ModelActivityData schemas and implementations
Initial design work circa 2006
The following section includes the initial design work done in 2006. Some of this is out-of-date.
Types of data and schemas used by model-activities.
In this first version of the document I am limiting my focus to model-activities of the experimental type. I define these models as ones where the user adjusts input parameters and starts the model, the model runs and ends in a new state. This type could naturally be extended to include a challenge type of experimental model where a goal is defined and a distance from goal is an output. I have not done that yet.
ModelActivityState
The ModelAcivityState is used to persist the state of a model-activity. This is used for model-activities where he user has the ability to create data, construct representations, or create state whose persistence would be useful to the user. The state saved is specific to the specific implementation of the model-activity. The data saved should be sufficient so that the state can be reconstituted by the model-activity so that a learner could continue work or a researcher or teacher could evaluate the work.
Examples of model-activities where ModelAcivityState persistence should be implemented.
- probeware data collection
- conceptual map
- electric hockey
- any model-activity where the user creates a model
Examples of model-activities where ModelAcivityState persistence should not be implemented.
- model animations (models which function effectively as movies)
ModelActivityData
The ModelActivityData is used to represent data about use of a model-activities that are general across the class of model-activities. The elements of the ModelActivityData represent data such as when the model was used and how long; how many times was the model run; what were the range of user settable input parameters and what settings did the user set; if a challenge was part of the model what was the result of each run. All of these data are general to model-activities of the experimental type.
Here is my suggested (informal) schemas for ModelActivityData:
Simplest possible ModelActivityData:
<modelactivitydata> <name></name> <start_time></start_time> <elapsed_time></elapsed_time> </modelactivitydata>
A somewhat richer ModelActivityData Schema for an experimental model:
<modelactivitydata>
<name></name>
<start_time></start_time>
<elapsed_time></elapsed_time>
<modelruns>
<modelrun>
<start_time></start_time>
<elapsed_time></elapsed_time>
</modelrun>
</modelruns>
</modelactivitydata>
A more complex version:
<modelactivitydata> <name></name> <start_time></start_time> <end_time></end_time> <computational_input name="unique_computational_input_name1"> <units></units> <range> <min_value></min_value> <max_value></max_value> </range> </computational_input> <computational_input name="unique_computational_input_name2"> <units></units> <range> <min_value></min_value> <max_value></max_value> </range> </computational_input> <representational_attribute name="unique_representational_attribute_name1"> <value_list> <value></value> <value></value> </value_list> </representational_attribute> <modelruns> <modelrun> <start_time></start_time> <end_time></end_time> <computational_input_value reference="unique_computational_input_name1" visible="boolean" mutable="boolean"> <value></value> </computational_input-value> <computational_input_value reference="unique_computational_input_name2" visible="boolean" mutable="boolean"> <value></value> </computational_input-value> <representational_attribute_value reference="unique_representational_attribute_name1"> <value></value> </representational_attribute_value> </modelrun> </modelruns> </modelactivitydata>
Actual implementations and examples
This sections documents actual implementations and includes examples of ModelActivityData learner data
UML diagram of the OTrunk schema for ModelActivityData
Here's a UML diagram of the schema as it is currently implemented in OTrunk:
http://www.concord.org/~aunger/images/modelactivitydata/default.svg
Real ModelActivityData from TELS AirBag model step
Here's a real example taken from an AirBags run in TELS. The schema used is in XML and not OTML but you can see some new elements:
A modelrun element has trial elements:
- a trial has two attributes
- goal: a string describing the learners intention in running this experiment
- number: a sequence number for the experiments using this model
A modelactivitydata element has a findings element with a list of finding elements:
- a finding has three attributes
- evidence: a learner-entered string describing evidence for this finding
- text: a learner-entered string describing the implications of this finding
- sequence: a generated sequence index that orders the findings by creation time
<modelactivitydata>
<name>Airbag</name>
<start_time>1197388463839</start_time>
<end_time>1197392556824</end_time>
<computational_input name="Dummy Position">
<units>meters</units>
<range>
<max_value>0.5</max_value>
<min_value>0</min_value>
</range>
</computational_input>
<computational_input name="Dummy Velocity">
<units>meters/second</units>
<range>
<max_value>0</max_value>
<min_value>-10</min_value>
</range>
</computational_input>
<computational_input name="Dummy Time">
<units>seconds</units>
<range>
<max_value>0.1</max_value>
<min_value>0</min_value>
</range>
</computational_input>
<representational_attribute name="Vertical Axis Type">
<value_list>
<value>X Position (m)</value>
<value>Vx: X Velocity (m/s)</value>
</value_list>
</representational_attribute>
<modelruns>
<modelrun>
<start_time>1197388557455</start_time>
<end_time>1197388670052</end_time>
<trial goal="undefined" number="1"/>
<computational_input_value reference="Dummy Position">
<value>0.04</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>0</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.04</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197388670052</start_time>
<end_time>1197388687522</end_time>
<trial goal="Why are shorter drivers at greater risk for injury from an airbag than taller drivers?
" number="2"/>
<computational_input_value reference="Dummy Position">
<value>0.04</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>0</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.04</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197388687522</start_time>
<end_time>1197388720822</end_time>
<trial goal="Why are shorter drivers at greater risk for injury from an airbag than taller drivers?
" number="3"/>
<computational_input_value reference="Dummy Position">
<value>0.04</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-4</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.06</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>Vx: X Velocity (m/s)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197388832468</start_time>
<end_time>1197388935099</end_time>
<trial goal="What happens when the dummy is far from the steering wheel?" number="6"/>
<computational_input_value reference="Dummy Position">
<value>0.5</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-4</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.06</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>Vx: X Velocity (m/s)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197388971036</start_time>
<end_time>1197389136618</end_time>
<trial goal="What happens when the dummy is close to the steering wheel?" number="10"/>
<computational_input_value reference="Dummy Position">
<value>0.12</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-4</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.06</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>Vx: X Velocity (m/s)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389136618</start_time>
<end_time>1197389177296</end_time>
<trial goal="Just exploring the simulation" number="11"/>
<computational_input_value reference="Dummy Position">
<value>0.42</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-4</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.06</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389177296</start_time>
<end_time>1197389272408</end_time>
<trial goal="What happens when the dummy is close to the steering wheel?" number="12"/>
<computational_input_value reference="Dummy Position">
<value>0.12</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-4</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.06</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389272408</start_time>
<end_time>1197389327436</end_time>
<trial goal="What happens when the dummy is close to the steering wheel?" number="13"/>
<computational_input_value reference="Dummy Position">
<value>0.3</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>0</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.06</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389327436</start_time>
<end_time>1197389361111</end_time>
<trial goal="Just exploring the simulation" number="14"/>
<computational_input_value reference="Dummy Position">
<value>0.36</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>0</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.06</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389361111</start_time>
<end_time>1197389396049</end_time>
<trial goal="Just exploring the simulation" number="15"/>
<computational_input_value reference="Dummy Position">
<value>0.36</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-10</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.06</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389396049</start_time>
<end_time>1197389436836</end_time>
<trial goal="Just exploring the simulation" number="16"/>
<computational_input_value reference="Dummy Position">
<value>0.5</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-10</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.06</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389436836</start_time>
<end_time>1197389464069</end_time>
<trial goal="Just exploring the simulation" number="17"/>
<computational_input_value reference="Dummy Position">
<value>0.5</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-10</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389464069</start_time>
<end_time>1197389494734</end_time>
<trial goal="Just exploring the simulation" number="18"/>
<computational_input_value reference="Dummy Position">
<value>0.5</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-10</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389494734</start_time>
<end_time>1197389545379</end_time>
<trial goal="Just exploring the simulation" number="19"/>
<computational_input_value reference="Dummy Position">
<value>0.5</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-10</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.1</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389545379</start_time>
<end_time>1197389585635</end_time>
<trial goal="Why are shorter drivers at greater risk for injury from an airbag than taller drivers?
" number="20"/>
<computational_input_value reference="Dummy Position">
<value>0.5</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-10</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.1</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389585635</start_time>
<end_time>1197389630899</end_time>
<trial goal="Why are shorter drivers at greater risk for injury from an airbag than taller drivers?
" number="21"/>
<computational_input_value reference="Dummy Position">
<value>0.5</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-10</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.1</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389642238</start_time>
<end_time>1197389684429</end_time>
<trial goal="Why are shorter drivers at greater risk for injury from an airbag than taller drivers?
" number="23"/>
<computational_input_value reference="Dummy Position">
<value>0.28</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-10</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.1</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389684429</start_time>
<end_time>1197389852538</end_time>
<trial goal="Why are shorter drivers at greater risk for injury from an airbag than taller drivers?
" number="24"/>
<computational_input_value reference="Dummy Position">
<value>0.28</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-10</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.1</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389852538</start_time>
<end_time>1197389892686</end_time>
<trial goal="Should cars be designed to crumple more or less during a crash to help prevent injury from an airbag?
" number="25"/>
<computational_input_value reference="Dummy Position">
<value>0.28</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-9</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.07</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389971531</start_time>
<end_time>1197389999606</end_time>
<trial goal="What happens when the dummy is far from the steering wheel?" number="27"/>
<computational_input_value reference="Dummy Position">
<value>0.28</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-9</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.07</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197389999606</start_time>
<end_time>1197390223912</end_time>
<trial goal="What happens when the dummy is far from the steering wheel?" number="28"/>
<computational_input_value reference="Dummy Position">
<value>0.5</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-9</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.07</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197390223912</start_time>
<end_time>1197390271282</end_time>
<trial goal="What happens when the dummy is far from the steering wheel?" number="29"/>
<computational_input_value reference="Dummy Position">
<value>0.26</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-9</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.07</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
<modelrun>
<start_time>1197390271282</start_time>
<end_time>0</end_time>
<trial goal="What happens when the dummy is far from the steering wheel?" number="30"/>
<computational_input_value reference="Dummy Position">
<value>0.26</value>
</computational_input_value>
<computational_input_value reference="Dummy Velocity">
<value>-9</value>
</computational_input_value>
<computational_input_value reference="Dummy Time">
<value>0.07</value>
</computational_input_value>
<representational_attribute_value reference="Vertical Axis Type">
<value>X Position (m)</value>
</representational_attribute_value>
</modelrun>
</modelruns>
<findings>
<finding evidence="The graph of the position versus time shows that the airbag hit the person" sequence="1" text="The person was injured by the moving airbag"/>
<finding evidence="on the graph, the air bag, and dummy intersect" sequence="2" text="shorter poeple are at higher risk to get injured because the air bag moves the driver back."/>
<finding evidence="the dummy takes a long time to move foward and hit the airbag." sequence="3" text="cars should be able to crumple more, because it gives time for the air bag to inflate."/>
<finding evidence="the grapg shows trhat they both takes along time to reach its points to entefirer." sequence="4" text="when the driver is far from the streeing wheel, the airbag gets inflated before the driver reaches it, so it doesnt get hurt. "/>
<finding evidence="onm the graph, they interfier quickly" sequence="5" text="when the driver is close to the steeing wheel, the air bag pushes the driver back. injuring te driver."/>
</findings>
</modelactivitydata>
Real ModelActivityData from TELS Global Warming NetLogo model step
Here's a real example taken from a Global Warming NetLogo model step from TELS.
This example shows each user generated change in a computational input during a model run. Later because of the size of these data generated by learners got quite large changes to a computational input during a model run was modeled by an computational_inputs element which summarized the extent of the changes made by a learner instead of each individual change.
<modelactivitydata>
<name>Greenhouse Effect</name>
<start_time>1196877287609</start_time>
<end_time>1196877427984</end_time>
<computational_input name="Number of clouds">
<units>number</units>
<range>
<max_value>100</max_value>
<min_value>0</min_value>
</range>
</computational_input>
<computational_input name="Pop-growth-rate">
<units>percent</units>
<range>
<max_value>20</max_value>
<min_value>-20</min_value>
</range>
</computational_input>
<computational_input name="CO2-emission">
<units>percent</units>
<range>
<max_value>200</max_value>
<min_value>0</min_value>
</range>
</computational_input>
<representational_attribute name="Sunray">
<value_list>
<value>Watch Sunray</value>
</value_list>
</representational_attribute>
<modelruns>
<modelrun>
<start_time>1196877295984</start_time>
<end_time>1196877424468</end_time>
<computational_input_value reference="Number of clouds">
<value>0</value>
<time>1196877295984</time>
</computational_input_value>
<computational_input_value reference="Pop-growth-rate">
<value>-3.85</value>
<time>1196877295984</time>
</computational_input_value>
<computational_input_value reference="CO2-emission">
<value>174</value>
<time>1196877296000</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>0</value>
<time>1196877313062</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>1</value>
<time>1196877315187</time>
</computational_input_value>
<representational_attribute_value reference="Sunray">
<value>Watch Sunray</value>
<time>1196877323234</time>
</representational_attribute_value>
<representational_attribute_value reference="Sunray">
<value>Watch Sunray</value>
<time>1196877325296</time>
</representational_attribute_value>
<representational_attribute_value reference="Sunray">
<value>Watch Sunray</value>
<time>1196877327093</time>
</representational_attribute_value>
<computational_input_value reference="Number of clouds">
<value>2</value>
<time>1196877402421</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>3</value>
<time>1196877402609</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>4</value>
<time>1196877402796</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>5</value>
<time>1196877402984</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>6</value>
<time>1196877403203</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>7</value>
<time>1196877403343</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>8</value>
<time>1196877403515</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>9</value>
<time>1196877403671</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>10</value>
<time>1196877403828</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>11</value>
<time>1196877404000</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>12</value>
<time>1196877404171</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>13</value>
<time>1196877404359</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>14</value>
<time>1196877404546</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>15</value>
<time>1196877404875</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>16</value>
<time>1196877405187</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>17</value>
<time>1196877405375</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>18</value>
<time>1196877405515</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>19</value>
<time>1196877405718</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>20</value>
<time>1196877406062</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>21</value>
<time>1196877406406</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>22</value>
<time>1196877406703</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>23</value>
<time>1196877406921</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>24</value>
<time>1196877407296</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>25</value>
<time>1196877407531</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>26</value>
<time>1196877407828</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>27</value>
<time>1196877408140</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>28</value>
<time>1196877408453</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>29</value>
<time>1196877408609</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>30</value>
<time>1196877408937</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>31</value>
<time>1196877409093</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>32</value>
<time>1196877409453</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>33</value>
<time>1196877409718</time>
</computational_input_value>
<computational_input_value reference="Number of clouds">
<value>34</value>
<time>1196877410078</time>
</computational_input_value>
<representational_attribute_value reference="Sunray">
<value>Watch Sunray</value>
<time>1196877415171</time>
</representational_attribute_value>
<representational_attribute_value reference="Sunray">
<value>Watch Sunray</value>
<time>1196877416406</time>
</representational_attribute_value>
<representational_attribute_value reference="Sunray">
<value>Watch Sunray</value>
<time>1196877417218</time>
</representational_attribute_value>
<representational_attribute_value reference="Sunray">
<value>Watch Sunray</value>
<time>1196877417750</time>
</representational_attribute_value>
<representational_attribute_value reference="Sunray">
<value>Watch Sunray</value>
<time>1196877418375</time>
</representational_attribute_value>
</modelrun>
</modelruns>
</modelactivitydata>