From 74a1548416d5c11cc0ee4c4d8d287225f2b1069b Mon Sep 17 00:00:00 2001 From: Mikhail-iontsev <92372420+Mikhail-iontsev@users.noreply.github.com> Date: Sun, 20 Oct 2024 16:52:46 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20OHDSI/Ar?= =?UTF-8?q?es@62c564165938dd18b078d24f44b1d757ffeabeef=20=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .nojekyll | 1 + 404.html | 43 ++++++++ _config.yml | 1 - ares-docs.html | 123 ++++++++++++++++++++++ ares_logo.svg | 56 ++++++++++ assets/404.html-B68jZ-pM.js | 1 + assets/app-BDaB3bYx.js | 42 ++++++++ assets/ares-docs.html-Dm1C8Ff4.js | 81 ++++++++++++++ assets/index.html-DVYBjc8E.js | 1 + assets/setupDevtools-7MC2TMWH-CshCj9Ex.js | 1 + assets/style-Cj22MYkn.css | 1 + icon.png | Bin 0 -> 20307 bytes index.html | 43 ++++++++ index.md | 15 --- 14 files changed, 393 insertions(+), 16 deletions(-) create mode 100644 .nojekyll create mode 100644 404.html delete mode 100644 _config.yml create mode 100644 ares-docs.html create mode 100644 ares_logo.svg create mode 100644 assets/404.html-B68jZ-pM.js create mode 100644 assets/app-BDaB3bYx.js create mode 100644 assets/ares-docs.html-Dm1C8Ff4.js create mode 100644 assets/index.html-DVYBjc8E.js create mode 100644 assets/setupDevtools-7MC2TMWH-CshCj9Ex.js create mode 100644 assets/style-Cj22MYkn.css create mode 100644 icon.png create mode 100644 index.html delete mode 100644 index.md diff --git a/.nojekyll b/.nojekyll new file mode 100644 index 00000000..8b137891 --- /dev/null +++ b/.nojekyll @@ -0,0 +1 @@ + diff --git a/404.html b/404.html new file mode 100644 index 00000000..ca21d007 --- /dev/null +++ b/404.html @@ -0,0 +1,43 @@ + + +
+ + + + + +ARES is A Research Exploration System designed for use in the study of patient level observational data that has been converted into the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). ARES was developed by Frank DeFalco, a member of the Observational Health Data Sciences & Informatics (OHDSI) community.
The Observational Health Data Sciences and Informatics (or OHDSI, pronounced "Odyssey") program is a multi-stakeholder, interdisciplinary collaborative to bring out the value of health data through large-scale analytics. All our solutions are open-source. Learn more about OHDSI.
Open the Ares releases page and download the latest available release (Ares.x.x-beta.zip), unpack the zip archive and serve using your favourite web server.
Here's an example running Ares using the "http-server" web server:
npm install -g http-server #download and install the http-server web server
+
+ http-server aresFolder #replace with the name of the folder containing Ares files
+
The link to the app will be available within the terminal once the http-server is launched.
Begin by downloading the source code for the ARES web application, which can be obtained by cloning the repository found on Github.
git clone https://github.com/ohdsi/ares
+
Once the repository is cloned locally the application can be built by using npm. These steps should be run from a bash shell or command prompt and are as follows:
cd aresDirectory #navigate to the directory Ares was cloned into
+ npm install #install Ares dependencies
+ npm run build -- --base=/ # Build the app. Replace "/" if you wish to run Ares within a subdirectory
+
The "--base" option is used to specify the base public path of the app. The default value is " /ares/" in case this option is not indicated.
The npm build process will create an output directory named "/dist" which will contain all files required for the ARES web application. These files should be placed in a directory that is served by any web server (like http-server), typically deployed in an "/ares" subdirectory (you can override that with the " --base" option as shown above.
The app could also be launched in dev mode and served by the built-in web server instantly. Run the following after cloning the repo and running "npm install"
npm run serve
+
Once the server is running, the app will be available at http://localhost:8080/ares (port 8080 is the default value and might be different if it's already being used by another app).
After completing the deployment of the web application the data files for ARES must be placed in the "/data" subfolder within the "/yourAresDirectory/public/" directory. The ARES data files are generated from your existing OMOP CDM database and require both Achilles and DataQualityDashboard.
Here's an example script to generate Ares files based on a sample dataset (replace connectionDetails to generate results for your database).
# DatabaseConnector::downloadJdbcDrivers("postgresql","D:/OHDSI/Drivers") - use it to download the JDBC driver
+options(connectionObserver = NULL)
+
+cdmDatabaseSchema = "main" #indicate the name of the cdm schema you created
+resultsDatabaseSchema = "main" #indicate the name of the results schema you created
+vocabDatabaseSchema = "main" #vocab should be located in the cdm schema
+numThreads = 1 #i only managed to get till the end in single-threaded mode, had problems utilizing 2 or more
+cdmSourceName = 'synthea'
+cdmVersion = "5.4" #do not change
+
+aresDataDirectory = "./data" #output directory
+sourceFolders = "./data" #source files folder for indexers.
+
+connectionDetails <- Eunomia::getEunomiaConnectionDetails() #Provides a sample dataset
+
+sourceReleaseKey = AresIndexer::getSourceReleaseKey(connectionDetails, cdmDatabaseSchema)
+
+
+# Example connection details
+#connectionDetails <- DatabaseConnector::createConnectionDetails(
+# dbms = dbms, #your database management system
+# server = server, #server address
+# user = user,
+# password = password,
+# pathToDriver = pathToDriver #location of the JDBC driver
+#)
+
+
+# Run Achilles
+Achilles::achilles(
+ connectionDetails,
+ cdmDatabaseSchema = cdmDatabaseSchema ,
+ resultsDatabaseSchema= resultsDatabaseSchema,
+ vocabDatabaseSchema = vocabDatabaseSchema,
+ numThreads = 1,
+ cdmVersion = "5.4.0",
+ createIndices = F,
+ createTable = T,
+ smallCellCount = 0,
+)
+# Export statistics generated by Achilles
+Achilles::exportToAres(
+ connectionDetails = connectionDetails,
+ cdmDatabaseSchema = cdmDatabaseSchema,
+ resultsDatabaseSchema = resultsDatabaseSchema,
+ vocabDatabaseSchema = vocabDatabaseSchema,
+ outputPath = sourceFolders,
+)
+
+datasourceReleaseOutputFolder <- file.path(aresDataDirectory, releaseKey)
+
+# Run Data Quality Dashboard
+DataQualityDashboard::executeDqChecks(
+ connectionDetails = connectionDetails,
+ cdmDatabaseSchema = cdmDatabaseSchema,
+ resultsDatabaseSchema = resultsDatabaseSchema,
+ vocabDatabaseSchema = vocabDatabaseSchema,
+ cdmSourceName = cdmSourceName,
+ numThreads = numThreads,
+ outputFolder = datasourceReleaseOutputFolder,
+ outputFile = "dq-result.json",
+ verboseMode = T,
+ writeToTable = F
+)
+
+
+list <- list.dirs(sourceFolders, recursive = FALSE)
+AresIndexer::augmentConceptFiles(sourceFolders = list)
+AresIndexer::buildExportQueryIndex(aresDataDirectory)
+AresIndexer::buildNetworkIndex(list, outputFolder = aresDataDirectory)
+AresIndexer::buildDataQualityIndex(list, outputFolder = aresDataDirectory)
+AresIndexer::buildNetworkUnmappedSourceCodeIndex(list, outputFolder = aresDataDirectory)
+
Visiting the ARES website will now show the data results for your current network. Each individual CDM needs to be processed in order for it to be available in ARES. CDM data sources with the same source name will be versioned using the release key allowing analysis across multiple versions of the same data source. An example of generating a complete network of different data sources and loading them into ARES can be found here.
Visualizations are used throughout ARES to assist in the interpretation of information. In this section sample visualizations are presented with descriptions to ensure they are well understood.
Visualization Techniques Cheat Sheet
Box-whisker diagrams present a simple picture representing the distribution of a set of data which include the values for the minimum, maximum, and quartiles of the distribution. They are also known as boxplots.
The roadmap for ARES is maintained on the GitHub repository.
ARES presents research generated through the suite of OHDSI related packages.
ARES leverages many open source libraries and tools to achieve its goals without which the task would be entirely insurmountable.
Many people have provided valuable feedback in the development of ARES.
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We believed that providing better visibility to the network of data sources available to a community would be beneficial and the pursuit of those objectives is the rationale for the development of ARES. - -Achilles and the Data Quality Dashboard provide data characterization and data quality assessment respectively. These tools had several limitations we saw the opportunity to improve upon. Specifically, while they provide adequate characterization of individual data sources, they lack any kind of overall network assessment across data sources. Additionally, these tools did not provide access to historical data once new releases of data sources were published, or any kind of integration between the characterization and data quality results. To address these limitations, we are developing in ARES and the AresIndexer projects a set of analyses that could better integrate the characterization and data quality work as well as provide ongoing access to data source changes over time. - - - - - -