diff --git a/zipline/data/data_portal.py b/zipline/data/data_portal.py
new file mode 100644
index 00000000..d691fc5b
--- /dev/null
+++ b/zipline/data/data_portal.py
@@ -0,0 +1,190 @@
+#
+# Copyright 2015 Quantopian, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from logbook import Logger
+
+log = Logger('DataPortal')
+
+BASE_FIELDS = {
+    'open': 'open',
+    'open_price': 'open',
+    'high': 'high',
+    'low': 'low',
+    'close': 'close',
+    'close_price': 'close',
+    'volume': 'volume',
+    'price': 'close'
+}
+
+
+class DataPortal(object):
+    def __init__(self,
+                 env,
+                 sim_params=None,
+                 equity_daily_reader=None,
+                 equity_minute_reader=None,
+                 future_daily_reader=None,
+                 future_minute_reader=None,
+                 adjustment_reader=None):
+
+        self._adjustment_reader = adjustment_reader
+
+        self._equity_daily_reader = equity_daily_reader
+        self._equity_minute_reader = equity_minute_reader
+        self._future_daily_reader = future_daily_reader
+        self._future_minute_reader = future_minute_reader
+
+    def get_previous_value(self, asset, field, dt, data_frequency):
+        """
+        Given an asset and a column and a dt, returns the previous value for
+        the same asset/column pair.  If this data portal is in minute mode,
+        it's the previous minute value, otherwise it's the previous day's
+        value.
+
+        Parameters
+        ---------
+        asset : Asset
+            The asset whose data is desired.
+
+        field: string
+            The desired field of the asset.  Valid values are "open",
+            "open_price", "high", "low", "close", "close_price", "volume", and
+            "price".
+
+        dt: pd.Timestamp
+            The timestamp from which to go back in time one slot.
+
+        data_frequency: string
+            The frequency of the data to query; i.e. whether the data is
+            'daily' or 'minute' bars
+
+        Returns
+        -------
+        The value of the desired field at the desired time.
+        """
+        NotImplementedError
+
+    def get_spot_value(self, asset, field, dt, data_frequency):
+        """
+        Public API method that returns a scalar value representing the value
+        of the desired asset's field at either the given dt.
+
+        Parameters
+        ---------
+        asset : Asset
+            The asset whose data is desired.gith
+
+        field: string
+            The desired field of the asset.  Valid values are "open",
+            "open_price", "high", "low", "close", "close_price", "volume", and
+            "price".
+
+        dt: pd.Timestamp
+            The timestamp for the desired value.
+
+        data_frequency: string
+            The frequency of the data to query; i.e. whether the data is
+            'daily' or 'minute' bars
+
+        Returns
+        -------
+        The value of the desired field at the desired time.
+        """
+        NotImplementedError
+
+    def get_history_window(self, assets, end_dt, bar_count, frequency, field,
+                           ffill=True):
+        """
+        Public API method that returns a dataframe containing the requested
+        history window.  Data is fully adjusted.
+
+        Parameters
+        ---------
+        assets : list of zipline.data.Asset objects
+            The assets whose data is desired.
+
+        bar_count: int
+            The number of bars desired.
+
+        frequency: string
+            "1d" or "1m"
+
+        field: string
+            The desired field of the asset.
+
+        ffill: boolean
+            Forward-fill missing values. Only has effect if field
+            is 'price'.
+
+        Returns
+        -------
+        A dataframe containing the requested data.
+        """
+        NotImplementedError
+
+    def get_splits(self, sids, dt):
+        """
+        Returns any splits for the given sids and the given dt.
+
+        Parameters
+        ----------
+        sids : list
+            Sids for which we want splits.
+
+        dt: pd.Timestamp
+            The date for which we are checking for splits.  Note: this is
+            expected to be midnight UTC.
+
+        Returns
+        -------
+        list: List of splits, where each split is a (sid, ratio) tuple.
+        """
+        NotImplementedError
+
+    def get_stock_dividends(self, sid, trading_days):
+        """
+        Returns all the stock dividends for a specific sid that occur
+        in the given trading range.
+
+        Parameters
+        ----------
+        sid: int
+            The asset whose stock dividends should be returned.
+
+        trading_days: pd.DatetimeIndex
+            The trading range.
+
+        Returns
+        -------
+        list: A list of objects with all relevant attributes populated.
+        All timestamp fields are converted to pd.Timestamps.
+        """
+        NotImplementedError
+
+    def get_fetcher_assets(self, day):
+        """
+        Returns a list of assets for the current date, as defined by the
+        fetcher data.
+
+        Notes
+        -----
+        Data is forward-filled.  If there is no fetcher data defined for day
+        N, we use day N-1's data (if available, otherwise we keep going back).
+
+        Returns
+        -------
+        list: a list of Asset objects.
+        """
+        NotImplementedError
diff --git a/zipline/data/future_pricing.py b/zipline/data/future_pricing.py
new file mode 100644
index 00000000..a485f78c
--- /dev/null
+++ b/zipline/data/future_pricing.py
@@ -0,0 +1,27 @@
+# Copyright 2015 Quantopian, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+class FutureDailyReader(object):
+    """
+    Stubbed out. Currently unimplemented.
+    """
+    pass
+
+
+class FutureMinuteReader(object):
+
+    def __init__(self, rootdir, sid_path_func=None):
+        self.rootdir = rootdir
+        self.sid_path_func = sid_path_func
diff --git a/zipline/data/us_equity_minutes.py b/zipline/data/us_equity_minutes.py
new file mode 100644
index 00000000..c57036b8
--- /dev/null
+++ b/zipline/data/us_equity_minutes.py
@@ -0,0 +1,93 @@
+# Copyright 2015 Quantopian, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import bcolz
+import json
+import os
+import pandas as pd
+
+MINUTES_PER_DAY = 390
+
+METADATA_FILENAME = 'metadata.json'
+
+
+class BcolzMinuteBarReader(object):
+
+    def __init__(self, rootdir, sid_path_func=None):
+        self.rootdir = rootdir
+
+        metadata = self._get_metadata()
+
+        self.first_trading_day = pd.Timestamp(
+            metadata['first_trading_day'], tz='UTC')
+
+        self._sid_path_func = sid_path_func
+
+        self._carrays = {
+            'open': {},
+            'high': {},
+            'low': {},
+            'close': {},
+            'volume': {},
+            'sid': {},
+            'dt': {},
+        }
+
+    def _get_metadata(self):
+        with open(os.path.join(self.rootdir, METADATA_FILENAME)) as fp:
+            return json.load(fp)
+
+    def _get_ctable(self, asset):
+        sid = int(asset)
+        if self._sid_path_func is not None:
+            path = self._sid_path_func(self.rootdir, sid)
+        else:
+            path = "{0}/{1}.bcolz".format(self.rootdir, sid)
+
+        return bcolz.open(path, mode='r')
+
+    def _find_position_of_minute(self, minute_dt):
+        """
+        Internal method that returns the position of the given minute in the
+        list of every trading minute since market open of the first trading
+        day.
+
+        IMPORTANT: This method assumes every day is 390 minutes long, even
+        early closes.  Our minute bcolz files are generated like this to
+        support fast lookup.
+
+        ex. this method would return 2 for 1/2/2002 9:32 AM Eastern, if
+        1/2/2002 is the first trading day of the dataset.
+
+        Parameters
+        ----------
+        minute_dt: pd.Timestamp
+            The minute whose position should be calculated.
+
+        Returns
+        -------
+        The position of the given minute in the list of all trading minutes
+        since market open on the first trading day.
+        """
+        NotImplementedError
+
+    def _open_minute_file(self, field, asset):
+        sid_str = str(int(asset))
+
+        try:
+            carray = self._carrays[field][sid_str]
+        except KeyError:
+            carray = self._carrays[field][sid_str] = \
+                self._get_ctable(asset)[field]
+
+        return carray