Ende September 2015 hat die DFG Leitlinien zum Umgang mit Forschungsdaten verabschiedet.
Leitlinien zum Umgang mit Forschungsdaten (DFG)
Sie stellen nicht nur die Bedeutung von Forschungsdaten als Grundlage wissenschaftlichen Arbeitens deutlich heraus, sondern geben gezielte Hinweise für die Projektplanung und Antragstellung. Letztlich ist damit jeder Wissenschaftler und jede Wissenschaftlerin aufgefordert, sich über das Datenmanagement bereits vor Beginn eines Forschungsprojektes gezielt Gedanken zu machen. Gleichzeitig informiert die DFG über prinzipielle Anforderungen an Forschungsdaten:
Dabei wird berücksichtigt, dass in den einzelnen Fachdisziplinen ganz unterschiedliche Regularien existieren, wie mit Forschungsdaten umgegangen wird. Gerade in den Geisteswissenschaften fehlt es noch an klaren Standards und Voraussetzungen, um Forschungsdatenmanagement im Verbund erfolgreich zu betreiben. Die Initiativen der DFG sind daher ein wichtiges Zeichen.
Als Forscherin, die sich schon länger mit eHumanities beschäftigt, als es das Wort überhaupt gibt, unterstütze ich nachdrücklich auch den letzten Absatz der Leitlinien. Hier wird gefordert, die eben nicht in Publikationen abrechenbaren Leistungen von Forscherinnen und Forschern bei der Würdigung wissenschaftlicher Qualifikationen stärker zu berücksichtigen. Allerdings fehlt es – jedenfalls in den Geisteswissenschaften – in dieser Hinsicht noch an guten Ideen, wie dies auch praktisch umsetzbar ist.
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The point about recognizing work that doesn’t directly appear in publications is especially important. Data management often takes a lot of effort but receives little visibility.
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Thanks for highlighting the DFG’s new guidelines — this is a timely and important step for research data management, especially because project planning and data handling need to be considered from the very beginning. I also appreciate the point about recognizing work that doesn’t show up directly in publications; that’s still a big issue in many fields. For anyone interested in how data-driven thinking can be made more practical and accessible, 格ゲー認知診断 is worth a look.
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Ein wichtiger Beitrag, weil Forschungsdatenmanagement oft erst dann sichtbar wird, wenn Ordnung, Nachvollziehbarkeit oder langfristige Verfügbarkeit fehlen. Klare Leitlinien helfen dabei, Forschung nicht nur zu dokumentieren, sondern auch später verständlich und nutzbar zu machen. In der Audioarbeit ist es ähnlich: Mit einem [Audio Trimmer](https://freemusiccreator.ai/audio-trimmer) entfernt man Überflüssiges, damit der wesentliche Inhalt klarer bleibt.