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Lisa Johnston

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

www.jisc.ac.uk/...opensciencerpt.aspx

shared by Lisa Johnston on 12 Jan 10 - Cached
  • Lisa Johnston on 12 Jan 10
     
    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.
Lisa Johnston

Digital Curation Centre: DCC SCARP Project - 0 views

www.dcc.ac.uk/scarp

report DCC

shared by Lisa Johnston on 25 Jan 10 - Cached
  • Lisa Johnston on 25 Jan 10
     
    18 January 2010 | Key perspectives | Type: report The Digital Curation Centre is pleased to announce the report "Data Dimensions: Disciplinary Differences in Research Data Sharing, Reuse and Long term Viability" by Key Perspectives, as one of the final outputs of the DCC SCARP project. The project investigated attitudes and approaches to data deposit, sharing and reuse, curation and preservation, over a range of research fields in differing disciplines. The synthesis report (which drew on the SCARP case studies plus a number of others, identified in the Appendix), identifies factors that help understand how curation practices in research groups differ in disciplinary terms. This provides a backdrop to different digital curation approaches.
Lisa Johnston

The Current Status of Scientific Data Sharing and Spatial Data Services in China | Moun... - 2 views

www.mtnforum.org/...nd-spatial-data-services-china

shared by Lisa Johnston on 31 Mar 11 - No Cached
  • Lisa Johnston on 31 Mar 11
     
    There are a lot of scientific data repositories in China that have been growing since the 90's. Interesting sea change of ethics and sharing practices.
Stephen Hearn

Developing Best Practices for Supplemental Materials - 0 views

river-valley.tv/ces-for-supplemental-materials

shared by Stephen Hearn on 07 Jul 11 - No Cached
  • Stephen Hearn on 07 Jul 11
     
    An interesting presentation (19 min.) by Linda Beebe, Senior Director of PsycINFO for the American Psychological Association, that places dataset management in the larger and shifting context of managing journal articles' supplemental materials.
Amy West

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

www.ploscompbiol.org/...10.1371%2Fjournal.pcbi.1000204

shared by Amy West on 12 Nov 08 - Cached
  • 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.
  • ...27 more annotations...
  • 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.
  • Amy West on 12 Nov 08
     
    Yes, but Alexandria was also a lot smaller; not totally persuaded by analogy here...
Lisa Johnston

Sustainable Digital Preservation and Access - 0 views

www.sdsc.edu/...PR121608_brtf_report.html

data storage best practices

shared by Lisa Johnston on 08 Jan 09 - Cached
  • Lisa Johnston on 08 Jan 09
     
    While storage and technological issues have been at the forefront of the discussion on digital information, relatively little focus has been on the economic aspect of preserving vast amounts of digital data fundamental to the modern world.
David Govoni

NASA CoLab - 0 views

colab.arc.nasa.gov

research science education e-learning e-research e-science opensource communities communities-of-practice NASA science2.0 secondlife virtual

shared by David Govoni on 10 Jan 09 - Cached
  • David Govoni on 10 Jan 09
     
    "NASA CoLab connects communities inside and outside NASA to collaborate. What types of collaboration? Just about anything! From providing a framework for people to work directly with NASA scientists to supporting open source projects, we stimulate explora
Amy West

WHAT EXPLAINS THE GERMAN LABOR MARKET MIRACLE IN THE GREAT RECESSION? - 0 views

www.nber.org/w17187.pdf

data management citations social science practices

shared by Amy West on 07 Jul 11 - No Cached
  • Amy West on 07 Jul 11
     
    This paper uses, among other sources, the US Bureau of Labor Statistics CPS data that covers 1960-2009 to analyze just 2 years of data. The authors do cite the whole CPS, but you have to read the paper to see which bits of that set matter to this paper. The bulk of the paper itself is their explanation of the various statistical methods they used to support their conclusions. The data is neither novel or unique to them. Their analysis however, may be novel and is certainly unique to them. They also provide some technical documentation, e.g. we did x with SPSS. So, ideally, it would be nice to have a citation to the paper, to the 2 year subset of data relevant to it and a citation to the entire BLS CPS data. This is not agricultural economics, but I think that pretty similar patterns will be found there too.
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