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Tutor profile: Stephen C.

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Stephen C.
Reference Librarian available to assist you with research (including scientific/medical)
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Questions

Subject: Writing

TutorMe
Question:

How should I cite an imaginary book within a work of fiction?

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Stephen C.
Answer:

Since the imaginary work does not, by definition, exist in the real world, you would cite the page its mentioned on in the real work.

Subject: Library and Information Science

TutorMe
Question:

What is the best way to search for the most recent information on training techniques for red pandas?

Inactive
Stephen C.
Answer:

There are five key components to a successful literature search: - Appropriate database(s): choose a database(s) that specializes in curating the subject you need - Synonymous searching: consider appropriate synonyms from the subject (e.g., training is now referred to as enrichment) - Truncation: use wildcards (*) to lengthen a word's root to find all instances (e.g., eat* includes eat, eats, eating, and eaten) - Boolean operators: AND, OR, and NOT can broaden or limit searches - Phrase searching: adding quotation marks to a search can limit results to an exact phrase (e.g., "Houston Texans" will only return results about the NFL team; not using quotation marks will return results that merely have both keywords, Houston AND Texans) When searching for specific animals, be sure to include the scientific name (e.g., Ailurus fulgens for red pandas). Since a scientific name is in Latin, like most foreign phrases, you do not need to use Phrase Searching. In scientific literature, the most recent results are within the last 3-5 years. This is because it takes time for papers to be read and themselves cited by other researchers. An appropriate search string for recent information on training of red pandas would: - Be in a database like Zoological Record - Be within the last five years - Search string - ("red panda*" OR Ailurus fulgens) AND (train* OR enrich*)

Subject: Data Science

TutorMe
Question:

You are seeking a federal grant for an observational survey of animals in their natural habitat. Each federal grant requires that you have a plan for the management and long-term (i.e., permanent storage) of your raw, synthesized, and published data. What is the theory behind data management? What data should be gathered? How? How can you ensure your data are standardized? How should you maintain your data to comply with the terms of the federal grant?

Inactive
Stephen C.
Answer:

When considering the collection and management of data, specifically for living species, the following are required: - Animal data is collected on the 'Genus species' level, while individual animals should be identified by either a consistent number or common name (e.g., GIRAFFE001 or LittleJohn) - All data within a given column should conform to accepted scientific measurements (i.e., metric system) - Programs like OpenRefine can help you identify and quickly edit errata (errors in data) - The Digital Curation Lifecycle recommends six redundancies (i.e., backups) of data. - One of these redundancies should be an open repository (e.g., university Scholarly Commons). This guarantees perpetual, open access. - Data should be shared in a long-term file format (i.e., comma-separated value sheet, like Excel) when possible, or include source code for the original program

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