Engineering Research Library Database Searching: Quotes, Boolean Operators, and Advanced Techniques

Phase 1 — Differences between Google and library databases

• Google understands phrases and natural language; library databases do not generally interpret synonyms or phrases unless you specify them explicitly.
• If you type a multiword concept without quotes in a library database, you may get articles that contain any of the words separately (e.g., public library OR public health OR public transportation), rather than the exact phrase.
• To search for an exact phrase, put it in quotes (e.g., "public health").
• Be mindful that databases often do not “read your mind” or infer synonyms; you must provide the precise terms you want to retrieve.
• Topic framing matters: sustainability, environmentalism, ecology are related but distinct terms; choose the one that best describes your topic and consider synonyms.

Phase 2 — Phrase searching and exact terms

• Use quotes around exact phrases to avoid broad results. Example: "remote sensing".
• If your topic is a specific term, such as signal processing, you may treat it as a single phrase for more precise results.
• Databases typically require you to specify keywords explicitly rather than asking questions.

Phase 3 — Boolean logic and search structuring

• Boolean operators you’ll use: AND, OR, NOT (and sometimes parentheses for grouping).
• OR expands results to include either term; AND narrows results by requiring both terms; NOT excludes terms you don’t want.
• Example concept: wildfire and drones
  • Simple: wildfire AND drones
  • Broader with synonyms: (wildfire OR "forest fire") AND drones
• Parentheses group terms to control the logic (like in algebra).
• NOT can be used to remove results you don’t want (e.g., NOT military).
• Practical example: to avoid surveillance-focused articles, you might add NOT surveillance.
• Note: NOT is not used as frequently, but can clean up results when noise is high.

$ext{Example search strings:}$

• "wildfire" AND drones
• ("forest fire" OR wildfire) AND drones AND (remote sensing OR "remote-sensing")
• (wildfire OR "forest fire") AND drones AND "remote sensing" AND California
• (wildfire) AND drones NOT military

Phase 4 — Building a search funnel (example with wildfire, drones, remote sensing)

• Start broad: wildfire or forest fire
  • Result may be huge; adjust focus to a subtopic like early detection.
• Narrow to a subtopic: early detection (the first moment when a wildfire is detected).
• Add a modality/application: remote sensing to focus on detection methods.
• Finally, add the technology: drones to specify how UAVs contribute.
• Perceived benefit of narrowing: more manageable results (e.g., ~200 peer-reviewed articles in scope).
• Localize further by geography when appropriate (e.g., California) if needed.

$ext{Funnel example:} \ ( ext{wildfire} \ \lor \ ext{forest fire}) \\land \ ext{early detection} \\land \ ext{remote sensing} \\land \ ext{drones} \\land \ ext{California}$

• Observations from the demonstration:
  • Initial broad search yielded $143{,}000$ results.
  • Adding remote sensing reduced to $2{,}500$ results.
  • Adding drones reduced to $191$ results.
  • A target of around $200$ results is considered a practical size for upper-division work.
• If the topic is brand new (e.g., a recent wildfire event), scholarly literature may lag behind news coverage; newspapers may report on events sooner than peer-reviewed articles.

Phase 5 — Advanced search in OneSearch and database-specific searching

• Start in the library homepage -> Advanced Search for upper-division work.

• Use filters to refine results:

  • Full text online (digital access)
  • Peer-reviewed journal articles (not conference proceedings for this assignment)
  • Last five years (to ensure recency)
  • Apply filters and lock them to prevent losing settings when adding terms.

• Demonstration highlights:

  • OneSearch aggregates across many databases but may not index every database; deeper searching may be needed in specialized databases.
  • Example database emphasis for engineering: ME, civil, electrical, etc.
  • Subject headings act as a powerful way to locate all content under a topic; results under a subject heading collect related works.

• Practical workflow:

  • Begin with a broad topical term (e.g., wildfire).
  • Narrow by subtopic (e.g., early detection).
  • Add modality (remote sensing).
  • Add technology (drones).
  • Optionally filter by geography (California) or time window (last five years).
  • If results are too numerous or too few, adjust terms or broaden/narrow as needed.

Phase 6 — An example article search in OneSearch

• Steps:
  1) Library homepage → Advanced Search → wildfire
  2) Apply filters: Full text online, Peer-reviewed journals, Last five years
  3) Add term: remote sensing
  4) Add term: drones
  5) Review results (aim for ~200 results):

  • If too many, add a geographical or topic constraint
  • If too few, remove a constraint or broaden terms

• Use the subject heading feature to focus on a subtopic (e.g., machine learning, neural networks) if relevant to the article.

• Open an article landing page to:

  • Confirm full text availability and the database hosting the article
  • Read abstract to confirm relevance
  • Check the article’s subjects for related content

• When ready, click to generate/copy the APA citation draft from OneSearch (APA 7th edition). Compare with the official APA style guide if needed. If using another database (e.g., ScienceDirect), citation generation may be less convenient.

• Important notes:

  • Article landing pages also show a stable permalink (permalink) for consistent access; avoid session IDs in citations.
  • OneSearch’s generated citation draft may have minor errors; verify against the APA Publication Manual.
  • If the system shows a red warning about citation accuracy, double-check manually.
  • If you cannot access a full text, use the library’s authentication steps (Account/login) to regain access.

• Example of a potential article landing page elements:

  • Title, authors, journal, year, abstract
  • Full text availability links (e.g., Academic Search Complete, etc.)
  • Subjects and keywords
  • Citation generation button (APA, MLA, etc.)
  • Permalink (stable URL)

Phase 7 — Evaluating and exporting citations

• Always verify the article is peer-reviewed and published within the required window (e.g., last five years).

• Use the landing page to confirm the proper bibliographic details before generating the citation.

• APA citation basics (seventh edition):

  • In-text citation examples and reference list formatting matter; incorrect punctuation/ordering can be a drop in grade.
  • Pay attention to capitalization, and use proper hanging indentation in the reference list.

• The library emphasizes the importance of accurate citations for credibility and reproducibility of research. Do not rely on AI-generated citations without verification.

• If you cite sources found via Google Scholar or machine-generated suggestions, trace them to the original database article to verify authors, year, title, and journal.

• Practical tips for citation reliability:

  • Use the library’s APA resources or the official APA Publication Manual to confirm formatting.
  • If you need authoritative guidance, consult the APA manual in print (or its reputable online resources).
  • When citing, include all authors, year, article title, journal name, volume, issue, and page numbers as applicable.
  • For non-article sources (videos, blogs, YouTube), apply the appropriate APA format for that source type.

Phase 8 — Using and navigating multiple databases

• OneSearch is a gateway to many databases, but it may not index every database; for engineering topics, consult engineering-focused databases as needed.
• Example databases mentioned:
  • ScienceDirect (engineering, science, technology, medicine)
  • Engineering Village (engineering literature)
  • GreenFILE (sustainability-related topics)
  • Other discipline-specific databases via the library’s A–Z list
• Access considerations:
  • You may encounter authentication prompts; if you’re deauthenticated, re-enter through the library portal (Accounts) to restore access.
  • Some databases display content differently (e.g., citation tools or export options); you may need to adapt to each database’s interface.

Phase 9 — Practical research workflow and class logistics

• Instructor-led activities include live demonstrations and student participation in real-time searches.
• Students are encouraged to: run searches, find peer-reviewed articles within the last five years, and share their chosen article in chat.
• Exit-ticket prompts often ask what was learned or what was new, to gauge understanding and prepare for next session.
• Project planning notes:
  • There are group topics to be identified and discussed; breakout rooms will be used for collaboration.
  • Students should begin identifying topics before the next session and prepare to build their paper around a chosen topic.
• Course logistics mentioned:
  • Quiz 1 and the evaluation SAR are due tomorrow by 11:59 PM.
  • The library is open until midnight (and 24 hours during finals).
  • Study rooms can be booked up to four days in advance.
  • Google Scholar can be a useful starting point for narrowing topics before moving to university databases.

Phase 10 — Ethical and practical considerations

• Do not rely on AI-generated citations (e.g., from ChatGPT) for final references; verify with the actual database articles.
• The definitive source for APA citations is the official Publication Manual; the library can loan copies or provide access to guidelines.
• Use primary sources and verify peer-review status rather than relying on secondary or AI-generated citations.
• Respect copyright and access limitations; use the library’s legitimate access points and stable permalinks for reproducible access.

Quick reference — Key numbers and terms

• Initial wildfire search results: $143{,}000$
• After adding remote sensing: $2{,}500$
• After adding drones: $191$
• Ideal manageable results: around $200$
• Broad topic search result example: $1{,}000$ to $1{,}400$ in ScienceDirect (depending on query)
• Reference to library resources: over $400$ databases (library-wide); OneSearch covers content from many databases, with some slides citing $480$ databases across all topics
• Page-length constraint example in ScienceDirect: you might constrain to page length (e.g., at least $8$ pages)
• Time window for recency: last $5$ years
• Important dates and times:
  • Quiz 1 and evaluation SAR due tomorrow by 11:59 PM
  • Finals period extends library hours to 24 hours
• Common database features:
  • Full text online filter
  • Peer-reviewed filter
  • Subject headings to narrow results
  • Citation tools (APA draft generation)
  • Permalink for stable access
• Common workflow concepts:
  • Use quotes for exact phrases
  • Use AND/OR/NOT and parentheses for complex queries
  • Lock filters to preserve search settings
  • Use advanced search when starting from scratch
  • Validate articles by abstract, IMRAD structure, and relevance

Summary takeaway

• Effective library searching combines exact phrase queries, Boolean logic, and targeted filters to transform a broad topic into a focused set of peer-reviewed, recent articles.
• Use quotes for exact phrases, build a funnel (broad → narrow), and rely on subject headings to pull related content under a single topic.
• When using databases like ScienceDirect, be prepared to navigate interface nuances, extract citations carefully, and verify references against APA guidelines.
• Always consider recency, relevance, and scholarly credibility; when in doubt, consult a librarian or use the library’s chat support to confirm peer-review status and access.
• Google Scholar can be a starting point, but transition to library databases for authoritative access, full text, and verified citations.