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The mission of this project is to find efficient ways to normalize and integrate species-interaction data. By making this data readily available, GloBI will enable researchers and enthusiasts to answer questions about localized, one-to-one species interactions and big-picture changes in species interactions over time. For example, GloBI can answer which species an Angel Shark (Squatina squatina) eats in the Gulf of Mexico, or return the results of a query for the number of Angel Sharks feeding in the Gulf of Mexico between 2005 and 2010.
There's many ways to access the GloBI interaction data. Please see Home#accessing-species-interaction-data for your options.
... correct taxonomic names (e.g. Homo saliens --> Homo sapiens) without changing the original data file?
See Taxonomy-Matching#submitting-name-corrections.
See How to Contribute Data to Global Biotic Interactions? for a list of options on how to contribute data.
Submit an issue and describe what it is you think should be changed (see this issue for an example).
This project is funded by EOL's Rubenstein Fellowship Program 2013 and would not be possible without the hard work and dedication of academic, government, and citizen scientists around the world that have gathered species interaction data and shared their datasets. For more news about our efforts, please visit our blog.
GloBI contains code to normalize and integrate existing species-interaction datasets and export the resulting integrated interaction dataset.
As part of the species-interaction normalization process, GloBI provides mechanisms for robust taxonomy matching. Please see Taxonomy Matching for more information.
GloBI attempts to re-use existing Ontologies and Vocabularies to link terms used in data sources to promote the machine readability of the data and integration with other linked datasets.
Most original dataset are managed in this github repository. For a step-by-step plan to update/ edit datasets, please visit Dataset Management.
To access normalized species interaction data you can download data in bulk, use software libraries (R and javascript) or access the API directly. The table below gives an overview of ways to access the data.
| Name | Description | Link |
|---|---|---|
| data archives | GloBI's data page links to data archives formats like Darwin Core, tsv, csv, rdf/nquads and neo4j graphdb | https://globalbioticinteractions.org/data |
| Web API | species interaction API to help integrate interaction data into your (web) app | see api wiki for some example |
| javascript libraries | for embedding interaction data (and widgets) into your web app | globi.js for widgets and globi-data.js for data api |
| R library | for accessing GloBI data in R | rglobi (github) |
| sparql endpoint | exposing interaction data using apache jena's fuseki, an rdf store | sparql console, example query that should return first ten triples in json format |
| neo4j rest api | execute Cypher queries or use other neo4j rest api operations | Neo4j Data Browser, more [[examples |
mvn clean install runs tests, builds the eol-globi-data tool, normalizes the imported datasets, and exports the normalized data to various data archives such as a neo4j graphdb, darwin core archive and rdf/turtle archive. This process might take awhile, depending on your network and computer configuration.
As part of this Maven build, the eol-globi-data tool is executed in module eol-globi-datasets and imports, normalizes, integrates, and exports the biotic interaction datasets.
To explore the resulting normalized datasets, various methods are used. At time of writing (2018), this includes a REST-y api, a triple store and a neo4j graph database. To get some ideas on how to run these services, please have a look at https://github.com/jhpoelen/globi-server-scripts or open an issue in case you get stuck.
The datasets below are (re-)created daily. A list of interaction dataset contributors can be found here.
