diff --git a/bids2openminds/main.py b/bids2openminds/main.py
index f710850..7c5f7f5 100644
--- a/bids2openminds/main.py
+++ b/bids2openminds/main.py
@@ -11,7 +11,7 @@
 from openminds import IRI
 
 from .utility import table_filter, pd_table_value, file_hash, file_storage_size, detect_nifti_version
-from .mapping import bids2openminds_instance
+from . import mapping
 
 
 def create_openminds_person(full_name):
@@ -94,32 +94,66 @@ def create_behavioral_protocol(layout, collection):
     return behavioral_protocols, behavioral_protocols_dict
 
 
+def techniques_openminds(suffix):
+    possible_types = ["Technique", "AnalysisTechnique", "StimulationApproach",
+                      "StimulationTechnique"]
+
+    if suffix in mapping.MAP_2_TECHNIQUES:
+        items_openminds = mapping.MAP_2_TECHNIQUES[suffix]
+    else:
+        return []
+
+    if items_openminds is None:
+        return []
+
+    openminds_techniques_list = []
+    for item_openminds in items_openminds:
+        for possible_type in possible_types:
+            openminds_type = getattr(controlled_terms, possible_type)
+            try:
+                openminds_obj = openminds_type.by_name(item_openminds)
+                break
+            except KeyError:
+                pass
+        openminds_techniques_list.append(openminds_obj)
+    return openminds_techniques_list
+
+
 def create_techniques(layout_df):
     suffixs = layout_df["suffix"].unique().tolist()
     techniques = []
     not_techniques_index = ["description", "participants", "events"]
     for suffix in suffixs:
         # excluding the None and non thechnique indexes
-        if not (pd.isna(suffix) or (suffix in not_techniques_index)):
-            openminds_techniques_cache = bids2openminds_instance(
-                suffix, "MAP_2_TECHNIQUES")
-            # Excluding the suffixs that are not in the library or flagged as non technique suffixes
-            if not pd.isna(openminds_techniques_cache):
-                techniques.extend(openminds_techniques_cache)
-            else:
-                warn(
-                    f"The {suffix} suffix is currently considered an auxiliary file for already existing techniques or a non technique file.")
+        if not (pd.isnull(suffix) or (suffix in not_techniques_index)):
+            openminds_techniques_cache = techniques_openminds(suffix)
+            techniques.extend(openminds_techniques_cache)
 
-    return techniques or None
+    techniques_set = set(techniques)
+    techniques_list = list(techniques_set)
+    return techniques_list or None
+
+
+def approaches_openminds(datatype):
+
+    if datatype in mapping.MAP_2_EXPERIMENTAL_APPROACHES:
+        items_openminds = mapping.MAP_2_EXPERIMENTAL_APPROACHES[datatype]
+
+    approches_list = []
+
+    for item in items_openminds:
+        approches_list.append(
+            controlled_terms.ExperimentalApproach.by_name(item))
+
+    return approches_list
 
 
 def create_approaches(layout_df):
     datatypes = layout_df["datatype"].unique().tolist()
     approaches = set([])
     for datatype in datatypes:
-        if not (pd.isna(datatype)):
-            approaches.update(bids2openminds_instance(
-                datatype, "MAP_2_EXPERIMENTAL_APPROACHES"))
+        if not (pd.isnull(datatype)):
+            approaches.update(approaches_openminds(datatype))
 
     return list(approaches) or None
 
@@ -233,6 +267,52 @@ def create_dataset(dataset_description, dataset_version, collection):
     return dataset
 
 
+def spices_openminds(data_subject: pd.DataFrame):
+    bids_species = pd_table_value(data_subject, "species")
+    if bids_species is None:
+        # In BIDS the default species is homo sapiens.
+        return controlled_terms.Species.homo_sapiens
+    if bids_species in mapping.MAP_2_SPECIES:
+        openminds_species = mapping.MAP_2_SPECIES[bids_species]
+        return controlled_terms.Species.by_name(openminds_species[0])
+    else:
+        try:
+            openminds_species = controlled_terms.Species.by_name(bids_species)
+            warn(
+                f"You have specified {bids_species} as species, we have autodetected {openminds_species.name}, please verify it.")
+            return openminds_species
+        except KeyError:
+            warn(
+                f"You have specified {bids_species} we currently don't support this species.")
+        return None
+
+
+def handedness_openminds(data_subject: pd.DataFrame):
+    bids_handedness = pd_table_value(data_subject, "handedness")
+    if bids_handedness is None:
+        return None
+    if bids_handedness in mapping.MAP_2_HANDEDNESS:
+        openminds_handedness = mapping.MAP_2_HANDEDNESS[bids_handedness]
+        return controlled_terms.Handedness.by_name(openminds_handedness[0])
+    else:
+        warn(
+            f"You have specified {bids_handedness} which is not a allowed value for handedness defined by BIDS standard.")
+        return None
+
+
+def sex_openminds(data_subject: pd.DataFrame):
+    bids_sex = pd_table_value(data_subject, "sex")
+    if bids_sex is None:
+        return None
+    if bids_sex in mapping.MAP_2_BIOLOGICALSEX:
+        bids_sex = mapping.MAP_2_BIOLOGICALSEX[bids_sex]
+        return controlled_terms.BiologicalSex.by_name(bids_sex[0])
+    else:
+        warn(
+            f"You have specified {bids_sex} which is not a allowed value for handedness defined by BIDS standard.")
+        return None
+
+
 def create_subjects(subject_id, layout_df, layout, collection):
 
     sessions = layout.get_sessions()
@@ -286,8 +366,6 @@ def create_subjects(subject_id, layout_df, layout, collection):
     # Select the tsv file of the table
     participants_path_tsv = pd_table_value(table_filter(
         participants_paths, ".tsv", "extension"), "path")
-    participants_path_json = pd_table_value(table_filter(
-        participants_paths, ".json", "extension"), "path")
 
     participants_table = pd.read_csv(participants_path_tsv, sep="\t", header=0)
     for subject in subject_id:
@@ -299,8 +377,7 @@ def create_subjects(subject_id, layout_df, layout, collection):
         if not sessions:
             state = omcore.SubjectState(
                 age=create_openminds_age(data_subject),
-                handedness=bids2openminds_instance(pd_table_value(
-                    data_subject, "handedness"), "MAP_2_HANDEDNESS", is_list=False),
+                handedness=handedness_openminds(data_subject),
                 internal_identifier=f"Studied state {subject_name}".strip(),
                 lookup_label=f"Studied state {subject_name}".strip()
             )
@@ -312,8 +389,7 @@ def create_subjects(subject_id, layout_df, layout, collection):
                 if not (table_filter(table_filter(layout_df, session, "session"), subject, "subject").empty):
                     state = omcore.SubjectState(
                         age=create_openminds_age(data_subject),
-                        handedness=bids2openminds_instance(pd_table_value(
-                            data_subject, "handedness"), "MAP_2_HANDEDNESS", is_list=False),
+                        handedness=handedness_openminds(data_subject),
                         internal_identifier=f"Studied state {subject_name} {session}".strip(
                         ),
                         lookup_label=f"Studied state {subject_name} {session}".strip(
@@ -324,13 +400,11 @@ def create_subjects(subject_id, layout_df, layout, collection):
                     state_cache.append(state)
             subject_state_dict[f"{subject}"] = state_cache_dict
         subject_cache = omcore.Subject(
-            biological_sex=bids2openminds_instance(pd_table_value(
-                data_subject, "sex"), "MAP_2_SEX", is_list=False),
+            biological_sex=sex_openminds(data_subject),
             lookup_label=f"{subject_name}",
             internal_identifier=f"{subject_name}",
             # TODO species should default to homo sapiens
-            species=bids2openminds_instance(pd_table_value(
-                data_subject, "species"), "MAP_2_SPECIES", is_list=False),
+            species=spices_openminds(data_subject),
             studied_states=state_cache
         )
         subjects_dict[f"{subject}"] = subject_cache
diff --git a/bids2openminds/mapping.py b/bids2openminds/mapping.py
index 4782e45..f630abf 100644
--- a/bids2openminds/mapping.py
+++ b/bids2openminds/mapping.py
@@ -1,173 +1,180 @@
-from .utility import openminds_instance
-
-
 MAP_2_EXPERIMENTAL_APPROACHES = {
-    "func": ["@id: https://openminds.ebrains.eu/instances/experimentalApproach/neuroimaging"],
+    "func": ["neuroimaging"],
     "dwi": [
-        "@id: https://openminds.ebrains.eu/instances/experimentalApproach/neuroimaging",
-        "@id: https://openminds.ebrains.eu/instances/experimentalApproach/neuralConnectivity",
-        "@id: https://openminds.ebrains.eu/instances/experimentalApproach/anatomy",
+        "neuroimaging",
+        "neural connectivity",
+        "anatomy"
     ],
-    "fmap": ["@id: https://openminds.ebrains.eu/instances/experimentalApproach/neuroimaging"],
+    "fmap": ["neuroimaging"],
     "anat": [
-        "@id: https://openminds.ebrains.eu/instances/experimentalApproach/neuroimaging",
-        "@id: https://openminds.ebrains.eu/instances/experimentalApproach/anatomy",
+        "neuroimaging",
+        "anatomy"
     ],
     "perf": [
-        "@id: https://openminds.ebrains.eu/instances/experimentalApproach/neuroimaging",
-        "@id: https://openminds.ebrains.eu/instances/experimentalApproach/anatomy",
+        "neuroimaging",
+        "anatomy"
     ],
-    "meg": ["@id: https://openminds.ebrains.eu/instances/experimentalApproach/neuroimaging"],
-    "eeg": ["@id: https://openminds.ebrains.eu/instances/experimentalApproach/electrophysiology"],
-    "ieeg": ["@id: https://openminds.ebrains.eu/instances/experimentalApproach/electrophysiology"],
-    "beh": ["@id: https://openminds.ebrains.eu/instances/experimentalApproach/behavior"],
+    "meg": ["neuroimaging"],
+    "eeg": ["electrophysiology"],
+    "ieeg": ["electrophysiology"],
+    "beh": ["behavior"],
     "pet": [
-        "@id: https://openminds.ebrains.eu/instances/experimentalApproach/radiology",
-        "@id: https://openminds.ebrains.eu/instances/experimentalApproach/neuroimaging",
+        "neuroimaging",
+        "radiology"
     ],
     "micr": [
-        "@id: https://openminds.ebrains.eu/instances/experimentalApproach/microscopy",
-        "@id: https://openminds.ebrains.eu/instances/experimentalApproach/anatomy",
-        "@id: https://openminds.ebrains.eu/instances/experimentalApproach/histology",
+        "microscopy",
+        "anatomy",
+        "histology"
     ],
-    "nirs": ["@id: https://openminds.ebrains.eu/instances/experimentalApproach/neuroimaging"],
+    "nirs": ["neuroimaging"]
 }
 
 MAP_2_TECHNIQUES = {
-    "angio": ["Angiogram"],
-    "M0map": ["Equilibrium magnetization (M0) map"],
-    "FLASH": ["Fast-Low-Angle-Shot image"],
-    "FLAIR": ["Fluid attenuated inversion recovery image"],
-    "UNIT1": ["Homogeneous (flat) T1-weighted MP2RAGE image"],
-    "inplaneT1": ["Inplane T1"],
-    "inplaneT2": ["Inplane T2"],
-    "R1map": ["Longitudinal relaxation rate image"],
-    "T1map": ["Longitudinal relaxation time image"],
-    "MTVmap": ["Macromolecular tissue volume (MTV) image"],
-    "MTRmap": ["Magnetization transfer ratio image"],
-    "MTsat": ["Magnetization transfer saturation image"],
-    "MWFmap": ["Myelin water fraction image"],
-    "S0map": ["Observed signal amplitude (S0) image"],
-    "R2starmap": ["Observed transverse relaxation rate image"],
-    "T2starmap": ["Observed transverse relaxation time image"],
-    "PDT2": ["PD and T2 weighted image"],
-    "PDw": ["Proton density (PD) weighted image"],
-    "PD": ["Proton density image"],
-    "PDmap": ["Proton density image"],
-    "Chimap": ["Quantitative susceptibility map (QSM)"],
-    "RB1map": ["RF receive sensitivity map"],
-    "TB1map": ["RF transmit field image"],
-    "T1rho": ["T1 in rotating frame (T1 rho) image"],
-    "T1w": ["T1-weighted image"],
-    "T2w": ["T2-weighted image"],
-    "T2star": ["T2* image"],
-    "T2starw": ["T2star weighted image"],
-    "R2map": ["True transverse relaxation rate image"],
-    "T2map": ["True transverse relaxation time image"],
-    "bold": ["Blood-Oxygen-Level Dependent image"],
-    "cbv": ["Cerebral blood volume image"],
-    "phase": ["Phase image"],
-    "defacemask": ["Defacing masks"],
-    "epi": ["EPI"],
-    "fieldmap": ["Fieldmap"],
-    "magnitude": ["Magnitude"],
-    "magnitude1": ["Magnitude"],
-    "magnitude2": ["Magnitude"],
-    "phase1": ["Phase"],
-    "phase2": ["Phase"],
-    "phasediff": ["Phase-difference"],
-    "dwi": ["@id: https://openminds.ebrains.eu/instances/technique/diffusionWeightedImaging"],
-    "sbref": ["Single-band reference image"],
-    "asl": ["Arterial Spin Labeling"],
-    "m0scan": ["M0"],
-    "eeg": ["@id:https://openminds.ebrains.eu/instances/technique/electroencephalography"],
-    "ieeg": ["Intracranial Electroencephalography"],
-    "physio": ["Physiological continuous recordings"],
-    "stim": ["stimulation continuous recordings"],
-    "beh": ["Behavioral experiments"],
-    "pet": ["@id:https://openminds.ebrains.eu/instances/technique/positronEmissionTomography"],
-    "2PE": ["2-photon excitation microscopy"],
-    "BF": ["Bright-field microscopy"],
-    "CARS": ["Coherent anti-Stokes Raman spectroscopy"],
-    "CONF": ["Confocal microscopy"],
-    "DIC": ["Differential interference contrast microscopy"],
-    "DF": ["Dark-field microscopy"],
-    "FLUO": ["Fluorescence microscopy"],
-    "MPE": ["Multi-photon excitation microscopy"],
-    "NLO": ["Nonlinear optical microscopy"],
-    "OCT": ["Optical coherence tomography"],
-    "PC": ["Phase-contrast microscopy"],
-    "PLI": ["Polarized-light microscopy"],
-    "SEM": ["Scanning electron microscopy"],
-    "SPIM": ["Selective plane illumination microscopy"],
-    "SR": ["Super-resolution microscopy"],
-    "TEM": ["Transmission electron microscopy"],
-    "uCT": ["Micro-CT"],
-    "nirs": ["Near-Infrared Spectroscopy"],
-    "motion": ["Motion"],
+    "angio": ["angiography"],
+    "M0map": ["equilibrium magnetization mapping"],
+    "FLASH": ["fast-low-angle-shot pulse sequence"], #TODO instance TBD
+    "FLAIR": ["fluid attenuated inversion recovery pulse sequence"], #TODO instance TBD
+    "UNIT1": None, #TODO instance TBD
+    "inplaneT1": [
+        "T1 pulse sequence", 
+        "structural magnetic resonance imaging"
+    ], #TODO sMRI
+    "inplaneT2": [
+        "T2 pulse sequence", 
+        "structural magnetic resonance imaging"
+    ], #TODO sMRI
+    "R1map": None, #TODO instance TBD
+    "T1map": None, #TODO instance TBD
+    "MTVmap": [
+        "quantitative magnetic resonance imaging",
+        "macromolecular tissue volume image processing"
+    ], #TODO other?
+    "MTRmap": [
+        "magnetization transfer imaging",
+        "magnetization transfer ratio image processing",
+        "magnetization transfer pulse sequence"
+    ], #TODO instances
+    "MTsat": [
+        "magnetization transfer imaging",
+        "magnetization transfer saturation image processing",
+        "magnetization transfer pulse sequence"
+    ], #TODO instances
+    "MWFmap": [
+        "myelin water imaging",
+        "T2 pulse sequence",
+        "myelin water fraction image processing"
+    ], #TODO instances
+    "S0map": None, #TODO instances
+    "R2starmap": None, #TODO instance TBD
+    "T2starmap": None, #TODO instance TBD
+    "PDT2": None, #TODO instance TBD
+    "PDw": None, #TODO instance TBD
+    "PD": None, #TODO instance TBD
+    "PDmap": None, #TODO instance TBD
+    "Chimap": None, #TODO instance TBD
+    "RB1map": None, #TODO instance TBD
+    "TB1map": None, #TODO instance TBD
+    "T1rho": None, #TODO instance TBD
+    "T1w": None, #TODO instance TBD
+    "T2w": None, #TODO instance TBD
+    "T2star": None, #TODO instance TBD
+    "T2starw": None, #TODO instance TBD
+    "R2map": None, #TODO instance TBD
+    "T2map": None, #TODO instance TBD
+    "bold": None, #TODO instance TBD
+    "cbv": None, #TODO instance TBD
+    "phase": None, #TODO instance TBD
+    "defacemask": None, #TODO instance TBD
+    "epi": None, #TODO instance TBD
+    "fieldmap": None, #TODO instance TBD
+    "magnitude": None, #TODO instance TBD
+    "magnitude1": None, #TODO instance TBD
+    "magnitude2": None, #TODO instance TBD
+    "phase1": None, #TODO instance TBD
+    "phase2": None, #TODO instance TBD
+    "phasediff": None, #TODO instance TBD
+    "dwi": ["diffusion-weighted imaging"],
+    "sbref": None, #TODO instance TBD
+    "asl": None, #TODO instance TBD
+    "m0scan": None, #TODO instance TBD
+    "eeg": ["electroencephalography"],
+    "ieeg": ["intracranial electroencephalography"],
+    "physio": None, #TODO instance TBD
+    "stim": None, #TODO instance TBD
+    "beh": None, #TODO instance TBD
+    "pet": ["positron emission tomography"],
+    "2PE": ["two-photon fluorescence microscopy"],
+    "BF": None, #TODO instance TBD
+    "CARS": None, #TODO instance TBD
+    "CONF": ["confocal microscopy"],
+    "DIC": None, #TODO instance TBD
+    "DF": None, #TODO instance TBD
+    "FLUO": None, #TODO instance TBD
+    "MPE": None, #TODO instance TBD
+    "NLO": None, #TODO instance TBD
+    "OCT": None, #TODO instance TBD
+    "PC": None, #TODO instance TBD
+    "PLI": ["polarized light microscopy"],
+    "SEM": None, #TODO instance TBD
+    "SPIM": None, #TODO instance TBD
+    "SR": None, #TODO instance TBD
+    "TEM": ["transmission electron microscopy"],
+    "uCT": None, #TODO instance TBD
+    "nirs": None, #TODO instance TBD
+    "motion": None, #TODO instance TBD
 }
 
-MAP_2_UNITS = {"year": ["@id:https://openminds.ebrains.eu/instances/unitOfMeasurement/year"]}
+MAP_2_UNITS = {
+    "year": ["year"]
+}
 
-MAP_2_SEX = {
-    "male": ["@id: https://openminds.ebrains.eu/instances/biologicalSex/male"],
-    "m": ["@id: https://openminds.ebrains.eu/instances/biologicalSex/male"],
-    "M": ["@id: https://openminds.ebrains.eu/instances/biologicalSex/male"],
-    "MALE": ["@id: https://openminds.ebrains.eu/instances/biologicalSex/male"],
-    "Male": ["@id: https://openminds.ebrains.eu/instances/biologicalSex/male"],
-    "female": ["@id: https://openminds.ebrains.eu/instances/biologicalSex/female"],
-    "f": ["@id: https://openminds.ebrains.eu/instances/biologicalSex/female"],
-    "F": ["@id: https://openminds.ebrains.eu/instances/biologicalSex/female"],
-    "FEMALE": ["@id: https://openminds.ebrains.eu/instances/biologicalSex/female"],
-    "Female": ["@id: https://openminds.ebrains.eu/instances/biologicalSex/female"],
+MAP_2_BIOLOGICALSEX = {
+    "male": ["male"],
+    "m": ["male"],
+    "M": ["male"],
+    "MALE": ["male"],
+    "Male": ["male"],
+    "female": ["female"],
+    "f": ["female"],
+    "F": ["female"],
+    "FEMALE": ["female"],
+    "Female": ["female"]
 }
 
 MAP_2_HANDEDNESS = {
-    "left": ["@id:https://openminds.ebrains.eu/instances/handedness/leftHandedness"],
-    "l": ["@id:https://openminds.ebrains.eu/instances/handedness/leftHandedness"],
-    "L": ["@id:https://openminds.ebrains.eu/instances/handedness/leftHandedness"],
-    "LEFT": ["@id:https://openminds.ebrains.eu/instances/handedness/leftHandedness"],
-    "Left": ["@id:https://openminds.ebrains.eu/instances/handedness/leftHandedness"],
-    "right": ["@id:https://openminds.ebrains.eu/instances/handedness/rightHandedness"],
-    "r": ["@id:https://openminds.ebrains.eu/instances/handedness/rightHandedness"],
-    "R": ["@id:https://openminds.ebrains.eu/instances/handedness/rightHandedness"],
-    "RIGHT": ["@id:https://openminds.ebrains.eu/instances/handedness/rightHandedness"],
-    "Right": ["@id:https://openminds.ebrains.eu/instances/handedness/rightHandedness"],
-    "ambidextrous": ["@id:https://openminds.ebrains.eu/instances/handedness/ambidextrousHandedness"],
-    "a": ["@id:https://openminds.ebrains.eu/instances/handedness/ambidextrousHandedness"],
-    "A": ["@id:https://openminds.ebrains.eu/instances/handedness/ambidextrousHandedness"],
-    "AMBIDEXTROUS": ["@id:https://openminds.ebrains.eu/instances/handedness/ambidextrousHandedness"],
-    "Ambidextrous": ["@id:https://openminds.ebrains.eu/instances/handedness/ambidextrousHandedness"],
+    "left": ["left handedness"],
+    "l": ["left handedness"],
+    "L": ["left handedness"],
+    "LEFT": ["left handedness"],
+    "Left": ["left handedness"],
+    "right": ["right handedness"],
+    "r": ["right handedness"],
+    "R": ["right handedness"],
+    "RIGHT": ["right handedness"],
+    "Right": ["right handedness"],
+    "ambidextrous": ["ambidextrous handedness"],
+    "a": ["ambidextrous handedness"],
+    "A": ["ambidextrous handedness"],
+    "AMBIDEXTROUS": ["ambidextrous handedness"],
+    "Ambidextrous": ["ambidextrous handedness"]
 }
 
 MAP_2_SPECIES = {
-    "homo sapiens": ["@id: https://openminds.ebrains.eu/instances/species/homoSapiens"],
-    "mus musculus": ["@id: https://openminds.ebrains.eu/instances/species/musMusculus"],
-    "rattus norvegicus": ["@id: https://openminds.ebrains.eu/instances/species/rattusNorvegicus"],
+    "homo sapiens": ["Homo sapiens"],
+    "mus musculus": ["Mus musculus"],
+    "rattus norvegicus": ["Rattus norvegicus"]
 }
 
 
-sample_types = {
-    "cell line",
-    "in vitro differentiated cells",
-    "primary cell",
-    "cell-free sample",
-    "cloning host",
-    "tissue",
-    "whole organisms",
-    "organoid",
-    "technical sample",
-}
-
-
-def bids2openminds_instance(bids_instance, dictionary, is_list: bool = True):
-    if bids_instance is None:
-        return None
-
-    try:
-        instance = openminds_instance(eval(dictionary)[bids_instance], is_list=is_list)
-        # TODO if warning warn(f"{item}is not a proper openMINDS instance") should say that this instance is not yet in openminds
-        return instance
-    except KeyError:
-        # Handle the case where the specified bids instance is not present in the dictionary
-        KeyError(f"Error: the bids instance '{bids_instance}' is not present in dictionary.")
+#sample_types = {
+#    "cell line": None, #TODO instance TBD
+#    "in vitro differentiated cells": None, #TODO instance TBD
+#    "primary cell": None, #TODO instance TBD
+#    "cell-free sample": None, #TODO instance TBD
+#    "cloning host": None, #TODO instance TBD
+#    "tissue": None, #TODO instance TBD
+#    "whole organisms": None, #TODO instance TBD
+#    "organoid": None, #TODO instance TBD
+#    "technical sample": None #TODO instance TBD
+#}
diff --git a/bids2openminds/utility.py b/bids2openminds/utility.py
index 0dbf9ac..ba557f3 100644
--- a/bids2openminds/utility.py
+++ b/bids2openminds/utility.py
@@ -12,11 +12,6 @@
 from openminds.latest.controlled_terms import UnitOfMeasurement
 
 
-def camel_to_snake(name):
-    name = re.sub("(.)([A-Z][a-z]+)", r"\1_\2", name)
-    return re.sub("([a-z0-9])([A-Z])", r"\1_\2", name).lower()
-
-
 def read_json(file_path: str) -> dict:
     """
     Reads the content of a JSON file and returns it as a Python dictionary.
@@ -69,30 +64,6 @@ def table_filter(dataframe: pd.DataFrame, filter_str: str, column: str = "suffix
         KeyError(f"Error: Column '{column}' not found in the DataFrame.")
 
 
-def openminds_instance(list: list, Terminologie: str = None, is_list: bool = True):
-    openminds_list = []
-
-    for item in list:
-        if item.replace(" ", "")[0:32] == "@id:https://openminds.ebrains.eu":
-            slash_location = item.rfind("/")
-            item_name = item[slash_location + 1:]
-            item_name_snake = camel_to_snake(item_name)
-            if not (Terminologie):
-                Terminologie = item[item[:slash_location].rfind(
-                    "/") + 1: slash_location]
-                Terminologie = Terminologie[0].upper() + Terminologie[1:]
-            controlled_class = getattr(controlled_terms, Terminologie)
-            openminds_item = getattr(controlled_class, item_name_snake)
-            openminds_list.append(openminds_item)
-        else:
-            warn(f"{item}is not a proper openMINDS instance")
-
-    if is_list:
-        return openminds_list
-    else:
-        return openminds_item
-
-
 def pd_table_value(data_frame, column_name, not_list: bool = True):
     try:
         if column_name in data_frame.columns:
diff --git a/test/test_example_datasets_click.py b/test/test_example_datasets_click.py
index 75a7372..3c32416 100644
--- a/test/test_example_datasets_click.py
+++ b/test/test_example_datasets_click.py
@@ -4,7 +4,7 @@
 from bids2openminds.converter import convert_click
 from click.testing import CliRunner
 
-(test_data_set, number_of_openminds_files) = ("ds003", 141)
+(test_data_set, number_of_openminds_files) = ("ds003", 143)
 
 
 def test_example_datasets_click():