Context of Use:

It provides a way to retrieve scientific publications very accurately. The system uses the SPARQL language to search scientific publications in full text as well as named entities identified in the full text.

Need:

It provides a method to extract scientific statements from the literature based on standard terminologies and controlled vocabularies

Added Value:

Flexibility, precision.

Competitive Advantage:

Compared to classic text mining, named entities identified in the full text improve the recall of queries by exploiting synonyms and semantic relationships declared in the terminologies, it also increases precision because queries allow to focus on structural elements (given section, paragraph, and/or sentence) on demand.

A qualitative upgrade on the current use of biodiversity data:

Given a topic of interest, the service can be used to extract relevant statements from the literature with good precision.

Exemplary Use of the Service:

Find biotic interactions described in the literature between a given species and other ones.

To find biotic interactions described in the literature between a given species and others, you can follow a structured approach that leverages both scientific databases and specific querying techniques. Here's a step-by-step guide on how to proceed:
1. Define the Target Species
  • Primary Species: Clearly define the species you are interested in. For example, let's say you choose the European honey bee (Apis mellifera).
  • Type of Interactions: Determine the types of biotic interactions you're interested in, such as predation, symbiosis, competition, or parasitism.
2. Identify Suitable Databases
  • PubMed Central (PMC): This is a free full-text archive of biomedical and life sciences journal literature.
  • Web of Science or Scopus: These are comprehensive databases covering a wide range of scientific disciplines.
  • Biodiversity Databases: Databases like the Global Biodiversity Information Facility (GBIF) or the Encyclopedia of Life (EOL) can provide additional context.
3. Construct Keyword Searches
  • Combine Species and Interaction Keywords: Use combinations of the species name (both common and scientific) with terms related to biotic interactions, like "symbiosis", "predation", or "competition".
  • Search Variations: Consider different variations and synonyms of your keywords to capture a broader range of relevant literature.
4. Use Advanced Search Options
  • Field-Specific Searches: Use field-specific search options to narrow down your results, such as searching within the abstract, title, or keywords.
  • Date Filters: Apply date filters to focus on the most recent research, if relevant.
5. Analyze Search Results
  • Screen Titles and Abstracts: Initially, review the titles and abstracts to identify the most relevant articles.
  • Full-Text Review: For selected articles, read the full text to extract detailed information about the biotic interactions.
6. Extract and Compile Data
  • Data Extraction: Extract details about the nature of the interaction, the species involved, and the context or conditions of these interactions.
  • Create a Database: Compile this information in a structured format, like a spreadsheet or database.
7. Consult Review Articles and Meta-Analyses
  • Comprehensive Overviews: Look for review articles or meta-analyses that summarize biotic interactions involving your species of interest.
8. Explore Supplementary Resources
  • Citations and References: Check the references and citations of your key articles to find additional relevant literature.
  • Expert Consultation: Consider reaching out to experts or researchers who specialize in your species or its interactions.
9. Continuous Update
  • Stay Updated: Set up alerts in databases to be notified of new publications related to your topic of interest.
10. Consider Ethical and Legal Aspects
  • Data Usage: Make sure to respect copyright and data usage policies when using and citing the information you gather.
By following this structured approach, you can comprehensively explore and document the biotic interactions of a given species as described in the scientific literature. This process not only aids in understanding the ecological role and relationships of the species but also contributes to the broader field of biodiversity research.


Competencies and Skills that are needed to use the Service:

Knowledge of the SPARQL language is required.

Challenges for the Users:

The SPARQL language is not straightforward for nonspecialists.

Users Role in the Service Development

The role of the users is important mainly in providing help to design and assess a natural language-based query system on top of SPARQL using MMLs.


Last modified: Sunday, 19 November 2023, 10:08 PM
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