diff --git a/pyglider/ncprocess.py b/pyglider/ncprocess.py
index b0fdb26..4acf8bd 100644
--- a/pyglider/ncprocess.py
+++ b/pyglider/ncprocess.py
@@ -14,7 +14,7 @@
 _log = logging.getLogger(__name__)
 
 
-def extract_timeseries_profiles(inname, outdir, deploymentyaml):
+def extract_timeseries_profiles(inname, outdir, deploymentyaml, force=False):
     """
     Extract and save each profile from a timeseries netCDF.
 
@@ -29,6 +29,9 @@ def extract_timeseries_profiles(inname, outdir, deploymentyaml):
     deploymentyaml : str or Path
         location of deployment yaml file for the netCDF file.  This should
         be the same yaml file that was used to make the timeseries file.
+
+    force : bool, default False
+        Force an overwite even if profile netcdf already exists
     """
     try:
         os.mkdir(outdir)
@@ -48,7 +51,7 @@ def extract_timeseries_profiles(inname, outdir, deploymentyaml):
             dss = ds.isel(time=ind)
             outname = outdir + '/' + utils.get_file_id(dss) + '.nc'
             _log.info('Checking %s', outname)
-            if not os.path.exists(outname):
+            if force or (not os.path.exists(outname)):
                 # this is the id for the whole file, not just this profile..
                 dss['trajectory'] = utils.get_file_id(ds).encode()
                 trajlen = len(utils.get_file_id(ds).encode())
@@ -73,8 +76,13 @@ def extract_timeseries_profiles(inname, outdir, deploymentyaml):
                     dss['v'] = profile_meta['v'].get('_FillValue', np.NaN)
                     dss['v'].attrs = profile_meta['v']
 
-                dss['profile_id'] = np.array(p*1.0)
+                dss['profile_id'] = np.int32(p)
                 dss['profile_id'].attrs = profile_meta['profile_id']
+                if '_FillValue' not in dss['profile_id'].attrs:
+                    dss['profile_id'].attrs['_FillValue'] = -1
+                dss['profile_id'].attrs['valid_min'] = np.int32(dss['profile_id'].attrs['valid_min'])
+                dss['profile_id'].attrs['valid_max'] = np.int32(dss['profile_id'].attrs['valid_max'])
+
                 dss['profile_time'] = dss.time.mean()
                 dss['profile_time'].attrs = profile_meta['profile_time']
                 # remove units so they can be encoded later:
@@ -90,9 +98,9 @@ def extract_timeseries_profiles(inname, outdir, deploymentyaml):
 
                 dss['lat'] = dss['latitude']
                 dss['lon'] = dss['longitude']
-                dss['platform'] = np.NaN
+                dss['platform'] = np.int32(1)
                 comment = (meta['glider_model'] + ' operated by ' +
-                        meta['institution'])
+                           meta['institution'])
                 dss['platform'].attrs['comment'] = comment
                 dss['platform'].attrs['id'] = (
                     meta['glider_name'] + meta['glider_serial'])
@@ -101,6 +109,9 @@ def extract_timeseries_profiles(inname, outdir, deploymentyaml):
                     meta['glider_model'] + dss['platform'].attrs['id'])
                 dss['platform'].attrs['type'] = 'platform'
                 dss['platform'].attrs['wmo_id'] = meta['wmo_id']
+                if '_FillValue' not in dss['platform'].attrs:
+                    dss['platform'].attrs['_FillValue'] = -1
+
 
                 dss['lat_uv'] = np.NaN
                 dss['lat_uv'].attrs = profile_meta['lat_uv']
@@ -109,16 +120,26 @@ def extract_timeseries_profiles(inname, outdir, deploymentyaml):
                 dss['time_uv'] = np.NaN
                 dss['time_uv'].attrs = profile_meta['time_uv']
 
-                dss['instrument_ctd'] = np.NaN
+                dss['instrument_ctd'] = np.int32(1.0)
                 dss['instrument_ctd'].attrs = profile_meta['instrument_ctd']
+                if '_FillValue' not in dss['instrument_ctd'].attrs:
+                    dss['instrument_ctd'].attrs['_FillValue'] = -1
 
                 dss.attrs['date_modified'] = str(np.datetime64('now')) + 'Z'
 
-                # ancillary variables::
+                # ancillary variables: link and create with values of 2.  If
+                # we dont' want them all 2, then create these variables in the
+                # time series
                 to_fill = ['temperature', 'pressure', 'conductivity',
                         'salinity', 'density', 'lon', 'lat', 'depth']
                 for name in to_fill:
-                    dss[name].attrs['ancillary_variables'] = name + '_qc'
+                    qcname = name + '_qc'
+                    dss[name].attrs['ancillary_variables'] = qcname
+                    if qcname not in dss.keys():
+
+                        dss[qcname] = ('time', 2 * np.ones(len(dss[name]), np.int8))
+                        dss[qcname].attrs = utils.fill_required_qcattrs({}, name)
+                        # 2 is "not eval"
                 # outname = outdir + '/' + utils.get_file_id(dss) + '.nc'
                 _log.info('Writing %s', outname)
                 timeunits = 'nanoseconds since 1970-01-01T00:00:00Z'
@@ -134,7 +155,9 @@ def extract_timeseries_profiles(inname, outdir, deploymentyaml):
                                                           'profile_time':
                                                          {'units': timeunits,
                                                          '_FillValue': -99999.0,
-                                                         'dtype': 'float64'}}
+                                                         'dtype': 'float64'},
+                }
+
                                                          )
 
                 # add traj_strlen using bare ntcdf to make IOOS happy
diff --git a/pyglider/slocum.py b/pyglider/slocum.py
index a1386b6..3f5e810 100644
--- a/pyglider/slocum.py
+++ b/pyglider/slocum.py
@@ -716,7 +716,6 @@ def raw_to_timeseries(indir, outdir, deploymentyaml, *,
         if atts != 'coordinates':
             attr[atts] = ncvar[name][atts]
     ds[name] = (('time'), ebd[name].values, attr)
-
     for name in thenames:
         _log.info('working on %s', name)
         if 'method' in ncvar[name].keys():
@@ -868,8 +867,8 @@ def binary_to_timeseries(indir, cachedir, outdir, deploymentyaml, *,
     # get the time:
     time = data.pop(0)
     ds['time'] = (('time'), time, attr)
-    ds['latitude'] = 0 * ds.time
-    ds['longitude'] = 0 * ds.time
+    ds['latitude'] = (('time'), np.zeros(len(time)))
+    ds['longitude'] = (('time'), np.zeros(len(time)))
     # get the time_base data:
     basedata = data.pop(0)
     # slot the time_base variable into the right place in the
@@ -908,7 +907,7 @@ def binary_to_timeseries(indir, cachedir, outdir, deploymentyaml, *,
             ValueError(f'{sensorname} not in science or eng parameter names')
 
         # make the attributes:
-        ncvar[name].pop('coordinates', None)
+        ncvar[name]['coordinates'] = 'time'
         attrs = ncvar[name]
         attrs = utils.fill_required_attrs(attrs)
         ds[name] = (('time'), val, attrs)
@@ -921,9 +920,6 @@ def binary_to_timeseries(indir, cachedir, outdir, deploymentyaml, *,
     ds = utils.get_distance_over_ground(ds)
 
     ds = utils.get_derived_eos_raw(ds)
-    ds = ds.assign_coords(longitude=ds.longitude)
-    ds = ds.assign_coords(latitude=ds.latitude)
-    ds = ds.assign_coords(depth=ds.depth)
 
     # screen out-of-range times; these won't convert:
     ds['time'] = ds.time.where((ds.time>0) & (ds.time<6.4e9), np.NaN)
@@ -953,8 +949,8 @@ def binary_to_timeseries(indir, cachedir, outdir, deploymentyaml, *,
     _log.info('writing %s', outname)
     ds.to_netcdf(outname, 'w',
                  encoding={'time': {'units': 'seconds since 1970-01-01T00:00:00Z',
-                                    '_FillValue': -999999,
-                                    'dtype': 'int64'}})
+                                    '_FillValue': np.NaN,
+                                    'dtype': 'float64'}})
 
     return outname
 
diff --git a/pyglider/utils.py b/pyglider/utils.py
index 076b944..aa64efe 100644
--- a/pyglider/utils.py
+++ b/pyglider/utils.py
@@ -398,6 +398,22 @@ def fill_required_attrs(attrs):
     return attrs
 
 
+def fill_required_qcattrs(attrs, varname):
+    required = {
+        "units": "1",
+        "flag_values": np.array([1, 2, 3, 4, 9], dtype=np.int8),
+        "valid_min": np.int8(1),
+        "valid_max": np.int8(9),
+        "flag_meanings": "PASS NOT_EVALUATED SUSPECT FAIL MISSING",
+        "standard_name": "quality_flag",
+        "long_name": "Initial flag for {varname}"
+    }
+    for k in required.keys():
+        if not (k in attrs.keys()):
+            attrs[k] = required[k]
+    return attrs
+
+
 def get_file_id(ds):
     """
     Make a file id for a Dataset
@@ -458,9 +474,10 @@ def fill_metadata(ds, metadata, sensor_data):
     ds.attrs['history'] = 'CPROOF glider toolbox version: pre-tag'
     for k, v in metadata.items():
         ds.attrs[k] = v
-    ds.attrs['featureType'] = 'timeseries'
+    ds.attrs['featureType'] = 'trajectory'
     ds.attrs['cdm_data_type'] = 'Trajectory'
-    ds.attrs['Conventions'] = 'CF-1.6'
+    ds.attrs['Conventions'] = 'CF-1.8'
+    ds.attrs['standard_name_vocabulary'] = 'CF STandard Name Table v72'
     ds.attrs['date_created'] = str(np.datetime64('now')) + 'Z'
     ds.attrs['date_issued'] = str(np.datetime64('now')) + 'Z'
     ds.attrs['date_modified'] = " "
diff --git a/tests/environment.yml b/tests/environment.yml
index 5edbc77..c80a469 100644
--- a/tests/environment.yml
+++ b/tests/environment.yml
@@ -15,6 +15,8 @@ dependencies:
   - pytest-cov
   - pooch
   - matplotlib
+  - compliance-checker
+  - cc-plugin-glider
   - pip:
     - dbdreader
     - polars
diff --git a/tests/example-data/example-slocum/deploymentRealtime.yml b/tests/example-data/example-slocum/deploymentRealtime.yml
index f30ece7..c57afc9 100644
--- a/tests/example-data/example-slocum/deploymentRealtime.yml
+++ b/tests/example-data/example-slocum/deploymentRealtime.yml
@@ -32,7 +32,7 @@ metadata:
   license: "This data may be redistributed and used without restriction or
             warranty"
   metadata_link: "https://cproof.uvic.ca"
-  Metadata_Conventions: CF-1.6, Unidata Dataset Discovery v1.0
+  Metadata_Conventions: CF-1.8, Unidata Dataset Discovery v1.0
   naming_authority: "ca.uvic.cproof"
   platform_type:    "Slocum Glider"
   processing_level: "Data provided as is with no expressed or implied
@@ -44,9 +44,9 @@ metadata:
   publisher_url:   http://cproof.uvic.ca
   references:     cproof toolbox URL
   # https://www.nodc.noaa.gov/General/NODC-Archive/seanamelist.txt
-  sea_name:   Coastal Waters of British Columbia
+  sea_name:   Coastal Waters of Southeast Alaska and British Columbia
   source:     Observational data from a profiling glider.
-  standard_name_vocabulary: CF STandard Name Table v49
+  standard_name_vocabulary: CF STandard Name Table v72
   summary: Manufacturer test in Saanich Inlet.
   transmission_system: IRRIDIUM
   wmo_id: "999999"
@@ -88,7 +88,6 @@ netcdf_variables:
     units:         seconds since 1970-01-01T00:00:00Z
     axis:          T
     observation_type: "measured"
-    coordinates:   time depth latitude longitude
 
   latitude:
     source:  m_lat
@@ -96,7 +95,6 @@ netcdf_variables:
     standard_name: latitude
     units:        degrees_north
     axis:         Y
-    coordinates:   time depth latitude longitude
     comment:     "Estimated between surface fixes"
     observation_type: measured
     platform:     platform
@@ -111,7 +109,6 @@ netcdf_variables:
     standard_name: longitude
     units:        degrees_east
     axis:         X
-    coordinates:  time depth latitude longitude
     comment:     "Estimated between surface fixes"
     observation_type: measured
     platform:     platform
@@ -125,21 +122,18 @@ netcdf_variables:
     long_name:    glider heading angle
     standard_name: platform_orientation
     units:        rad
-    coordinates:  time depth latitude longitude
 
   pitch:
     source:  m_pitch
     long_name:    glider pitch angle
     standard_name: platform_pitch_angle
     units:        rad
-    coordinates:  time depth latitude longitude
 
   roll:
     source:  m_roll
     long_name:    glider roll angle
     standard_name: platform_roll_angle
     units:        rad
-    coordinates:  time depth latitude longitude
 
   # profile info:
   waypoint_latitude:
@@ -147,14 +141,12 @@ netcdf_variables:
     long_name:    waypoint latitude
     standard_name: latitude
     units:        degree_north
-    coordinates:  time depth latitude longitude
 
   waypoint_longitude:
     source:  c_wpt_lon
     long_name:    waypoint longitude
     standard_name: longitude
     units:        degree_east
-    coordinates:  time depth latitude longitude
 
   # data parameters
   conductivity:
@@ -162,7 +154,6 @@ netcdf_variables:
     long_name:    water conductivity
     standard_name: sea_water_electrical_conductivity
     units:        S m-1
-    coordinates:  time depth latitude longitude
     instrument:    instrument_ctd
     valid_min:    0.
     valid_max:    10.
@@ -176,7 +167,6 @@ netcdf_variables:
     long_name:    water temperature
     standard_name: sea_water_temperature
     units:        Celsius
-    coordinates:  time depth latitude longitude
     instrument:   instrument_ctd
     valid_min:    -5.0
     valid_max:    50.0
@@ -190,7 +180,6 @@ netcdf_variables:
     long_name:    water pressure
     standard_name:  sea_water_pressure
     units:        dbar
-    coordinates:  time depth latitude longitude
     conversion:   bar2dbar
     valid_min:    0.0
     valid_max:    2000.0
@@ -210,19 +199,16 @@ netcdf_variables:
     long_name:    chlorophyll
     standard_name: concentration_of_chlorophyll_in_sea_water
     units:        mg m-3
-    coordinates:  time depth latitude longitude
 
   cdom:
     source:  sci_flbbcd_cdom_units
     long_name:    CDOM
     units:        ppb
-    coordinates:  time depth latitude longitude
 
   backscatter_700:
     source:  sci_flbbcd_bb_units
     long_name:    700 nm wavelength backscatter
     units:         "1"
-    coordinates:  time depth latitude longitude
 
 # Oxygen
   oxygen_concentration:
@@ -230,7 +216,6 @@ netcdf_variables:
     long_name:    oxygen concentration
     standard_name: mole_concentration_of_dissolved_molecular_oxygen_in_sea_water
     units:        umol l-1
-    coordinates:   time depth latitude longitude
 
 # derived water speed:
   # water_velocity_eastward:
@@ -252,8 +237,8 @@ profile_variables:
   profile_id:
     comment: Sequential profile number within the trajectory.  This value is unique in each file that is part of a single trajectory/deployment.
     long_name: 'Profile ID'
-    valid_max: 2147483647.0
-    valid_min: 1.0
+    valid_max: 2147483646
+    valid_min: 1
 
   profile_time:
     comment:           Timestamp corresponding to the mid-point of the profile
diff --git a/tests/results/example-seaexplorer-raw/L0-timeseries/dfo-bb046-20200908.nc b/tests/expected/example-seaexplorer-raw/L0-timeseries/dfo-bb046-20200908.nc
similarity index 76%
rename from tests/results/example-seaexplorer-raw/L0-timeseries/dfo-bb046-20200908.nc
rename to tests/expected/example-seaexplorer-raw/L0-timeseries/dfo-bb046-20200908.nc
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similarity index 72%
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similarity index 93%
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diff --git a/tests/results/example-slocum/L0-timeseries/dfo-rosie713-20190615.nc b/tests/expected/example-slocum/L0-timeseries/dfo-rosie713-20190615.nc
similarity index 73%
rename from tests/results/example-slocum/L0-timeseries/dfo-rosie713-20190615.nc
rename to tests/expected/example-slocum/L0-timeseries/dfo-rosie713-20190615.nc
index 4a520d1..a452d26 100644
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diff --git a/tests/test_pyglider.py b/tests/test_pyglider.py
index e5663ca..0c003bd 100644
--- a/tests/test_pyglider.py
+++ b/tests/test_pyglider.py
@@ -4,6 +4,7 @@
 import numpy as np
 import yaml
 
+import pyglider.ncprocess as ncprocess
 import pyglider.seaexplorer as seaexplorer
 import pyglider.slocum as slocum
 
@@ -24,7 +25,7 @@
 # Open test data file
 test_data = xr.open_dataset(
     library_dir /
-    'tests/results/example-seaexplorer/L0-timeseries/dfo-eva035-20190718.nc')
+    'tests/expected/example-seaexplorer/L0-timeseries/dfo-eva035-20190718.nc')
 variables = list(output.variables)
 
 
@@ -84,7 +85,6 @@ def test_example_seaexplorer_interp_nrt(var):
 
 
 # Test raw (full resolution) seaexplorer data.
-
 rawdir = str(example_dir / 'example-seaexplorer-raw/delayed_raw/') + '/'
 rawncdir = str(example_dir / 'example-seaexplorer-raw/delayed_rawnc/') + '/'
 deploymentyaml_raw = str(example_dir / 'example-seaexplorer-raw/deployment.yml')
@@ -97,7 +97,7 @@ def test_example_seaexplorer_interp_nrt(var):
 # Open test data file
 test_data_raw = xr.open_dataset(
     library_dir /
-    'tests/results/example-seaexplorer-raw/L0-timeseries/dfo-bb046-20200908.nc')
+    'tests/expected/example-seaexplorer-raw/L0-timeseries/dfo-bb046-20200908.nc')
 
 @pytest.mark.parametrize("var", variables)
 def test_example_seaexplorer_raw(var):
@@ -148,135 +148,3 @@ def test_example_seaexplorer_interp_raw(var):
         assert np.allclose(
             np.array(dt0, dtype='float64'),
             np.array(dt1, dtype='float64'))
-
-
-# Create an L0 timeseries from slocum data and test that the resulting netcdf is
-# identical to the test data
-cacdir = str(example_dir / 'example-slocum/cac/') + '/'
-sensorlist = str(example_dir / 'example-slocum/dfo-rosie713_sensors.txt')
-binarydir = str(example_dir / 'example-slocum/realtime_raw/') + '/'
-rawdir_slocum = str(example_dir / 'example-slocum/realtime_rawnc/') + '/'
-deploymentyaml_slocum = str(example_dir / 'example-slocum/deploymentRealtime.yml')
-l1tsdir = str(example_dir / 'example-slocum/L0-timeseries-test/') + '/'
-scisuffix = 'tbd'
-glidersuffix = 'sbd'
-do_direct = True
-
-if do_direct:
-    # turn *.sbd and *.tbd into timeseries netcdf files
-    outname_slocum = slocum.binary_to_timeseries(
-        binarydir, cacdir, l1tsdir, deploymentyaml_slocum, search='*.[s|t]bd',
-        profile_filt_time=20, profile_min_time=20)
-else:
-    slocum.binary_to_rawnc(
-        binarydir, rawdir_slocum, cacdir, sensorlist, deploymentyaml_slocum,
-        incremental=False, scisuffix=scisuffix, glidersuffix=glidersuffix)
-
-    slocum.merge_rawnc(rawdir_slocum, rawdir_slocum, deploymentyaml_slocum,
-                       scisuffix=scisuffix, glidersuffix=glidersuffix)
-    outname_slocum = slocum.raw_to_timeseries(
-        rawdir_slocum, l1tsdir, deploymentyaml_slocum,
-        profile_filt_time=100, profile_min_time=300)
-
-output_slocum = xr.open_dataset(outname_slocum)
-# Open test data file
-test_data_slocum = xr.open_dataset(
-    library_dir /
-    'tests/results/example-slocum/L0-timeseries/dfo-rosie713-20190615.nc')
-variables_slocum = list(output_slocum.variables)
-
-
-def test_variables_slocum():
-    test_variables = list(test_data_slocum.variables)
-    test_variables.sort()
-    variables_slocum.sort()
-    assert variables_slocum == test_variables
-
-
-@pytest.mark.parametrize("var", variables_slocum)
-def test_example_slocum(var):
-    # Test that variables and coordinates match
-    assert output_slocum[var].attrs == test_data_slocum[var].attrs
-    if var not in ['time']:
-        np.testing.assert_allclose(output_slocum[var].values,
-                                   test_data_slocum[var].values, rtol=1e-6)
-    else:
-        dt0 = output_slocum[var].values - np.datetime64('2000-01-01')
-        dt1 = test_data_slocum[var].values - np.datetime64('2000-01-01')
-        assert np.allclose(
-            np.array(dt0, dtype='float64'),
-            np.array(dt1, dtype='float64'))
-
-
-def test_example_slocum_metadata():
-    # Test that attributes match. Have to remove creation and issue
-    # dates first
-    output_slocum.attrs.pop('date_created')
-    output_slocum.attrs.pop('date_issued')
-    test_data_slocum.attrs.pop('date_created')
-    test_data_slocum.attrs.pop('date_issued')
-    assert output_slocum.attrs == test_data_slocum.attrs
-
-
-# Create an L0 timeseries from slocum data and test that the resulting netcdf is
-# identical to the test data
-cacdir = str(example_dir / 'example-slocum-littleendian/cac/') + '/'
-sensorlist = str(
-    example_dir / 'example-slocum-littleendian/dfo-maria997_sensors.txt')
-binarydir = str(
-    example_dir / 'example-slocum-littleendian/realtime_raw/') + '/'
-rawdir_slocum = str(
-    example_dir / 'example-slocum-littleendian/realtime_rawnc/') + '/'
-deploymentyaml_slocum = str(
-    example_dir / 'example-slocum-littleendian/deployment.yml')
-l1tsdir = str(
-    example_dir / 'example-slocum-littleendian/L0-timeseries-test/') + '/'
-scisuffix = 'tbd'
-glidersuffix = 'sbd'
-
-slocum.binary_to_rawnc(
-    binarydir, rawdir_slocum, cacdir, sensorlist, deploymentyaml_slocum,
-    incremental=True, scisuffix=scisuffix, glidersuffix=glidersuffix)
-slocum.merge_rawnc(rawdir_slocum, rawdir_slocum, deploymentyaml_slocum,
-                   scisuffix=scisuffix, glidersuffix=glidersuffix)
-outname_slocum_le = slocum.raw_to_timeseries(
-    rawdir_slocum, l1tsdir, deploymentyaml_slocum,
-    profile_filt_time=400, profile_min_time=100)
-output_slocum_le = xr.open_dataset(outname_slocum_le)
-# Open test data file
-test_data_slocum_le = xr.open_dataset(
-    library_dir /
-    ('tests/results/example-slocum-littleendian/' +
-     'L0-timeseries/dfo-maria997-20220614.nc'))
-variables_slocum_le = list(output_slocum.variables)
-
-
-def test_variables_slocum_littleendian():
-    test_variables = list(test_data_slocum_le.variables)
-    test_variables.sort()
-    variables_slocum.sort()
-    assert variables_slocum == test_variables
-
-
-@pytest.mark.parametrize("var", variables_slocum)
-def test_example_slocum_littleendian(var):
-    # Test that variables and coordinates match
-    assert output_slocum_le[var].attrs == test_data_slocum_le[var].attrs
-    if var not in ['time']:
-        np.testing.assert_allclose(output_slocum_le[var].values,
-                                   test_data_slocum_le[var].values, rtol=1e-6)
-    else:
-        dt0 = output_slocum_le[var].values - np.datetime64('2000-01-01')
-        dt1 = test_data_slocum_le[var].values - np.datetime64('2000-01-01')
-        assert np.allclose(
-            np.array(dt0, dtype='float64'),
-            np.array(dt1, dtype='float64'))
-
-
-def test_example_slocum_littleendian_metadata():
-    # Test that attributes match. Have to remove creation and issue dates first
-    output_slocum_le.attrs.pop('date_created')
-    output_slocum_le.attrs.pop('date_issued')
-    test_data_slocum_le.attrs.pop('date_created')
-    test_data_slocum_le.attrs.pop('date_issued')
-    assert output_slocum_le.attrs == test_data_slocum_le.attrs
diff --git a/tests/test_slocum.py b/tests/test_slocum.py
new file mode 100644
index 0000000..bc6beaa
--- /dev/null
+++ b/tests/test_slocum.py
@@ -0,0 +1,162 @@
+import xarray as xr
+
+from compliance_checker.runner import ComplianceChecker, CheckSuite
+import json
+from pathlib import Path
+import pytest
+import numpy as np
+import yaml
+
+import pyglider.ncprocess as ncprocess
+import pyglider.seaexplorer as seaexplorer
+import pyglider.slocum as slocum
+
+
+
+library_dir = Path(__file__).parent.parent.absolute()
+example_dir = library_dir / 'tests/example-data/'
+
+# Create an L0 timeseries from slocum data and test that the resulting netcdf is
+# identical to the test data
+cacdir = example_dir / 'example-slocum/cac/'
+sensorlist = str(example_dir / 'example-slocum/dfo-rosie713_sensors.txt')
+binarydir = str(example_dir / 'example-slocum/realtime_raw/') + '/'
+rawdir_slocum = str(example_dir / 'example-slocum/realtime_rawnc/') + '/'
+deploymentyaml_slocum = str(example_dir / 'example-slocum/deploymentRealtime.yml')
+tsdir = str(example_dir / 'example-slocum/L0-timeseries/') + '/'
+scisuffix = 'tbd'
+glidersuffix = 'sbd'
+profiledir = str(example_dir /  'example-slocum/L0-profiles/')
+do_direct = True
+
+# This needs to get run every time the tests are run, so do at top level:
+
+# turn *.sbd and *.tbd into timeseries netcdf files
+outname_slocum = slocum.binary_to_timeseries(binarydir, cacdir, tsdir, deploymentyaml_slocum,
+                                             search='*.[s|t]bd', profile_filt_time=20,
+                                             profile_min_time=20)
+# make profiles...
+ncprocess.extract_timeseries_profiles(outname_slocum, profiledir, deploymentyaml_slocum,
+                                      force=True)
+
+output_slocum = xr.open_dataset(outname_slocum)
+# Open test data file
+test_data_slocum = xr.open_dataset(
+    library_dir /
+    'tests/expected/example-slocum/L0-timeseries/dfo-rosie713-20190615.nc')
+variables_slocum = list(output_slocum.variables)
+
+
+def test_variables_slocum():
+    test_variables = list(test_data_slocum.variables)
+    test_variables.sort()
+    variables_slocum.sort()
+    assert variables_slocum == test_variables
+
+
+@pytest.mark.parametrize("var", variables_slocum)
+def test_example_slocum(var):
+    # Test that variables and coordinates match
+    assert output_slocum[var].attrs == test_data_slocum[var].attrs
+    if var not in ['time']:
+        np.testing.assert_allclose(output_slocum[var].values,
+                                   test_data_slocum[var].values, rtol=1e-6)
+    else:
+        dt0 = output_slocum[var].values - np.datetime64('2000-01-01')
+        dt1 = test_data_slocum[var].values - np.datetime64('2000-01-01')
+        assert np.allclose(
+            np.array(dt0, dtype='float64'),
+            np.array(dt1, dtype='float64'))
+
+
+def test_example_slocum_metadata():
+    # Test that attributes match. Have to remove creation and issue
+    # dates first
+    output_slocum.attrs.pop('date_created')
+    output_slocum.attrs.pop('date_issued')
+    test_data_slocum.attrs.pop('date_created')
+    test_data_slocum.attrs.pop('date_issued')
+    assert output_slocum.attrs == test_data_slocum.attrs
+
+
+# test the profiles with compliance_checker...
+
+def test_profiles_compliant():
+    # Load all available checker classes
+    check_suite = CheckSuite()
+    check_suite.load_all_available_checkers()
+    # Run cf and adcc checks
+    path = profiledir + '/dfo-rosie713-20190620T1313.nc'
+    checker_names = ['gliderdac', 'cf:1.8']
+    verbose = 0
+    criteria = 'normal'
+    output_filename = example_dir / 'report.json'
+    output_format = 'json'
+    """
+    Inputs to ComplianceChecker.run_checker
+
+    path            Dataset location (url or file)
+    checker_names   List of string names to run, should match keys of checkers dict (empty list means run all)
+    verbose         Verbosity of the output (0, 1, 2)
+    criteria        Determines failure (lenient, normal, strict)
+    output_filename Path to the file for output
+    output_format   Format of the output
+
+    @returns                If the tests failed (based on the criteria)
+    """
+    return_value, errors = ComplianceChecker.run_checker(path,
+                                                        checker_names,
+                                                        verbose,
+                                                        criteria,
+                                                        output_filename=output_filename,
+                                                        output_format=output_format)
+    # Open the JSON output and get the compliance scores
+    with open(output_filename, 'r') as fp:
+        cc_data = json.load(fp)
+        test = cc_data['gliderdac']
+        assert test['high_count'] == 0
+        assert test['medium_count'] == 0
+        assert test['low_count'] == 0
+        test = cc_data['cf:1.8']
+        assert test['high_count'] == 0
+        assert test['medium_count'] == 0
+        assert test['low_count'] == 0
+
+
+def test_timeseries_compliant():
+    # Load all available checker classes
+    check_suite = CheckSuite()
+    check_suite.load_all_available_checkers()
+    # Run cf and adcc checks
+    path = tsdir + '/dfo-rosie713-20190615.nc'
+    checker_names = ['cf:1.8']
+    verbose = 0
+    criteria = 'normal'
+    output_filename = example_dir / 'report.json'
+    output_format = 'json'
+    """
+    Inputs to ComplianceChecker.run_checker
+
+    path            Dataset location (url or file)
+    checker_names   List of string names to run, should match keys of checkers dict (empty list means run all)
+    verbose         Verbosity of the output (0, 1, 2)
+    criteria        Determines failure (lenient, normal, strict)
+    output_filename Path to the file for output
+    output_format   Format of the output
+
+    @returns                If the tests failed (based on the criteria)
+    """
+    return_value, errors = ComplianceChecker.run_checker(path,
+                                                        checker_names,
+                                                        verbose,
+                                                        criteria,
+                                                        output_filename=output_filename,
+                                                        output_format=output_format)
+    # Open the JSON output and get the compliance scores
+    with open(output_filename, 'r') as fp:
+        cc_data = json.load(fp)
+        test = cc_data['cf:1.8']
+        assert test['high_count'] == 0
+        # somehow the checker is confused by our trajectory variables.
+        assert test['medium_count'] == 1
+        assert test['low_count'] == 0
diff --git a/tests/test_utils.py b/tests/test_utils.py
index 8fc0c86..69439e4 100644
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -10,7 +10,7 @@
 library_dir = Path(__file__).parent.parent.absolute()
 example_dir = library_dir / 'tests/example-data/'
 
-test_data = xr.open_dataset(library_dir / 'tests/results/example-seaexplorer/L0-timeseries/dfo-eva035-20190718.nc')
+test_data = xr.open_dataset(library_dir / 'tests/expected/example-seaexplorer/L0-timeseries/dfo-eva035-20190718.nc')
 deploymentyaml = example_dir / 'example-seaexplorer-legato-flntu-arod-ad2cp/deploymentRealtime.yml'
 with open(deploymentyaml) as fin:
     deployment = yaml.safe_load(fin)