11 Matching Annotations
  1. Dec 2015
    1. A Scientist, His Work and a Climate Reckoning

      An example of what it means to create and record high quality measurements. It takes time and effort and focus. Quality measurements cost money.

    1. A Safety Net for Scientific Data

      A short article that highlights several aspects and issues regarding the long-term preservation (and re-use) of research data.

    1. But the essence of his scientific legacy was his passion for doing things in a meticulous way. Itexplains why, even as challengers try to pick apart every other aspect of climate science, his half-century record of carbon dioxide measurements stands unchallenged

      An example of what it means to create and record high quality measurements. It takes time and effort and focus. Quality measurements cost money.



    1. Data curation is critical for scientific data digitization, sharing, integration and utilization

      This sentence assumes that there is a well-known and agreed to meaning of "data curation". The content of the paper does provide examples of what might be curation activities.



    1. The WHO’s International Agency for Research on Cancer weighs the strength of the scientific evidence that some food, drink, pesticide, smokable plant, whatever is a carcinogen. What it does not do is consider how much that substance actually increases your risk for actually getting cancer—even if it differs by magnitudes of 100.

      The article highlights two issues with research data. One is significance. Risk assessment requires a context to be useful information. Another is how classification can lead to confusing inferences.

    1. We propose linked open data as enabling a more interlinked and easily navigable scholarly environment that would permit: better integration of research materials with primary and secondary source objects and datasets; the potential to bridge but also address the specificities of the nomenclature, discourses, and methodologies of humanities disciplines and sub-disciplines; and the ability to respect institutional and individual investments in ownership or credit of resources by allowing for identifiable collections of data while fostering resource interlinking.

      The proposed benefits apply to all research domains, not just Humanities.

    1. Science is not about certainty. Science is about finding the most reliable way of thinking at the present level of knowledge. Science is extremely reliable; it’s not certain. In fact, not only is it not certain, but it’s the lack of certainty that grounds it. Scientific ideas are credible not because they are sure but because they’re the ones that have survived all the possible past critiques, and they’re the most credible because they were put on the table for everybody’s criticism.

      This notion can be hard to understand: reliable but not certain.

    1. Edwards, A Vast Machine, p. 489, fn 15. A short and informative description of climate reanalysis data issues. I think it is illustrative of data issues in other domains and projects.

    1. An intentional provocation, but the idea that theory is not needed is attractive. A better project is to construct a better understanding of both theory and data.

    1. Making research data available for others (everyone?) to view, reuse, and build on is a key requirement for scientific work in the 21st century. This article highlights how much and how fast data can become lost.