diff --git a/README.md b/README.md
index 08009f91521276953fc2ea0e84607d69da657ddb..55760f053306c1f189ab25b4536a0dac08847784 100644
--- a/README.md
+++ b/README.md
@@ -125,3 +125,129 @@ These 2 are highlighted as an example of a primary and ancillary dataset that be
```
adex_data_scraper --argfile examples\vo\apertif_dr1_continuum_images_localhost.args
adex_data_scraper --argfile examples\postgres\ancillary_apertif_inspectionplots_localhost.args
+```
+
+## How To add new VO collections to ADEX
+This is an example of how to add the ALMA ivoa.obscore collecion to ADEX.
+
+
+
+Most of the work is in the `adex-data-scraper` (the current repo).
+With one small configuration change in the `adex-backend-django` configuration files for `adex-labs` and `adex-next` to enable the new collection.
+
+* use a VO application like Topcat to find or query datasets. This example uses Topcat:
+ * look for the Table Access Protocol (TAP service). In Topcat: VO => TAP query => keyword 'ALMA'
+ * select a table: alma.ivoa.obscore
+ * SDQL Query: SELECT TOP 1000 * FROM ivoa.obscore
+ * double click 'Table List'
+
+This shows the fields that you need to translate with a 'connector' to ADEX.
+
+
+
+#### argument file
+Create your argument file (also see 'examples' chapter)
+
+```
+--datasource=vo
+--connector=ALMA.Obscore
+--data_host=http://jvo.nao.ac.jp/skynode/do/tap/alma/ivoa.obscore
+--batch_size=1000
+--adex_backend_host=https://sdc.astron.nl/adex_backend/
+--adex_resource=primary_dp/create
+--adex_token=6b85509349313c7bdb16bd706d43ee5eb1cfb5da
+--clear_collection
+--collection=alma_obscore
+```
+
+Most arguments are default or obvious, but some need a bit more explanation.
+
+`--connector=ALMA.Obscore`
+
+This refers to a file `ALMA.py` and classname `Obscore` in that file, in the `vo.connectors` directory.
+You will need to create that file, this is the 'connector'. (see next chapter)
+
+`--data_host=http://jvo.nao.ac.jp/skynode/do/tap/alma/ivoa.obscore`
+
+This is a combination of the 'service URL' and the table name (indicated in red in the topcat screenshot)
+
+`--collection=alma_obscore`
+
+You can freely choose this name. This is the name that appears in the Collection dropdown menu.
+You need to use the same name in the adex backend configuration (see 'adex-backend-django configuration')
+
+
+#### write the connector (ALMA.Obscore)
+This translates the results from the ADQL query to ADEX format.
+Not every VO services uses the same field names for similar information (like ra,dec),
+so you need to look at the VO table result or Schema in TOPCAT which names this service uses.
+Also, not all the ADEX fields will be available in every service, and they an be left out.
+
+The 'translate()' function is an overridden function, which means that its name, arguments and
+returned results are given and should not be changed.
+Don't change the keys in the dict, only the identifiers in the 'row'
+
+For example, ADEX expects the Right Ascension named as '**ra**',
+which should be in decimal degrees as returned as a float in the payload json.
+
+The ALMA service returns Right Ascension named as 's_ra' and returns it as a string.
+So you need to convert it so that it fits ADEX: float(row['s_ra'])
+
+```python
+class Obscore():
+
+ def translate(self, row, args):
+ """
+ parse the specific row that comes from the VO adql query,
+ and translate it into the standard json payload for posting to the ADEX backend REST API
+
+ :param row: the results from the ADQL query to a VO service
+ :param args: the commandline arguments, but only args.collection is currently used
+ :return: ADEX record as json structure
+ """
+ payload = dict(
+ pid=row['data_id'],
+ name=row['target_name'],
+ dp_type=row['dataproduct_type'],
+ format="fits",
+ locality="online",
+ access_url=row['access_url'],
+ ra=float(row['s_ra']),
+ dec=float(row['s_dec']),
+ equinox="2000.0",
+
+ release_date=row['obs_release_date'],
+ data_provider="ALMA",
+
+ sky_footprint=row['s_region'],
+
+ dataset_id=str(row['data_id']),
+ activity=None,
+ collection = args.collection,
+ )
+
+ return payload
+```
+
+#### adex-backend-django configuration
+The frontend applications (adex-labs and adex-gui) get their configuration from adex-backend.
+This is the directory where the frontend configuration files are kept.
+https://git.astron.nl/astron-sdc/adex-backend-django/-/tree/main/adex_backend/adex_backend/configuration?ref_type=heads
+
+Look for the "collections" tag in the configuration, and add new alma_obscore collection to it
+
+ "collections": [
+ { "name" : "linc_skymap", "dp_types": ['qa-skymap']},
+ { "name" : "linc_visibilities", "dp_types": ['die-calibrated-visibilities'], "distinct_field" : "dataset_id"},
+ { "name" : "apertif-dr1", "dp_types": ['science-skymap']},
+ { "name" : "lotts-dr2", "dp_types": ['skymap']},
+ { "name" : "lofar-skyimage", "dp_types": ['skyimage']},
+ { "name" : "alma_obscore", "dp_types": ['IMAGE','CUBE']}
+ ],
+
+The `alma_obscore` is the name you chose for your collection, as defined in the argument file.
+
+`IMAGE`and `CUBE` are values of the `dataproduct_type` field in the ALMA ivoa.obscore collection.
+These can be mapped onto the ADEX dp_type field (see previous chapter).
+By adding them to the configuration, the frontend(s) knows to give these values as filter options once the `alma_obscore` collection is selected.
+
diff --git a/docs/adex-labs_alma.jpg b/docs/adex-labs_alma.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..98bcf06e9cbe119d4a81db3b83ea4eb3566374a3
Binary files /dev/null and b/docs/adex-labs_alma.jpg differ
diff --git a/docs/topcat_alma.jpg b/docs/topcat_alma.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..9840a1a58fd70e6b0b1d4442c1cefed21112f021
Binary files /dev/null and b/docs/topcat_alma.jpg differ
diff --git a/examples/vo/alma/alma_obscore_localhost.args b/examples/vo/alma/alma_obscore_localhost.args
new file mode 100644
index 0000000000000000000000000000000000000000..dcca5f16704de9e3245cdde5258856411b19c950
--- /dev/null
+++ b/examples/vo/alma/alma_obscore_localhost.args
@@ -0,0 +1,9 @@
+--datasource=vo
+--connector=ALMA.Obscore
+--data_host=http://jvo.nao.ac.jp/skynode/do/tap/alma/ivoa.obscore
+--batch_size=1000
+--adex_backend_host=http://localhost:8000/adex_backend/
+--adex_resource=primary_dp/create
+--adex_token=9519e433ba37487f1a18121dfb1957d992fbb790
+--clear_collection
+--collection=alma_obscore
diff --git a/examples/vo/alma/alma_obscore_sdc.args b/examples/vo/alma/alma_obscore_sdc.args
new file mode 100644
index 0000000000000000000000000000000000000000..7e6b764bfb8642dda3aed0631b2f9cf86cb97cad
--- /dev/null
+++ b/examples/vo/alma/alma_obscore_sdc.args
@@ -0,0 +1,9 @@
+--datasource=vo
+--connector=ALMA.Obscore
+--data_host=http://jvo.nao.ac.jp/skynode/do/tap/alma/ivoa.obscore
+--batch_size=1000
+--adex_backend_host=https://sdc.astron.nl/adex_backend/
+--adex_resource=primary_dp/create
+--adex_token=6b85509349313c7bdb16bd706d43ee5eb1cfb5da
+--clear_collection
+--collection=alma_obscore
diff --git a/scraper/vo/connectors/ALMA.py b/scraper/vo/connectors/ALMA.py
new file mode 100644
index 0000000000000000000000000000000000000000..3fda8aa3d868e788c2294a43149c35225f65eb0f
--- /dev/null
+++ b/scraper/vo/connectors/ALMA.py
@@ -0,0 +1,35 @@
+
+class Obscore():
+
+ def translate(self, row, args):
+ """
+ parse the specific row that comes from the VO adql query,
+ and translate it into the standard json payload for posting to the ADEX backend REST API
+
+ :param row: the results from the ADQL query to a VO service
+ :param args: the commandline arguments, but only args.collection is currently used
+ :return: ADEX record as json structure
+ """
+ payload = dict(
+ pid=row['data_id'],
+ name=row['target_name'],
+ dp_type=row['dataproduct_type'],
+ format="fits",
+ locality="online",
+ access_url=row['access_url'],
+ ra=float(row['s_ra']),
+ dec=float(row['s_dec']),
+ equinox="2000.0",
+
+ release_date=row['obs_release_date'],
+ data_provider="ALMA",
+
+ sky_footprint=row['s_region'],
+
+ dataset_id=str(row['data_id']),
+ activity=None,
+ collection = args.collection,
+ )
+
+ return payload
+
diff --git a/scraper/vo/connectors/Apertif_DR1.py b/scraper/vo/connectors/Apertif_DR1.py
index 6687c538af2f229ffe22a152599321181d980e6d..d363ed09848de2bafcfaacdfb95bbbfd58f57a76 100644
--- a/scraper/vo/connectors/Apertif_DR1.py
+++ b/scraper/vo/connectors/Apertif_DR1.py
@@ -9,7 +9,7 @@ class ContinuumImagesConnector():
:param row: the results from the ADQL query to a VO service
:param args: the commandline arguments, but only args.collection is currently used
- :return: user, password, host, database, db_port
+ :return: ADEX record as json structure
"""
freq_min = float(row['freqmin'])
freq_max = float(row['freqmax'])
diff --git a/scraper/vo/connectors/LotssDR2.py b/scraper/vo/connectors/LotssDR2.py
index cffb90eb3ea4ab0159f083bb9422a1557edc93e2..16fbb6f5bd224fde6a906f0789cff19924b4a666 100644
--- a/scraper/vo/connectors/LotssDR2.py
+++ b/scraper/vo/connectors/LotssDR2.py
@@ -8,7 +8,7 @@ class LotssDR2Mosaics():
:param row: the results from the ADQL query to a VO service
:param args: the commandline arguments, but only args.collection is currently used
- :return: user, password, host, database, db_port
+ :return: ADEX record as json structure
"""
payload = dict(
pid=row['data_pid'],
diff --git a/scraper/vo/vo_scraper.py b/scraper/vo/vo_scraper.py
index cefa2ef7260f5a348129eb955b5d7a030f14ef2a..e311bc4f4d413c3f10479034185d45962edf0a16 100644
--- a/scraper/vo/vo_scraper.py
+++ b/scraper/vo/vo_scraper.py
@@ -6,7 +6,7 @@ import logging
logger = logging.getLogger('vo_scraper')
from scraper.adex_io import ADEX
-from scraper.vo.connectors import Apertif_DR1, LotssDR2, Linc
+from scraper.vo.connectors import Apertif_DR1, LotssDR2, Linc, ALMA
def run(args):
"""
@@ -40,6 +40,10 @@ def run(args):
connector_class = getattr(Linc, connector_name)
connector = connector_class()
+ if connector_module.upper() == 'ALMA':
+ connector_class = getattr(ALMA, connector_name)
+ connector = connector_class()
+
# construct the ADQL query
#select_fields = "centeralpha,centerdelta,imagetitle,accref"
select_fields = "*"
@@ -93,7 +97,10 @@ def run(args):
t3 = datetime.datetime.now()
print(f"{total_count} records in total in {t3 - t0}")
+ except UnboundLocalError as error:
+ print(f"ERROR: {error}. Did you import and hook up the {connector_module} connector in vo_scraper.py?")
+ return
except Exception as error:
- print(f"ERROR: {error}")
+ print(f"ERROR: {error}.")
return