I am interested to collect information of presence and identity of bee specimens in museums for understand biodiversity and the change to which they were subject during many years. However, I know that there are many problems with the integration of data.
1st. there are many mistakes and bias of the areas sample and identification of specimens. I know about some programs that can make the revision of the data and detect errors.
2nd. However, I will like to know how if is there a general experience or strategy. How to integrate and analyze the data? I want to know if someone has some experience of what are the best tools or what is necessary to create an integrative strategie. Is actually really necessary an integrative strategy or it is something that is not of much interest?
thanks for your opinion,
I am sorry my field is plant taxonomy, however there are some my colleges are related to Bees
I am not sure I understand your question correctly. How do the "programs" (you mean software or routine checking program?) can detect errors in taxonomical identification?
Can you re-phrase your needs, please?
Yes Dmitry Telnov. When you have so many specimens to analize there are different types of errors as bias in the data and identification mistakes. Of course the programs cannot detect if the identification was not correct, but can detect if there are mistakes with the names, they are incomplent or there are many synonyms. The detection of this mistakes will of course help a lot to simplify the work. I know that there are some that do this. The question is how efficient they are? how big the matrices they can analyze? and if they can work efficiently with data from different sources?
- Badges
- Science topic