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Experimental procedures are strange beasts. Loathed (at least temporarily) by those who must prepare them yet central to science, the lowly experimental section is mostly forgotten in the daily struggle of publish or perish. Abstracts, discussions, and conclusions will probably be useless 20 years from now, at least in chemistry. In contrast, the experimental section (and the tables based on them) may well live forever.

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Ein Fehler ist aufgetreten. Sieh dir dieses Video auf www.youtube.com an oder aktiviere JavaScript, falls es in deinem Browser deaktiviert sein sollte. As part of research I’m doing on a new collaborative chemistry Web application, I’ve been using quite a few social networking and news sites.

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A recent D-F article discussed the potential for online videos in chemical research. Although chemistry has been slow to catch on, biologists have been busy creating phenomenal video content. One of the best efforts in this space is the Journal of Visualized Experiements (JoVE). YouTube videos spread so quickly in part because of their ability to be embedded into other Websites.

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Like SMILES, InChI is a line notation that can be used to encode and store chemical information relatively efficiently. Although there are a number of scenarios where this strategy is used, what many of them have in common is the need to eventually convert an InChI into a human-readable form. In most cases, this form will be a 2D chemical structure.

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Web 2.0 may be all about participation, but the numbers reported by The McKinsey Quarterly suggest a self-selecting oligarchy rather than a democracy. Success may well depend more on engaging the top 2-10% of users rather than appealing to all of them. Food for though when forming your next community, be it electronic or otherwise.

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With the ever-increasing volume and heterogeneity of data that we need to cope with, data visualization is a skill that every effective scientist needs to master. Like most essential scientific skills, data visualization is one of those things that is not so much learned in classes, but rather absorbed from one’s surroundings. So if you want to improve your data visualization skills, where can you turn?