competitive biomed field, and I was taught never to present something unless it was either submitted or ready to be submitted.
  • I don't really spend any time worrying about being scooped because I collect my own data.
  • Why look at a poster or talk of 100% published work, I've already seen the stuff in a journal to start with
  • Final year materials chemist = keeping cards close to my chest. Once bitten, never again.
  • In neuro, I'd say that at smaller conferences and less high-profile talks at big conferences (i.e. not keynotes or featured lectures), the bulk of what you're hearing is unpublished. ALL posters are unpublished--in fact, I think (?) it's a rule at SfN that the content of posters can't be published already.
  • In my field I'd guess that most talks include data that is in press or at some close to publication sta
  • A big name should be more generous, but then again they do have to save guard the career of the student/postdoc who generated the data. Also the star or keynote speaker is expected to address a wider audience, and make their talk relevant to the overall theme of the conference.
  • In my (experimental) social science, most conferences explicitly say that you cannot submit to present already published or even accepted work.
  • In my field (Astronomy), I'd say 95% of the talks are about unpublished data.
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    A blog post & comments on what's preferred in conference presentations: published or unpublished data. Interesting.
Amy West

Open access to research data a lot tougher than you think - 2 views

  • It means that researchers need to deal with the formatting and deposition of data, an annoying step when they would rather be focusing on their next project. Given the time lag, it's also difficult to associate the correct metadata with the material that's being a
  • According to the commentary, scientists view data deposition as a burden due to the extra work it involves. Research data is usually not in the correct format for submission to repositories when the project is completed, and so the scientist must take the time to convert it.
  • The authors here propose a new approach to data management, where each research institution should employ data managers to work with scientists and administer local, structured data storage. Local storage and support is the preference of most scientists, who would rather not hand off control of their data to remote strangers.
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