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Science is still a very creative (i.e. non systematic) process. To create new "scientific findings" you need new insights. These insights typically come from pu

Science is still a very creative (i.e. non systematic) process. To create new "scientific findings" you need new insights. These insights typically come from publications/conferences/discussions with other researchers rather than big machine readable datasets.

return0 13y ago
Most research articles I read can be boiled down to a paragraph of substance, with the rest of the space filled with introductions and things we already know. Agree about conferences etc. but I don't see how articles create discussion, since most journals do not even have comment sections, and even those that do, rarely have any comments. Articles are an arcane notion used to gauge researcher's output, until something new and more efficient comes along. Ps. http://www.cell.com/neuron/retrieve/pii/S089662731300648X http://www.cell.com/neuron/retrieve/pii/S089662731300648X
- pcrh 13y ago
  Obviously this depends on the quality of an article, but there is more to the "extra bits" (i.e. that which is not plain data) than mere fluff. If you are very familiar with a topic (i.e have a PhD in precisely that area), the extra bits are not of much interest, though the methodology might be. If you have some passing familiarity, then the introduction and discussion can help you a lot in understanding the implications proposed for the data. Most biomedical experimentation takes place in the context of considerable amount of uncertainty, e.g. relevance of the model used for human disease, etc, and more, as described in the article you linked to, so it does help many readers to have some kind of context. The lack of discussion in biomedical articles is likely due to a fear of reprisals.
- mjn 13y ago
  Depends a bit on the area. You can machine-code results if the field is extremely static in its conceptual and epistemic framework, so it's just a matter of slotting new things in place. Some "industrial-style" science does work like that. But large areas don't. Most of the articles I read have the majority of the actual research going on in the text, not in whatever the "results" might nominally be. For example, a programming language paper might prove a few theorems about type-soundness, but it's rare that a new type-soundness theorem is really want you want out of the paper; that's just supporting apparatus. What's more interesting is the design discussion, motivation for why this feature was introduced and how it relates to previous features, explanation of how it was implemented, discussion of variants and future work, etc.

return0 13y ago

Most research articles I read can be boiled down to a paragraph of substance, with the rest of the space filled with introductions and things we already know. Agree about conferences etc. but I don't see how articles create discussion, since most journals do not even have comment sections, and even those that do, rarely have any comments. Articles are an arcane notion used to gauge researcher's output, until something new and more efficient comes along. Ps. http://www.cell.com/neuron/retrieve/pii/S089662731300648X http://www.cell.com/neuron/retrieve/pii/S089662731300648X

pcrh 13y ago
Obviously this depends on the quality of an article, but there is more to the "extra bits" (i.e. that which is not plain data) than mere fluff. If you are very familiar with a topic (i.e have a PhD in precisely that area), the extra bits are not of much interest, though the methodology might be. If you have some passing familiarity, then the introduction and discussion can help you a lot in understanding the implications proposed for the data. Most biomedical experimentation takes place in the context of considerable amount of uncertainty, e.g. relevance of the model used for human disease, etc, and more, as described in the article you linked to, so it does help many readers to have some kind of context. The lack of discussion in biomedical articles is likely due to a fear of reprisals.
mjn 13y ago
Depends a bit on the area. You can machine-code results if the field is extremely static in its conceptual and epistemic framework, so it's just a matter of slotting new things in place. Some "industrial-style" science does work like that. But large areas don't. Most of the articles I read have the majority of the actual research going on in the text, not in whatever the "results" might nominally be. For example, a programming language paper might prove a few theorems about type-soundness, but it's rare that a new type-soundness theorem is really want you want out of the paper; that's just supporting apparatus. What's more interesting is the design discussion, motivation for why this feature was introduced and how it relates to previous features, explanation of how it was implemented, discussion of variants and future work, etc.