add bibliography file in Data folder

.gitignore

@@ -1,5 +1,6 @@
 private/
 Data/
+!Data/savedrecs.txt
 Getting_traffic_safety_data_from_online_resource_cache/
 Getting_traffic_safety_data_from_online_resource_files/
 .Rproj.user

Getting traffic safety data from online resource.Rmd

@@ -144,7 +144,7 @@ out <- capture.output(summary(netstat, k=60))
 ![A keyword co-occurrence network of the literature, depicting the 60 most used keywords.](Figures/keywords-co-occ-60words.png){width=500px}
 </center>
 
-## A conceptual Structure Map
+## A conceptual structure map
 
 Creating a Conceptual Structure Map from the Titles Using the MCA Method with terms mentioned at least 25 times in the title
 
@@ -394,8 +394,8 @@ datatable(
 
 
 
-An example of clustering{.tabset .tabset-fade}
-========================
+A clustering example {.tabset .tabset-fade}
+====================
 ***
 The following codes attempts to replicate the visual clustering approach by @van1999cluster
 
@@ -550,9 +550,13 @@ summary(poisson_fit)
 
 For a detailed explanation on interpreting the results of a Poisson regression, the readers can refer to [the example by the UCLA](https://stats.idre.ucla.edu/r/dae/poisson-regression/).
 
+# Optimization
+
+Since optimization code is mostly Python-based, we do not provide code on the optimization section here. Should the readers have interest in this part, they can contact Qiong, Amir, and Alex.
+
 # Acknowledgement{-}
 
-We thank the National Science Foundation for supporting our research. We also thank the DarkSky API for providing us five million free calls to their weather database.
+This work was supported in part by  the National Science Foundation (CMMI-1635927 and CMMI-1634992), the Ohio Supercomputer Center (PMIU0138 and PMIU0162), the American Society of Safety Professionals (ASSP) Foundation, the University of Cincinnati Education and Research Center Pilot Research Project Training Program, and the Transportation Informatics Tier I University Transportation Center (TransInfo). We also thank the DarkSky API for providing us five million free calls to their weather database.
 
 # References {#references .unnumbered}
 

Getting_traffic_safety_data_from_online_resource.html

@@ -3962,14 +3962,14 @@ <h2><a href="#content">Supplemental materials - Transportation safety review</a>
       <ul>
       <li><a href="#bibliographic-analysis"><span class="toc-section-number">1</span> Bibliographic analysis</a><ul>
       <li><a href="#keyword-co-occurrences"><span class="toc-section-number">1.1</span> keyword co-occurrences</a></li>
-      <li><a href="#a-conceptual-structure-map"><span class="toc-section-number">1.2</span> A conceptual Structure Map</a></li>
+      <li><a href="#a-conceptual-structure-map"><span class="toc-section-number">1.2</span> A conceptual structure map</a></li>
       </ul></li>
       <li><a href="#extracting-online-transportation-safety-data"><span class="toc-section-number">2</span> Extracting online transportation safety data</a><ul>
       <li><a href="#crash-related-data"><span class="toc-section-number">2.1</span> Crash-related data</a></li>
       <li><a href="#traffic-flow-data"><span class="toc-section-number">2.2</span> Traffic flow data</a></li>
       <li><a href="#weather-data"><span class="toc-section-number">2.3</span> Weather data</a></li>
       </ul></li>
-      <li><a href="#an-example-of-clustering"><span class="toc-section-number">3</span> An example of clustering</a><ul>
+      <li><a href="#a-clustering-example"><span class="toc-section-number">3</span> A clustering example</a><ul>
       <li><a href="#collecting-data"><span class="toc-section-number">3.1</span> Collecting Data</a></li>
       <li><a href="#clustering"><span class="toc-section-number">3.2</span> Clustering</a></li>
       <li><a href="#visualization"><span class="toc-section-number">3.3</span> Visualization</a></li>
@@ -3978,6 +3978,7 @@ <h2><a href="#content">Supplemental materials - Transportation safety review</a>
       <li><a href="#logistic-regression"><span class="toc-section-number">4.1</span> Logistic regression</a></li>
       <li><a href="#poisson-regression"><span class="toc-section-number">4.2</span> Poisson regression</a></li>
       </ul></li>
+      <li><a href="#optimization"><span class="toc-section-number">5</span> Optimization</a></li>
       <li><a href="#acknowledgement">Acknowledgement</a></li>
       <li><a href="#references">References</a></li>
       </ul>
@@ -4079,7 +4080,7 @@ <h2><span class="header-section-number">1.1</span> keyword co-occurrences</h2>
 </center>
 </div>
 <div id="a-conceptual-structure-map" class="section level2">
-<h2><span class="header-section-number">1.2</span> A conceptual Structure Map</h2>
+<h2><span class="header-section-number">1.2</span> A conceptual structure map</h2>
 <p>Creating a Conceptual Structure Map from the Titles Using the MCA Method with terms mentioned at least 25 times in the title</p>
 <div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" title="1">CS &lt;-<span class="st"> </span><span class="kw">conceptualStructure</span>(</a>
 <a class="sourceLine" id="cb3-2" title="2">  M,<span class="dt">field=</span><span class="st">&quot;ID_TM&quot;</span>, <span class="dt">method=</span><span class="st">&quot;MCA&quot;</span>, <span class="dt">minDegree=</span><span class="dv">20</span>, </a>
@@ -4319,8 +4320,8 @@ <h3><span class="header-section-number">2.3.2</span> Historical (daily)</h3>
 </div>
 </div>
 </div>
-<div id="an-example-of-clustering" class="section level1 tabset tabset-fade">
-<h1><span class="header-section-number">3</span> An example of clustering</h1>
+<div id="a-clustering-example" class="section level1 tabset tabset-fade">
+<h1><span class="header-section-number">3</span> A clustering example</h1>
 <hr />
 <p>The following codes attempts to replicate the visual clustering approach by <span class="citation">Van Wijk and Van Selow (<a href="#ref-van1999cluster">1999</a>)</span></p>
 <blockquote>
@@ -4507,9 +4508,13 @@ <h3>R code</h3>
 </div>
 </div>
 </div>
+<div id="optimization" class="section level1">
+<h1><span class="header-section-number">5</span> Optimization</h1>
+<p>Since optimization code is mostly Python-based, we do not provide code on the optimization section here. Should the readers have interest in this part, they can contact Qiong, Amir, and Alex.</p>
+</div>
 <div id="acknowledgement" class="section level1 unnumbered">
 <h1>Acknowledgement</h1>
-<p>We thank the National Science Foundation for supporting our research. We also thank the DarkSky API for providing us five million free calls to their weather database.</p>
+<p>This work was supported in part by the National Science Foundation (CMMI-1635927 and CMMI-1634992), the Ohio Supercomputer Center (PMIU0138 and PMIU0162), the American Society of Safety Professionals (ASSP) Foundation, the University of Cincinnati Education and Research Center Pilot Research Project Training Program, and the Transportation Informatics Tier I University Transportation Center (TransInfo). We also thank the DarkSky API for providing us five million free calls to their weather database.</p>
 </div>
 <div id="references" class="section level1 unnumbered">
 <h1>References</h1>

index.html

@@ -3962,14 +3962,14 @@ <h2><a href="#content">Supplemental materials - Transportation safety review</a>
       <ul>
       <li><a href="#bibliographic-analysis"><span class="toc-section-number">1</span> Bibliographic analysis</a><ul>
       <li><a href="#keyword-co-occurrences"><span class="toc-section-number">1.1</span> keyword co-occurrences</a></li>
-      <li><a href="#a-conceptual-structure-map"><span class="toc-section-number">1.2</span> A conceptual Structure Map</a></li>
+      <li><a href="#a-conceptual-structure-map"><span class="toc-section-number">1.2</span> A conceptual structure map</a></li>
       </ul></li>
       <li><a href="#extracting-online-transportation-safety-data"><span class="toc-section-number">2</span> Extracting online transportation safety data</a><ul>
       <li><a href="#crash-related-data"><span class="toc-section-number">2.1</span> Crash-related data</a></li>
       <li><a href="#traffic-flow-data"><span class="toc-section-number">2.2</span> Traffic flow data</a></li>
       <li><a href="#weather-data"><span class="toc-section-number">2.3</span> Weather data</a></li>
       </ul></li>
-      <li><a href="#an-example-of-clustering"><span class="toc-section-number">3</span> An example of clustering</a><ul>
+      <li><a href="#a-clustering-example"><span class="toc-section-number">3</span> A clustering example</a><ul>
       <li><a href="#collecting-data"><span class="toc-section-number">3.1</span> Collecting Data</a></li>
       <li><a href="#clustering"><span class="toc-section-number">3.2</span> Clustering</a></li>
       <li><a href="#visualization"><span class="toc-section-number">3.3</span> Visualization</a></li>
@@ -3978,6 +3978,7 @@ <h2><a href="#content">Supplemental materials - Transportation safety review</a>
       <li><a href="#logistic-regression"><span class="toc-section-number">4.1</span> Logistic regression</a></li>
       <li><a href="#poisson-regression"><span class="toc-section-number">4.2</span> Poisson regression</a></li>
       </ul></li>
+      <li><a href="#optimization"><span class="toc-section-number">5</span> Optimization</a></li>
       <li><a href="#acknowledgement">Acknowledgement</a></li>
       <li><a href="#references">References</a></li>
       </ul>
@@ -4041,15 +4042,15 @@ <h2><a href="#content">Supplemental materials - Transportation safety review</a>
   });
 });
 </script>
-<p>In this review paper, we attempt to provide a comprehensive review on transportation research and optimization models. This website serves as the supplementary materials to create reproducible examples in the manuscript <strong>Bridging the Gap between Transportation Safety Research and its Incorporation inOptimization Models: a Detailed Review and Perspective</strong>. It has been submitted to <em><a href="https://www.journals.elsevier.com/transportation-research-part-c-emerging-technologies">Transportation Research Part C: Emerging Technologies</a></em>.</p>
+<p>In this review paper, we attempt to provide a comprehensive review on transportation research and optimization models. This website serves as the supplementary materials to create reproducible examples in the manuscript <strong>Bridging the Gap between Transportation Safety Research and its Incorporation in Optimization Models: a Detailed Review and Perspective</strong>. It has been submitted to <em><a href="https://www.journals.elsevier.com/transportation-research-part-c-emerging-technologies">Transportation Research Part C: Emerging Technologies</a></em>.</p>
 <p>This vignette includes examples on the following five aspects:</p>
 <ol style="list-style-type: decimal">
 <li><strong>Bibliographic analysis</strong>: Bibliometric Summary for Transportation Safety, Bibliographic Network Matrices - Journal Names, keyword co-occurrences network, a Conceptual Structure Map</li>
 <li><strong>Extracting online transportation safety data</strong>: Crash-related data, traffic flow data, and weather data.</li>
 <li><strong>An example of clustering</strong></li>
 <li><strong>Statistical methods</strong>: logistic regression and Poisson regression</li>
 </ol>
-<p>To maximize the readability of this vignette, we hided all R codes by default, but readers can look into any code by clicking the <code>code</code> button.</p>
+<p>To maximize the readability of this website, we hided all R codes by default, but readers can look into any code by clicking the <code>code</code> button. The data folder is not uploaded to the GitHub repository since the files exceed the limited size, but all the data are open access and interested readers can download all the files at the link given in each section.</p>
 <div id="bibliographic-analysis" class="section level1 tabset tabset-fade">
 <h1><span class="header-section-number">1</span> Bibliographic analysis</h1>
 <hr />
@@ -4079,7 +4080,7 @@ <h2><span class="header-section-number">1.1</span> keyword co-occurrences</h2>
 </center>
 </div>
 <div id="a-conceptual-structure-map" class="section level2">
-<h2><span class="header-section-number">1.2</span> A conceptual Structure Map</h2>
+<h2><span class="header-section-number">1.2</span> A conceptual structure map</h2>
 <p>Creating a Conceptual Structure Map from the Titles Using the MCA Method with terms mentioned at least 25 times in the title</p>
 <div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" title="1">CS &lt;-<span class="st"> </span><span class="kw">conceptualStructure</span>(</a>
 <a class="sourceLine" id="cb3-2" title="2">  M,<span class="dt">field=</span><span class="st">&quot;ID_TM&quot;</span>, <span class="dt">method=</span><span class="st">&quot;MCA&quot;</span>, <span class="dt">minDegree=</span><span class="dv">20</span>, </a>
@@ -4319,8 +4320,8 @@ <h3><span class="header-section-number">2.3.2</span> Historical (daily)</h3>
 </div>
 </div>
 </div>
-<div id="an-example-of-clustering" class="section level1 tabset tabset-fade">
-<h1><span class="header-section-number">3</span> An example of clustering</h1>
+<div id="a-clustering-example" class="section level1 tabset tabset-fade">
+<h1><span class="header-section-number">3</span> A clustering example</h1>
 <hr />
 <p>The following codes attempts to replicate the visual clustering approach by <span class="citation">Van Wijk and Van Selow (<a href="#ref-van1999cluster">1999</a>)</span></p>
 <blockquote>
@@ -4507,9 +4508,13 @@ <h3>R code</h3>
 </div>
 </div>
 </div>
+<div id="optimization" class="section level1">
+<h1><span class="header-section-number">5</span> Optimization</h1>
+<p>Since optimization code is mostly Python-based, we do not provide code on the optimization section here. Should the readers have interest in this part, they can contact Qiong, Amir, and Alex.</p>
+</div>
 <div id="acknowledgement" class="section level1 unnumbered">
 <h1>Acknowledgement</h1>
-<p>We thank the National Science Foundation for supporting our research. We also thank the DarkSky API for providing us five million free calls to their weather database.</p>
+<p>This work was supported in part by the National Science Foundation (CMMI-1635927 and CMMI-1634992), the Ohio Supercomputer Center (PMIU0138 and PMIU0162), the American Society of Safety Professionals (ASSP) Foundation, the University of Cincinnati Education and Research Center Pilot Research Project Training Program, and the Transportation Informatics Tier I University Transportation Center (TransInfo). We also thank the DarkSky API for providing us five million free calls to their weather database.</p>
 </div>
 <div id="references" class="section level1 unnumbered">
 <h1>References</h1>