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# Project Name: DataDash
# DataDash – Explore public APIs and datasets
[TOC]
## Description
DataDash is a simple product hunt like "Tool" for searching and discovering the newest Datasets and API's.
It provides the ability to Up-/ Down- vote entries, and to indicate the quality of a given Dataset/API by giving up to 5 starts.
DataDash is a simple Product Hunt-like "tool" for searching and discovering the newest datasets and APIs.
It provides the ability to up-/downvote entries, and to indicate the quality of a given dataset/API by rating it on a scale of 0 to 5 stars.
## Installation
### On Linux and Mac
To install DataDash, follow these steps:
1. Clone the repository:
#### 1. Clone the repository:
```bash
git clone https://github.com/your-username/DataDash.git
$ git clone https://git.fim.uni-passau.de/padas/24ss-5430-web-and-data-eng/gruppe-3/datadash.git
```
2. Enter the repo
#### 2. Enter the repo:
```bash
cd datadash
$ cd datadash
```
3. Install Java 22-jdk:
Please refer to the Installation instructions for your os
4. Start the application:
```
./mvnw spring-boot:run
```
additional requirements will be downloaded by and managed maven.
#### Deployment
1. Clone the repository:
#### 3. Install Java JDK 22: Please refer to the installation instructions for your package manager/OS.
#### 4. Start the application:
```bash
git clone https://github.com/your-username/DataDash.git
$ ./mvnw spring-boot:run
```
2. Enter the repo
Additional dependencies will be downloaded and managed by maven.
```
cd datadash
```
## Deployment
### 1. Follow [installation steps 1-3](#installation).
3. Remove sample data(Optional)
remove the ```src/main/resources/data.sql``` to remove the sample data.
*Note:* This will also remove all default Categories.
### 2. _(Optional)_ Remove sample data:
Remove [`src/main/resources/data.sql`](src/main/resources/data.sql) to remove the sample data.
4. Install Java 22-jdk:
Please refer to the Installation instructions for your os
5. Start the application:
> **Note:** This will also remove all default categories.
### 3. Package the application:
```bash
./mvnw package
$ ./mvnw package
```
this will create the ```.war``` file that you can deploy as you like
This will create the `.war` file that you can deploy as you like.
## Usage
1. Open your web browser and navigate to `http://localhost:8080`.
2. Some dummy data will be shown.
3. add your own Datasets and API's with via the add button in the top left corner
4. you can Search for datasets or browse by selecting how the entries shall be sorted under the ```⥮``` menu. You can also filter for Categories or type( e.g.Category or API)
5. For mor information on a certain dataset just click on it
1. You can differentiate between API and Dataset via the blue box.
2. The quality of is indicated by the stars on the lefthandside just below the title.
3. You can also vote, just by hovering and clicking on the stars.
4. To the left of the stars the summary is displayed
5. Below the stars the the source of the Dataset/API is linked
6. In the Next section some Stats regarding the date of submission, Category, License and the Terms of use are shown
7. Next you can see A longer description.
8. At the very bottom of the Page there is the button that will bring you back to the homepage. If you want to go back to the Previous page (e.g. Search) you might want to use the back button of your browser.
9. If you created the entry that you are looking at you will find that next to the ```back to main page``` button you will find a ```Delete``` button. This will delete the entry without asking asking if you are sure.
2. Some **dummy data** will be shown (if configured, see [deployment step 2](#2-optional-remove-sample-data)).
3. Add your own datasets and APIs via the **add button** in the top left corner.
4. In the top right you can see the **search toolbar**. Here you can **sort**, input **search terms**, and **filter by categories or type of content** (i.e. dataset or API).
5. For **more information** on a certain dataset just click on it
1. You can differentiate between **API** and **dataset** via the **blue box**.
2. The **user perceived quality** is indicated by the **number and stars** on the left hand side just below the title.
3. You can also **vote** by just **hovering** and then **clicking on the stars**.
4. Right next to the stars the **summary** is displayed. It's a short text describing the main purpose.
5. Below the star rating and summary the **dataset's/API's source** is linked
6. In the next section some metadata regarding the **date of submission**, **category**, **license** and a link to the **Terms of Use** are shown.
7. Next you can see a **full description**.
8. At the very bottom of the page there is a button that will bring you **back to the homepage**. If you want to go back to the **previous page** (e.g. search) you might want to use **your browser's back button**.
9. If you created the entry that you are currently looking at, you will find a **`Delete`** button next to the `Back to main page` button. This will **delete** the entry **without any further confirmation**.
## Used Frameworks/Libraries
### Frontend
None, our whole frontend is written in **native HTML, CSS, and JavaScript**.
None, our whole frontend is written in native javaScript, HTML and CSS.
It has been tested on **Firefox 127** and **Chromium 126**.
## Backend
- spring-boot-starter-web
- springdoc-openapi-starter-webmvc-ui<
- spring-boot-starter-tomcat
- spring-boot-starter-test
- com.h2database
### Backend
We have used the following dependencies:
- `spring-boot-starter-web`
- `springdoc-openapi-starter-webmvc-ui`
- `spring-boot-starter-tomcat`
- `spring-boot-starter-test`
- `com.h2database`