Added DOI/citation info.

Author: mtaghiza

README.md

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+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10142770.svg)](https://doi.org/10.5281/zenodo.10142770)
+
+
 # [**SQLxMatch: In-Database Spatial Cross-Match of Astronomical Catalogs**](https://github.com/sciserver/SQLxMatch)
 
 ##### Manuchehr Taghizadeh-Popp <sup>1*</sup> and Laszlo Dobos<sup>1,2</sup>
@@ -28,6 +31,18 @@ Instructions on how to install and operate `SQLxMatch` can found under the [docs
 Example Jupyter Notebooks and demos can be found under [demo](https://github.com/sciserver/sqlxmatch/tree/main/demo) folder.
 
 
+## **Citation**
+
+Taghizadeh-Popp, M. and Dobos, L. (2023) “SQLxMatch: In-Database Spatial Cross-Match of Astronomical Catalogs”. Zenodo. doi: 10.5281/zenodo.10142771.
+
+
+
+
+
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10142770.svg)](https://doi.org/10.5281/zenodo.10142770)
+
 ## **License**
 
 All code and contents of this repository are licensed under the Apache 2.0 license. For more details see the [LICENSE.txt](https://github.com/sciserver/sqlxmatch/tree/main/LICENSE.txt) file.
+
+

demo/SQLxMatch_CasJobs_demo.ipynb

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     }
    },
    "source": [
+    "[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10142770.svg)](https://doi.org/10.5281/zenodo.10142770)\n",
     "# [**SQLxMatch: In-Database Spatial Cross-Match of Astronomical Catalogs**](https://github.com/sciserver/SQLxMatch)\n",
     "\n",
     "##### Manuchehr Taghizadeh-Popp <sup>1*</sup> and Laszlo Dobos<sup>1,2</sup>\n",
@@ -30,6 +31,12 @@
     "The advantage of this <i>`in-database`</i> remote cross-match, compared to other <i>`in-memory`</i> local cross-match software libraries, is that the users leverage the remote database server's own (and potentially bigger) computing/memory/storage resources to filter and cross-match the full catalogs right away, having only a relatively small-sized cross-match output table returned to them.\n",
     "This can be faster and more efficient than having users to download the full catalogs into their own computers (if they have enough storage), and then load them in python for filtering and running the cross-match, for instance.\n",
     "\n",
+    "#### **Citation**\n",
+    "\n",
+    "Taghizadeh-Popp, M. and Dobos, L. (2023) “SQLxMatch: In-Database Spatial Cross-Match of Astronomical Catalogs”. Zenodo. doi: 10.5281/zenodo.10142771.\n",
+    "\n",
+    "[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10142770.svg)](https://doi.org/10.5281/zenodo.10142770)\n",
+    "\n",
     "\n",
     "\n",
     "### The `SQLxMatch` stored procedure\n",

docs/README.md

@@ -1,3 +1,5 @@
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10142770.svg)](https://doi.org/10.5281/zenodo.10142770)
+
 # [**SQLxMatch: In-Database Spatial Cross-Match of Astronomical Catalogs**](https://github.com/sciserver/SQLxMatch)
 
 ##### Manuchehr Taghizadeh-Popp <sup>1*</sup> and Laszlo Dobos<sup>1,2</sup>
@@ -15,6 +17,12 @@ To improve cross-match query execution speed, we install `SQLxMatch` in a SQL Se
 The advantage of this <i>`in-database`</i> remote cross-match, compared to other <i>`in-memory`</i> local cross-match software libraries, is that the users leverage the remote database server's own (and potentially bigger) computing/memory/storage resources to filter and cross-match the full catalogs right away, having only a relatively small-sized cross-match output table returned to them.
 This can be faster and more efficient than having users to download the full catalogs into their own computers (if they have enough storage), and then load them in python for filtering and running the cross-match, for instance.
 
+**Citation**
+------------
+
+Taghizadeh-Popp, M. and Dobos, L. (2023) “SQLxMatch: In-Database Spatial Cross-Match of Astronomical Catalogs”. Zenodo. doi: 10.5281/zenodo.10142771.
+
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10142770.svg)](https://doi.org/10.5281/zenodo.10142770)
 
 
 **Installation**