You can find the most current version at http://ssarherps.org/cndb/

The URIs are stateful! You can always use the same link to recreate the exact parameters.

Specifically, the URI is a Base-64 encoded query string of what is loaded asynchronously.

Therefore,

http://ssarherps.org/cndb/#YmF0cmFjaG9zZXBzJmxvb3NlPXRydWU

has the query string reconstructed from the bit after the hash:

Base64.decode("YmF0cmFjaG9zZXBzJmxvb3NlPXRydWU")
// returns "batrachoseps&loose=true"

You can generate links that way, corresponding to the options given in the following API section.

1. q: The main query, for common names or species.
2. fuzzy: if truthy, use a similar sounding search for results, like SOUNDEX. Note this won't work for authority years or deprecated scientific names. Default false
3. loose: Truthy. Don't check for strict matches, allow partials and case-insensitivity Application default true; API default false
4. only: restrict search to this csv column list. Return an error if invalid column specified.
5. include: Include additional search columns in this csv list. Return an error if invalid column specified.
6. type: restrict search to this major_type. Literal scientific match only. Return an error if the type does not exist. Default none
7. filter: restrict search by this list of {"column":"value"} object list. Requires key "BOOLEAN_TYPE" set to either "AND" or "OR". Return an error if the key does not exist, or if an unknown column is specified. This should be supplied as a URL-encoded JSON string (eg, %7B%22species_authority%22:%22neill%22,%22boolean_type%22:%22and%22%7D) or a Base64-encoded string (eg, eyJzcGVjaWVzX2F1dGhvcml0eSI6Im5laWxsIiwiYm9vbGVhbl90eXBlIjoiYW5kIn0), where both examples represent {"species_authority":"neill","boolean_type":"and"}. Default none
8. limit: Search result return limit. Default unlimited
9. order: A csv list of columns to order by. Defaults to genus, species, subspecies

The JSON result gives the following parameters:

1. status: boolean true or false. true is returned on an good search, regardless of hits.

2. (false status only) error: A technical error message

3. (false status only) human_error: A message to display to users.

4. (bad parameters only) given: The provided parameters.

5. (bad filter only) columns: The provided column list.

6. (bad filter only) bad_coulmn: The invalid column.

7. result: An object containing one taxon per numeric key, which itself contains:

   id # internal counter
   common_name
   genus
   species
   subspecies
   deprecated_scientific # Object, eg {"Genus species":"Authority:Year"}
   major_type # eg, squamata
   major_common_type # eg, lizard, turtle.
   major_subtype # eg, snake v. non-snake, aquatic vs. tortoise.
   minor_type # eg, lacertid, boa, pleurodire, dendrobatid; roughly a ranked "family", scientific only
   linnean_order # Deprecated, included for compatibility
   genus_authority #  eg, "Linnaeus"
   species_authority # eg, "Attenborough"
   authority_year # eg, {2013:2014} in the format {"Genus Authority Year":"Species Authority Year"}
   notes # Miscellaneous notes
   image # Path to an image, relative to ssarherps.org/cndb/, if it exists
   image_credit
   image_license
   taxon_author # Last edited by ...
   taxon_credit # Cite taxon info

8. count: The number of results

9. method: The way the search was executed

10. query: The requested search

11. params: The checked matches

12. query_params: A breakdown of your computed query

    1. bool: The used boolean_type
    2. loose: boolean true or false
    3. fuzzy: boolean true or false
    4. order_by: The way the results are sorted
    5. filter: An object representing any applied filters
       1. had_filter: boolean true or false
       2. filter_params: The used filter parameters
       3. filter_literal: The provided filter in the query

13. execution_time: The time to execute your query and return your result, in ms.

Please note that all entries are returned in lower case, except for result.[taxon].notes and result.[taxon].image (where an image exists and the path includes mixed case).

As the rest of the data have strict formatting requirements, all other formatting is left up to the application to correctly apply CSS styles to generate the desired case.

Please note that the example JSON results may not have all of the fields or data in the result key of the most recent version. There will be no compatability breaking. All the correct fields are listed above.

The search algorithm behaves as follows:

1. If the search is_numeric(), a loose search is done against the authority_year column in the database. The returned method with the JSON is authority_year. Example:

   {"status":true,"result":{"0":{"id":"562","genus":"eurycea","species":"subfluvicola","subspecies":"","common_name":"ouachita streambed salamander","image":"","major_type":"caudata","major_common_type":"salamanders","major_subtype":"brook salamanders","minor_type":"","linnean_order":"caudata","genus_authority":"rafinesque","species_authority":"steffen, irwin, blair, and bonett","authority_year":"{\"1822\": \"2014\"}","deprecated_scientific":"","notes":""},"1":{"id":"70","genus":"macrochelys","species":"appalachicolae","subspecies":"","common_name":"suwannee alligator snapping turtle","image":"","major_type":"testudines","major_common_type":"turtles","major_subtype":"alligator snapping turtles","minor_type":"","linnean_order":"testudines","genus_authority":"gray","species_authority":"thomas, granatosky, bourque, krysko, moler, gamble, suarez, leone, enge, and roman","authority_year":"{\"1855\": \"2014\"}","deprecated_scientific":"","notes":""}},"count":2,"method":"year_search","query":"2014","params":{"authority_year":"2014"},"query_params":{"bool":false,"loose":true,"order_by":"genus,species,subspecies","filter":{"had_filter":false,"filter_params":null,"filter_literal":null}},"execution_time":1.98006629944}

2. The search is then checked for the absence of the space character. If no overrides are set, common_name, genus, species, subspecies, major_common_type, major_subtype, and deprecated_scientific columns are all searched. The returned method is spaceless_search. Example:

   {"status":true,"result":{"0":{"id":"484","genus":"aneides","species":"lugubris","subspecies":"","common_name":"arboreal salamander","image":"","major_type":"caudata","major_common_type":"salamanders","major_subtype":"climbing salamanders","minor_type":"","linnean_order":"caudata","genus_authority":"baird","species_authority":"hallowell","authority_year":"{\"1851\": \"1849\"}","deprecated_scientific":"","notes":""}},"count":1,"method":"spaceless_search","query":"arboreal","params":{"common_name":"arboreal","genus":"arboreal","species":"arboreal","subspecies":"arboreal","major_common_type":"arboreal","major_subtype":"arboreal","deprecated_scientific":"arboreal"},"query_params":{"bool":"OR","loose":true,"order_by":"genus,species,subspecies","filter":{"had_filter":false,"filter_params":null,"filter_literal":null}},"execution_time":3.57890129089}

3. The search is then checked for spaces.

   1. If a filter is set (with the required boolean_type parameter):

      1. If there is two or three words, the first word is checked against the genus column, second against the species column, and third against the subspecies column. The returned method is scientific. Example

         {"status":true,"result":{"0":{"id":"235","genus":"farancia","species":"erytrogramma","subspecies":"seminola","common_name":"southern florida rainbow snake","image":"","major_type":"squamata","major_common_type":"snakes","major_subtype":"mudsnakes and rainbow snakes","minor_type":"","linnean_order":"serpentes","genus_authority":"gray","species_authority":"neill","authority_year":"{\"1842\": \"1964\"}","deprecated_scientific":"","notes":""}},"count":1,"method":"scientific","query":"farancia erytrogramma","params":{"species_authority":"neill"},"query_params":{"bool":"and","loose":true,"order_by":"genus,species,subspecies","filter":{"had_filter":true,"filter_params":{"species_authority":"neill","boolean_type":"and"},"filter_literal":"{\"species_authority\":\"neill\",\"boolean_type\":\"and\"}"}},"execution_time":2.66885757446}

      2. If the above returns no results, the deprecated_scientific column is checked. At the time of this writing, there are no entries in this column and this check will always fail. The returned method is deprecated_scientific.

      3. If the above returns no results, the common_name column is checked. The returned method is no_scientific_common. Example:

         {"status":true,"result":{"0":{"id":"235","genus":"farancia","species":"erytrogramma","subspecies":"seminola","common_name":"southern florida rainbow snake","image":"","major_type":"squamata","major_common_type":"snakes","major_subtype":"mudsnakes and rainbow snakes","minor_type":"","linnean_order":"serpentes","genus_authority":"gray","species_authority":"neill","authority_year":"{\"1842\": \"1964\"}","deprecated_scientific":"","notes":""}},"count":1,"method":"no_scientific_common","query":"rainbow snake","params":{"species_authority":"neill"},"query_params":{"bool":"and","loose":true,"order_by":"genus,species,subspecies","filter":{"had_filter":true,"filter_params":{"species_authority":"neill","boolean_type":"and"},"filter_literal":"{\"species_authority\":\"neill\",\"boolean_type\":\"and\"}"}},"execution_time":1.58905982971}

   2. If the filter parameter isn't specified, the above scientific and deprecated scientific searches are executed with "best-guess" boolean types (with returned methods scientific_raw and deprecated_scientific_raw). Example:

      {"status":true,"result":{"0":{"id":"683","genus":"taricha","species":"torosa","subspecies":"","common_name":"california newt","image":"","major_type":"caudata","major_common_type":"salamanders","major_subtype":"pacific newts","minor_type":"","linnean_order":"caudata","genus_authority":"gray","species_authority":"rathke, in eschscholtz","authority_year":"{\"1850\": \"1833\"}","deprecated_scientific":"","notes":""}},"count":1,"method":"scientific_raw","query":"taricha torosa","params":{"genus":"taricha","species":"torosa"},"query_params":{"bool":"and","loose":true,"order_by":"genus,species,subspecies","filter":{"had_filter":false,"filter_params":null,"filter_literal":null}},"execution_time":0.568151473999}

      1. If all these fail, and fuzzy is false, the fallback flag is set and a search is done against common_name. The returned method is space_common_fallback. Example:

         {"status":true,"result":{"0":{"id":"233","genus":"farancia","species":"erytrogramma","subspecies":"","common_name":"rainbow snake","image":"","major_type":"squamata","major_common_type":"snakes","major_subtype":"mudsnakes and rainbow snakes","minor_type":"","linnean_order":"serpentes","genus_authority":"gray","species_authority":"palisot de beauvois in sonnini and latreille","authority_year":"{\"1842\": \"1801\"}","deprecated_scientific":"","notes":""},"1":{"id":"234","genus":"farancia","species":"erytrogramma","subspecies":"erytrogramma","common_name":"common rainbow snake","image":"","major_type":"squamata","major_common_type":"snakes","major_subtype":"mudsnakes and rainbow snakes","minor_type":"","linnean_order":"serpentes","genus_authority":"gray","species_authority":"palisot de beauvois in sonnini and latreille","authority_year":"{\"1842\": \"1801\"}","deprecated_scientific":"","notes":""},"2":{"id":"235","genus":"farancia","species":"erytrogramma","subspecies":"seminola","common_name":"southern florida rainbow snake","image":"","major_type":"squamata","major_common_type":"snakes","major_subtype":"mudsnakes and rainbow snakes","minor_type":"","linnean_order":"serpentes","genus_authority":"gray","species_authority":"neill","authority_year":"{\"1842\": \"1964\"}","deprecated_scientific":"","notes":""}},"count":3,"method":"space_common_fallback","query":"rainbow snake","params":{"genus":"rainbow","species":"snake","common_name":"rainbow snake"},"query_params":{"bool":"or","loose":true,"order_by":"genus,species,subspecies","filter":{"had_filter":false,"filter_params":null,"filter_literal":null}},"execution_time":0.930070877075}

   3. If the fuzzy flag is set, or the above still gives no results and the loose flag is set, a search is done word-wise on common_name, major_common_type, and major_subtype (eg, for all matches that contain each word as a substring in any of the columns). The returned method is space_loose_fallback. Example

      {"status":true,"result":{"0":{"id":"480","genus":"aneides","species":"flavipunctatus","subspecies":"","common_name":"black salamander","image":"","major_type":"caudata","major_common_type":"salamanders","major_subtype":"climbing salamanders","minor_type":"","linnean_order":"caudata","genus_authority":"baird","species_authority":"strauch","authority_year":"{\"1851\": \"1870\"}","deprecated_scientific":"","notes":""},"1":{"id":"481","genus":"aneides","species":"flavipunctatus","subspecies":"flavipunctatus","common_name":"speckled black salamander","image":"","major_type":"caudata","major_common_type":"salamanders","major_subtype":"climbing salamanders","minor_type":"","linnean_order":"caudata","genus_authority":"baird","species_authority":"strauch","authority_year":"{\"1851\": \"1870\"}","deprecated_scientific":"","notes":""},"2":{"id":"482","genus":"aneides","species":"flavipunctatus","subspecies":"niger","common_name":"santa cruz black salamander","image":"","major_type":"caudata","major_common_type":"salamanders","major_subtype":"climbing salamanders","minor_type":"","linnean_order":"caudata","genus_authority":"baird","species_authority":"myers and maslin","authority_year":"{\"1851\": \"1948\"}","deprecated_scientific":"","notes":""},"3":{"id":"501","genus":"batrachoseps","species":"nigriventris","subspecies":"","common_name":"black- bellied slender salamander","image":"","major_type":"caudata","major_common_type":"salamanders","major_subtype":"slender salamanders","minor_type":"","linnean_order":"caudata","genus_authority":"bonaparte","species_authority":"cope","authority_year":"{\"1839\": \"1869\"}","deprecated_scientific":"","notes":""},"4":{"id":"519","genus":"desmognathus","species":"folkertsi","subspecies":"","common_name":"dwarf black-bellied salamander","image":"","major_type":"caudata","major_common_type":"salamanders","major_subtype":"dusky salamanders","minor_type":"","linnean_order":"caudata","genus_authority":"baird","species_authority":"camp, tilley, austin, and marshall","authority_year":"{\"1850\": \"2002\"}","deprecated_scientific":"","notes":""},"5":{"id":"529","genus":"desmognathus","species":"quadramaculatus","subspecies":"","common_name":"black-bellied salamander","image":"","major_type":"caudata","major_common_type":"salamanders","major_subtype":"dusky salamanders","minor_type":"","linnean_order":"caudata","genus_authority":"baird","species_authority":"holbrook","authority_year":"{\"1850\": \"1840\"}","deprecated_scientific":"","notes":""},"6":{"id":"531","genus":"desmognathus","species":"welteri","subspecies":"","common_name":"black mountain salamander","image":"","major_type":"caudata","major_common_type":"salamanders","major_subtype":"dusky salamanders","minor_type":"","linnean_order":"caudata","genus_authority":"baird","species_authority":"barbour","authority_year":"{\"1850\": \"1950\"}","deprecated_scientific":"","notes":""},"7":{"id":"670","genus":"pseudotriton","species":"ruber","subspecies":"schencki","common_name":"black-chinned red salamander","image":"","major_type":"caudata","major_common_type":"salamanders","major_subtype":"red and mud salamanders","minor_type":"","linnean_order":"caudata","genus_authority":"tschudi","species_authority":"brimley","authority_year":"{\"1846\": \"1912\"}","deprecated_scientific":"","notes":""}},"count":8,"method":"space_loose_fallback","query":"salamander black","params":null,"query_params":{"bool":"or","loose":true,"fuzzy":false,"order_by":"genus,species,subspecies","filter":{"had_filter":false,"filter_params":null,"filter_literal":null}},"execution_time":1.25002861023}

You can access the administration / editing interface by logging in at http://ssarherps.org/cndb/admin

If you create a user, an exisiting user with the admin flag set will need to authorize your access. You will not be able to log in or access the admin interface until this occurs.

If you log in to another device / location, all other session credentials will be invalidated. This occurs at API-level, and may require a re-login if your network location changes.

Old scientific names are to be stored in the field Deprecated Scientific Names. This field has a rigid required structure. They're written as a JSON entry with special requirements (and no braces).

Therefore, each deprecated scientific name is to be written as "Genus species":"Authority: YYYY", with an arbitrarily long list of those separated by commas. Therefore, be cognizant of the following rules:

• There should be no space between colons or commas. E.g., "foo":"bar" and "foo:bar","bar":"baz" is OK, but not "foo" :"bar","bar":"baz" or "foo":"bar", "bar":"baz".

• The "Authority: YEAR" string is optional in the space around the colon. The year has to match the rules established in Issue #37

• The validity of the taxon information is not checked.

Please use the issue tracker here to report all bugs.

If you find a security bug, please practice responsible disclosure! Email [email protected] with the issue. The administrative page uses a fork of tigerhawkvok/php-userhandler, As appropriate, report bugs or offer pull requests on the right branch.

Tasks are managed here by Grunt. The most important tasks also have a Cakefile to run it directly via cake at the command line (for the CoffeeScript). This is the reason for yuicompressor.jar in the root directory, which requires the Java JRE.

You can install Grunt from the command line by running npm install -g grunt-cli.

You can update the whole application, with dependencies, by running grunt build at the root directory.

Install this in the cndb folder below the root directory of the site. If this is to be located elsewhere, change the variable searchParams.targetApi in /coffee/search.coffee and recompile the coffeescript.

You can re-prepare the files by running grunt compile at the root directory.

1. Take your root Excel file and save it as a CSV
2. Run the file parsers/db/clean_and_parse_to_sql.py
3. The resulting file in the directory root is ready to be imported into the database

NOTE: This will delete the existing table

1. You can SSH into the database and paste the contents of the sql file generated above.
2. Otherwise, you can upload the file, then SSH into the database, and run source FILENAME.sql when visiting the database in the mysql prompt:

mysql> \r DATABASE_NAME
mysql> source FILENAME.sql

This is the most reliable way to do it.

1. Run the file parsers/db/update_sql_from_csv.py and do as above.

common_name
genus
species
subspecies
deprecated_scientific # Stored as JSON object, eg {"Genus species":"Authority:Year"}
major_type # eg, squamata
major_common_type # eg, lizard, turtle.
major_subtype # eg, snake v. non-snake, aquatic vs. tortoise. Only common, public use -- match "expectation"
minor_type # eg, lacertid, boa, pleurodire, dendrobatid; roughly a ranked "family", scientific only
linnean_order # Deprecated, included for compatibility
genus_authority #  eg, "Linnaeus"
parens_auth_genus # Boolean -- show genus authority in parenthesis. See #46
species_authority # eg, "Attenborough"
parens_auth_genus # Boolean -- show species authority in parenthesis. See #46
authority_year # eg, {2013:2014} in the format {"Genus Authority Year":"Species Authority Year"}
notes # Miscellaneous notes
image # hit calphotos api if this field is empty
image_credit # If not in public domain
image_license # If not in public domain
taxon_author # Last editor of entry
taxon_credit # Credit for `notes`
taxon_credit_date # The date for the taxon credit