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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta content="width=device-width, initial-scale=1.0" name="viewport">
<title>Blessed Be the Fruit</title>
<meta content="" name="description">
<meta content="" name="keywords">
<!-- Favicons -->
<link href="assets/img/pomegranate2.png" rel="icon">
<!-- Google Fonts -->
<link
href="https://fonts.googleapis.com/css?family=Open+Sans:300,300i,400,400i,600,600i,700,700i|Raleway:300,300i,400,400i,500,500i,600,600i,700,700i|Poppins:300,300i,400,400i,500,500i,600,600i,700,700i"
rel="stylesheet">
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<!-- Template Main CSS File -->
<link href="assets/css/style.css" rel="stylesheet">
<!-- Import jQuery -->
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.6.1/jquery.min.js"></script>
<!-- VISUALISATIONS -->
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<script src="https://cdn.amcharts.com/lib/5/index.js"></script>
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<!-- =======================================================
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</head>
<body>
<!-- ======= Header ======= -->
<header id="header" class="fixed-top d-flex align-items-center">
<div class="container d-flex align-items-center justify-content-between">
<div class="logo">
<h1><a href="index.html">bbf</a></h1>
</div>
<nav id="navbar" class="navbar">
<ul>
<li><a class="nav-link scrollto active" href="#hero">Home</a></li>
<li><a class="nav-link scrollto" href="#about">About</a></li>
<li><a class="nav-link scrollto" href="#results">Results</a></li>
<li><a class="nav-link scrollto" href="#datasets">Datasets</a></li>
<li class="dropdown"><a href=""><span>Documentation</span><i class="bi bi-chevron-down"></i></a>
<ul>
<li><a class="nav-link scrollto" href="#analyses">Analyses</a></li>
<li><a class="nav-link scrollto" href="#viz">Visualizations</a></li>
<li><a class="nav-link scrollto" href="#sustain">Sustainability</a></li>
</ul>
</li>
<li><a class="nav-link scrollto" href="#team">Team</a></li>
<li><a class="nav-link scrollto" href="#license">License</a></li>
</ul>
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</nav><!-- .navbar -->
</div>
</header><!-- End Header -->
<!-- ======= Hero Section ======= -->
<section id="hero" class="d-flex align-items-center">
<div class="container">
<div class="row">
<div class="col-lg-6 pt-5 pt-lg-0 order-2 order-lg-1 d-flex flex-column justify-content-center">
<h1 data-aos="fade-up">blessed be the fruit</h1>
<h2 data-aos="fade-up" data-aos-delay="400">Is there any observable pattern indicating a correlation between
<span class="underlined underlined--offset">religious observance</span>, <span
class="underlined underlined--offset">pregnancy rates</span> and <span
class="underlined underlined--offset">education level</span> in young women throughout Italy?
</h2>
<div data-aos="fade-up" data-aos-delay="800">
<a href="#about" class="btn-get-started scrollto">Find out!</a>
</div>
</div>
<div class="col-lg-6 order-1 order-lg-2 hero-img" data-aos="fade-left" data-aos-delay="200">
<img src="assets/img/pmgfull.png" class="img-fluid animated" alt="">
</div>
</div>
</div>
</section><!-- End Hero -->
<main id="main">
<!-- ======= About Us Section ======= -->
<section id="about" class="about">
<div class="container">
<div class="section-title" data-aos="fade-up">
<h2>About the project</h2>
</div>
<div class="row content">
<div class="col-lg-6" data-aos="fade-up" data-aos-delay="150">
<p>
"Blessed be the fruit" is an <span class="underlined underlined--offset"><b>open data
project</b></span> regarding the analysis of factors that might influence pregnancy rates in young
women in Italy.<br>
Specifically, we have decided to approach this topic by laying down a few fundamental features:
</p>
<ul>
<li><i class="ri-check-double-line"></i><b>Year span</b>: 2017-2019, in order to gather the most frequent
data not yet affected by the COVID-19 pandemic</li>
<li><i class="ri-check-double-line"></i><b>Gender</b>: female, as source datasets do not go beyond the
binary definition of gender, discarding queer identities
</li>
<li><i class="ri-check-double-line"></i><b>Age range</b>: 15-25</li>
<li><i class="ri-check-double-line"></i><b>Factors of interest</b>: religious observance and education
</li>
</ul>
</div>
<div class="col-lg-6 pt-4 pt-lg-0" data-aos="fade-up" data-aos-delay="300">
<p>
The project, other than answering to the research question, also encompasses <span
class="underlined underlined--offset"><b>in-depth analyses</b></span> of different aspects of open data
regarding quality, legalty, ethics and technicalities.
</p>
<p>
Different <span class="underlined underlined--offset"><b>visualizations</b></span> are possible,
supporting the communication and ensuring a better understanding of the results.<br>
</p>
<p>
<a href="documentation/DOCUMENTATION.ipynb"
style="vertical-align: middle;" download><span class="material-symbols-outlined">download</span></a>
Finally, a <b>full detailed documentation</b> is freely downloadable by the user.<br>
</p>
<hr>
<h6><i>RQ: Is there any observable pattern indicating a correlation between religious observance, pregnancy
rates and education level in young women throughout Italy?</i></h6>
<a href="#results" class="btn-learn-more scrollto">Find out the results!</a>
</div>
</div>
</div>
</section><!-- End About Us Section -->
<!-- ======= Counts Section ======= -->
<section id="counts" class="counts">
<div class="container">
<div class="row">
<div class="image col-xl-3 d-flex align-items-stretch justify-content-center justify-content-xl-start"
data-aos="fade-right" data-aos-delay="150">
<img src="assets/img/pmgfront_new.png" alt="" class="img-fluid pmgfront">
</div>
<div class="col-xl-9 d-flex align-items-stretch pt-4 pt-xl-0" data-aos="fade-left" data-aos-delay="300">
<div class="content d-flex flex-column justify-content-center">
<div class="row">
<div class="col-md-6 d-md-flex align-items-md-stretch">
<div class="count-box">
<i class="bi bi-file-earmark-bar-graph"></i>
<span data-purecounter-start="0" data-purecounter-end="16" data-purecounter-duration="1.3"
class="purecounter"></span>
<p><strong>Datasets</strong>, between source ones and mashup ones, used to answer the research
question</p>
</div>
</div>
<div class="col-md-6 d-md-flex align-items-md-stretch">
<div class="count-box">
<i class="bi bi-people-fill"></i>
<span data-purecounter-start="0" data-purecounter-end="327236" data-purecounter-duration="1.3"
class="purecounter"></span>
<p><strong>Pregnancies</strong> in the female population aged 15-25 during the year span 2017-2019
in Italy
</p>
</div>
</div>
<div class="col-md-6 d-md-flex align-items-md-stretch">
<div class="count-box">
<i class="bi bi-brightness-alt-high-fill"></i>
<span data-purecounter-start="0" data-purecounter-end="43853" data-purecounter-duration="1.3"
class="purecounter"></span>
<p>Thousands <strong>religion followers</strong> in the year span 2017-2019 in Italy</p>
</div>
</div>
<div class="col-md-6 d-md-flex align-items-md-stretch">
<div class="count-box">
<i class="bi bi-mortarboard-fill"></i>
<span data-purecounter-start="0" data-purecounter-end="6322" data-purecounter-duration="1.3"
class="purecounter"></span>
<p><strong>Early leavers from higher education</strong> in the female population aged 18-24 during
the year span 2017-2019 in Italy</p>
</div>
</div>
</div>
</div><!-- End .content-->
</div>
</div>
</div>
</section><!-- End Counts Section -->
<!-- ======= Results Section ======= -->
<section id="results" class="about">
<div class="container">
<div class="section-title" data-aos="fade-up">
<h2>Results</h2>
<p><span class="underlined underlined--offset"><b>Click on a year to find out the specific results!</b></span>
</p>
</div>
<div class="row" data-aos="fade-up" data-aos-delay="200">
<div class="col-lg-12 d-flex justify-content-center">
<ul id="results-buttons">
<li class="map-li" type="button" data-bs-toggle="collapse" data-bs-target="#first_year"
aria-expanded="false">
2017
</li>
<li class="map-li" type="button" data-bs-toggle="collapse" data-bs-target="#second_year"
aria-expanded="false">
2018
</li>
<li class="map-li" type="button" data-bs-toggle="collapse" data-bs-target="#third_year"
aria-expanded="false">
2019
</li>
</ul>
</div>
</div>
<!-- 2017 -->
<div class="container collapse analysis-card" id="first_year" data-bs-parent="#results">
<div class="align-items-stretch mb-5 mb-lg-0">
<div class="analysis-box">
<div class="analysis-box-title">
<h4 class="year-result-text">Results for year 2017</h4>
</div>
<!-- Factors division -->
<div class="row justify-content-center">
<div class="col-md-4 text-center">
<p class="factor-text">Religious observance rates</p>
<p>Highest rate: Puglia 32.9%<br>
Lowest rate: Liguria 16.3%
</p>
</div>
<div class="col-md-4 text-center">
<p class="factor-text">Pregnancy rates</p>
<p> Highest rate: Sicilia 4.8%<br>
Lowest rate: Basilicata 2.5%
</p>
</div>
<div class="col-md-4 text-center">
<p class="factor-text">Education leavers rates</p>
<p>Highest rate: Campania 9.1%<br>
Lowest rate: Marche 2.6%
</p>
</div>
</div>
<!-- Maps -->
<div class="row justify-content-center" id="map-container">
<div class="col-md-4">
<div class="map" id="map_17_rel"></div>
</div>
<div class="col-md-4">
<div class="map" id="map_17_preg"></div>
</div>
<div class="col-md-4">
<div class="map" id="map_17_edu"></div>
</div>
</div>
<!-- Bar chart -->
<br>
<div class="text-center">
<p class="factor-text" style="padding-top:2em; margin-bottom:0;">Bar chart</p>
</div>
<div class="row justify-content-center">
<div class="col-md-10">
<div class="bar-graph" id="bar-graph-17"></div>
</div>
</div>
</div>
</div>
</div>
<!-- 2018 -->
<div class="container collapse analysis-card" id="second_year" data-bs-parent="#results">
<div class="align-items-stretch mb-5 mb-lg-0">
<div class="analysis-box">
<div class="analysis-box-title">
<h4 class="year-result-text">Results for year 2018</h4>
</div>
<!-- Factors division -->
<div class="row justify-content-center">
<div class="col-md-4 text-center">
<p class="factor-text">Religious observance rates</p>
<p>Highest rate: Calabria 15.7%<br>
Lowest rate: Sardegna 2.8%
</p>
</div>
<div class="col-md-4 text-center">
<p class="factor-text">Pregnancy rates</p>
<p>Highest rate: Sicilia 2.4%<br>
Lowest rate: Marche 0.4%
</p>
</div>
<div class="col-md-4 text-center">
<p class="factor-text">Education leavers rates</p>
<p>Highest rate: Sicilia 10.6%<br>
Lowest rate: Marche / Friuli-Venezia Giulia 3.5%
</p>
</div>
</div>
<!-- Maps -->
<div class="row justify-content-center" id="map-container">
<div class="col-md-4">
<div class="map" id="map_18_rel"></div>
</div>
<div class="col-md-4">
<div class="map" id="map_18_preg"></div>
</div>
<div class="col-md-4">
<div class="map" id="map_18_edu"></div>
</div>
</div>
<!-- Bar chart -->
<br>
<div class="text-center">
<p class="factor-text" style="padding-top:2em; margin-bottom:0;">Bar chart</p>
</div>
<div class="row justify-content-center">
<div class="col-md-10">
<div class="bar-graph" id="bar-graph-18"></div>
</div>
</div>
</div>
</div>
</div>
<!-- 2019 -->
<div class="container collapse analysis-card" id="third_year" data-bs-parent="#results">
<div class="align-items-stretch mb-5 mb-lg-0">
<div class="analysis-box">
<div class="analysis-box-title">
<h4 class="year-result-text">Results for year 2019</h4>
</div>
<!-- Factors division -->
<div class="row justify-content-center">
<div class="col-md-4 text-center">
<p class="factor-text">Religious observance rates</p>
<p>Highest rate: Campania 15.8%<br>
Lowest rate: Liguria 7.9%
</p>
</div>
<div class="col-md-4 text-center">
<p class="factor-text">Pregnancy rates</p>
<p>Highest rate: Sicilia 2.5%<br>
Lowest rate: Basilicata 1.3%
</p>
</div>
<div class="col-md-4 text-center">
<p class="factor-text">Education leavers rates</p>
<p>Highest rate: Sicilia 10.3%<br>
Lowest rate: Abruzzo 2.1%
</p>
</div>
</div>
<!-- Maps -->
<div class="row justify-content-center" id="map-container">
<div class="col-md-4">
<div class="map" id="map_19_rel"></div>
</div>
<div class="col-md-4">
<div class="map" id="map_19_preg"></div>
</div>
<div class="col-md-4">
<div class="map" id="map_19_edu"></div>
</div>
</div>
<!-- Bar chart -->
<br>
<div class="text-center">
<p class="factor-text" style="padding-top:2em; margin-bottom:0;">Bar chart</p>
</div>
<div class="row justify-content-center">
<div class="col-md-10">
<div class="bar-graph" id="bar-graph-19"></div>
</div>
</div>
</div>
</div>
</div>
<!-- Conclusions -->
<div class="row content">
<div class="pt-4 pt-lg-0" data-aos="fade-up" data-aos-delay="150" style="padding-bottom: 1em;">
<p class="analysis-text">
<b>Our main visualizations</b>:
</p>
<h5><span class="underlined underlined--offset"><b>choropleth maps</b></span></h5>
<p class="analysis-text">
We decided to provide choropleth maps as they were the best option to visualize individually the variation
of our data over our geographical area of interest,
as well as to visually highlight similarities in our variables trends.<br>
Please note that:
<ul>
<li><b>Religious observance percentage rates</b> are calculated over the general population without
distinction in gender or age class</li>
<li><b>Pregnancy percentage rates</b> are calculated over a sample population of women belonging to an age
class of 15-24</li>
<li><b>Education leavers percentage rates</b> are caluculated over a sample population of women belonging
to an age class of 18-24</li>
</ul>
Overall, these maps allow us to observe a general trend common to our three variables, whose rate tend to
increase in southern regions and islands.
Nonetheless, there are too many regional specificities and exceptions in values' similarities throughout the
years and <span class="underlined underlined--offset"><b>this prevent us to affirm any strong correlation
between variables</b></span>, let alone any possible causality between them.
</p>
<h5><span class="underlined underlined--offset"><b>bar chart</b></span></h5>
<p class="analysis-text">
The bar chart visualization was included as well, since it offers us an <b>immediate and clear
comparison</b> between values of each of our variables.
</p>
</div>
<div class="pt-4 pt-lg-0" data-aos="fade-up" data-aos-delay="300">
<h5><span class="underlined underlined--offset"><b>conclusions</b></span></h5>
<p class="analysis-text">
For a further evaluation of our analysis, we can likely state that <b>we don't have enough data to know if
a variable </b> - and in that case which one - <b>causes the other</b>.
</p>
<blockquote>
For
example, we could hypothesize that the early leavers rate is indeed affected by the early pregnancy rates,
since being pregnant could be a reason for a young woman to choose to leave education or training. To affirm this, however,
we would need to look into <b>other possible correlated factors</b>, such as <b>poverty rates</b>, to make
sure they are not strongly affecting our data.
</blockquote>
<blockquote>
For the same reason, we can't possibly infer causality between religious rates and our other variables:
even though they do seem to vary together, there's no mean for us to tell whether religiosity is
the reason one is inclined to leave education and start a family early in life,
or whether, after this happens, people are inclined to move their sociality from educational contests to
religious contests.
Just to give some examples of possible reasons of
correlation.<br>
Furthermore, to properly assess the connection between religiosity and pregnancies, with specific
differentiation amongst induced abortions and live births, for instance, we would need much more data
about how religiosity affects women's <b>access to Voluntary Termination of Pregnancy</b> (VTP, in
Italian "Interruzione Volontaria di Gravidanza", IVG) in the first place.
As we know, Italy has a very <a
href="https://it.wikipedia.org/wiki/Obiezione_di_coscienza_in_Italia#Obiezione_nell'ambito_dell'interruzione_volontaria_di_gravidanza_(IVG)"
target="_blank">high rate of coscientious objectors</a>
(in 2012: 69,6% of gynecologists, 47,5% of anesthetists and 45% of non medical staff [<a
href="https://www.salute.gov.it/imgs/C_17_pubblicazioni_2226_allegato.pdf" target="_blank">source</a>]).
<br>
This could significantly affect the pregnancy
rates per region, as they have been counted including <b>abortions in the place where they happen</b> and
not
according to the woman's residency. It goes without saying, if a region prevents
a woman to access VTP they might be likely to migrate to other region, hence, this phenomenon might also
have affected our data.
Unfortunately, there are very <b>few and non-institutional data about the phenomenon</b> and this prevented
us to futherly investigate the degree of its impact on our study.
</blockquote>
<p class="analysis-text" style="padding-top:1em;">
Finally, to highlight other features related to our variables and illustrate trends and other interesting
information, you can have a look at our in the <a href="#viz"><b>"Additional Visualizations"
section</b></a>. There, we provided:
<ul>
<li><span class="underlined underlined--offset"><b>bubble charts</b></span> for every year to investigate
and better visualize how much our variables are correlated together,</li>
<li><span class="underlined underlined--offset"><b>pie charts</b></span> for pregnancies data, in order to
better understand the rates of the different outcomes of pregnancies,</li>
<li><span class="underlined underlined--offset"><b>time series</b></span> for each reason, in order to
better investigate how our values changed over the three year span we analyzed.</li>
</ul>
</p>
</div>
</div>
</section><!-- End Results Section -->
<!-- ======= Datasets Section ======= -->
<section id="datasets" class="portfolio datasets">
<div class="container">
<div class="section-title" data-aos="fade-up">
<h2>Source and mashup datasets</h2>
</div>
<div class="row content">
<div class="col-lg-6" data-aos="fade-up" data-aos-delay="150">
<p>
As mentioned, our project comprises the use of <b>16 different datasets</b>, between source ones and
mashup ones.
</p>
<p>
The <b>7 source datasets</b> have been downloaded in .csv
format from different databases belonging to Istat, the
Italian National Institute of Statistics. Specifically, we have used three different databases:
<ul>
<li><i class="ri-check-double-line"></i><b><a href="https://demo.istat.it/?l=en" target="_blank">demo:
demographics in
figures</a></b>: on resident population in the Italian municipalities and information on main
demographic phenomena</li>
<li><i class="ri-check-double-line"></i><b><a href="http://dati.istat.it/?lang=en"
target="_blank">I.Stat</a></b>: a
datawarehouse organised by theme, presented in multidimensional tables and with a wide range of standard
metadata</li>
<li><i class="ri-check-double-line"></i><b><a href="https://esploradati.istat.it/databrowser/#/en"
target="_blank">IstatData</a></b>: the new database into which
all
I.Stat content will be gradually migrated</li>
</ul>
To make our project as accessible as possible even in the future, we have preferred
IstatData over I.Stat when doable.
</p>
</div>
<div class="col-lg-6 pt-4 pt-lg-0" data-aos="fade-up" data-aos-delay="300">
<p>
During the <span class="underlined underlined--offset"><b>download phase</b></span>, we have manually
filtered out everything that was not of interest for our
research, keeping only the data strictly related to our research question (we have, for example, discarded
any information related to marital status in the datasets regarding population).
</p>
<p>
Still, the source datasets went through an additional <span class="underlined underlined--offset"><b>clean
up phase</b></span> in which we discarded duplicate (e.g.,
columns with different names and values but referring to the same information) and irrelevant data and,
when
necessary, added missing "coded data" to allow for an easier management of the datasets.
</p>
<p>
Finally, we proceeded with the <span class="underlined underlined--offset"><b>mashup phase</b></span>,
creating the final three main mashup datasets used to answer our
research question. As with source and clean datasets, we distinguished between the
three years of our time span of interest: in this way, we ended up with <b>9 final mashup datasets</b>
(three for
each
factor of interest).<br>
</p>
<p>
The code for the clean up and mashup phases can be found in the appropriate documentation, freely
downloadable.
</p>
</div>
</div>
<div class="row" data-aos="fade-up" data-aos-delay="200">
<div class="col-lg-12 d-flex justify-content-center">
<ul id="portfolio-flters">
<li data-filter="*" class="filter-active">All</li>
<li data-filter=".source-dataset">Source datasets</li>
<li data-filter=".mashup-dataset">Mashup datasets</li>
</ul>
</div>
</div>
<!-- Here the datasets -->
<div class="row portfolio-container" data-aos="fade-up" data-aos-delay="300">
<div class="col-lg-3 col-md-4 portfolio-item source-dataset">
<div class="icon-box">
<div class="dataset-title">
<i class="bi bi-file-earmark" style="color: #557c70;"></i>
<h3>D1 - Population 2017</h3>
</div>
<p style="border-top: #557c70 solid 1px;">
<b>ID</b>: D1<br>
<b>Provenience</b>: <a href="https://demo.istat.it/?l=en" target="_blank">demo</a><br>
<b>Format</b>: .csv, .xlsx, .pdf<br>
<b>Metadata</b>: Not provided<br>
<b>URI</b>: <a href="https://demo.istat.it/app/?i=RIC&l=en" target="_blank">2017Population</a><br>
<b>License</b>: CC BY 3.0<br>
</p>
</div>
</div>
<div class="col-lg-3 col-md-4 portfolio-item source-dataset">
<div class="icon-box">
<div class="dataset-title">
<i class="bi bi-file-earmark" style="color: #557c70;"></i>
<h3>D2 - Population 2018, 2019</h3>
</div>
<p style="border-top: #557c70 solid 1px;">
<b>ID</b>: D2<br>
<b>Provenience</b>: <a href="https://demo.istat.it/?l=en" target="_blank">demo</a><br>
<b>Format</b>: .csv, .xlsx, .pdf<br>
<b>Metadata</b>: Not provided<br>
<b>URI</b>: <a href="https://demo.istat.it/app/?i=POS&l=en" target="_blank">201819Population</a><br>
<b>License</b>: CC BY 3.0<br>
</p>
</div>
</div>
<div class="col-lg-3 col-md-4 portfolio-item source-dataset">
<div class="icon-box">
<div class="dataset-title">
<i class="bi bi-file-earmark" style="color: #557c70;"></i>
<h3>D3 - Religious observance</h3>
</div>
<p style="border-top: #557c70 solid 1px;">
<b>ID</b>: D3<br>
<b>Provenience</b>: <a href="http://dati.istat.it/?lang=en" target="_blank">I.Stat</a><br>
<b>Format</b>: .csv, .xlsx, .px, .xml <br>
<b>Metadata</b>: <a href="https://siqual.istat.it/SIQual/sintesi.do?id=0058000"
target="_blank">Provided</a><br>
<b>URI</b>: <a href="http://dati.istat.it/index.aspx?queryid=24349"
target="_blank">ReligiousObservance</a><br>
<b>License</b>: CC BY 3.0<br>
</p>
</div>
</div>
<div class="col-lg-3 col-md-4 portfolio-item source-dataset">
<div class="icon-box">
<div class="dataset-title">
<i class="bi bi-file-earmark" style="color: #557c70;"></i>
<h3>D4 - Live births</h3>
</div>
<p style="border-top: #557c70 solid 1px;">
<b>ID</b>: D4<br>
<b>Provenience</b>: <a href="https://esploradati.istat.it/databrowser/#/"
target="_blank">IstatData</a><br>
<b>Format</b>: .json, .xml, .xlsx, .csv<br>
<b>Metadata</b>: Provided<br>
<b>URI</b>: <a
href="https://esploradati.istat.it/databrowser/#/en/dw/categories/IT1,POP,1.0/POP_BIRTHFERT/DCIS_NATI1/DCIS_NATI1_PARENT_CHARACT/IT1,25_74_DF_DCIS_NATI1_8,1.0"
target="_blank">LiveBirths</a><br>
<b>License</b>: CC BY 3.0<br>
</p>
</div>
</div>
<div class="col-lg-3 col-md-4 portfolio-item source-dataset">
<div class="icon-box">
<div class="dataset-title">
<i class="bi bi-file-earmark" style="color: #557c70;"></i>
<h3>D5 - Spontaneous abortions</h3>
</div>
<p style="border-top: #557c70 solid 1px;">
<b>ID</b>: D5<br>
<b>Provenience</b>: <a href="http://dati.istat.it/?lang=en" target="_blank">I.Stat</a><br>
<b>Format</b>: .csv, .xlsx, .px, .xml <br>
<b>Metadata</b>: <a href="https://siqual.istat.it/SIQual/sintesi.do?id=5000132"
target="_blank">Provided</a><br>
<b>URI</b>: <a href="http://dati.istat.it/index.aspx?queryid=29218"
target="_blank">SpontAbortions</a><br>
<b>License</b>: CC BY 3.0<br>
</p>
</div>
</div>
<div class="col-lg-3 col-md-4 portfolio-item source-dataset">
<div class="icon-box">
<div class="dataset-title">
<i class="bi bi-file-earmark" style="color: #557c70;"></i>
<h3>D6 - Induced abortions</h3>
</div>
<p style="border-top: #557c70 solid 1px;">
<b>ID</b>: D6<br>
<b>Provenience</b>: <a href="http://dati.istat.it/?lang=en" target="_blank">I.Stat</a><br>
<b>Format</b>: .csv, .xlsx, .px, .xml <br>
<b>Metadata</b>: <a href="https://siqual.istat.it/SIQual/visualizza.do?id=0038900"
target="_blank">Provided</a><br>
<b>URI</b>: <a href="http://dati.istat.it/index.aspx?queryid=7098"
target="_blank">InducedAbortions</a><br>
<b>License</b>: CC BY 3.0<br>
</p>
</div>
</div>
<div class="col-lg-3 col-md-4 portfolio-item source-dataset">
<div class="icon-box">
<div class="dataset-title">
<i class="bi bi-file-earmark" style="color: #557c70;"></i>
<h3>D7 - Early leavers from education</h3>
</div>
<p style="border-top: #557c70 solid 1px;">
<b>ID</b>: D7<br>
<b>Provenience</b>: <a href="http://dati.istat.it/?lang=en" target="_blank">I.Stat</a><br>
<b>Format</b>: .csv, .xlsx, .px, .xml <br>
<b>Metadata</b>: <a
href="https://siqual.istat.it/SIQual/visualizza.do?id=5000098&refresh=true&language=EN"
target="_blank">Provided</a><br>
<b>URI</b>: <a href="http://dati.istat.it/Index.aspx?DataSetCode=DCCV_ESL_UNT2020"
target="_blank">EarlyLeavers</a><br>
<b>License</b>: CC BY 3.0<br>
</p>
</div>
</div>
<div class="col-lg-3 col-md-4 portfolio-item mashup-dataset">
<div class="icon-box">
<div class="dataset-title">
<i class="bi bi-database" style="color: #b74d3a;"></i>
<h3>MD1 - General religious observance in each region</h3>
</div>
<p style="border-top: #b74d3a solid 1px;">
<b>ID</b>: MD1<br>
<b>Creation date</b>: 15 January 2023<br>
<b>Format</b>: .csv<br>
<b>Metadata</b>: Provided<br>
<b>URI</b>: <a href="https://github.com/OrsolaMBorrini/blessedfruit/blob/main/data/mashupDS/MD1_17.csv"
target="_blank">MD1_17</a>,
<a href="https://github.com/OrsolaMBorrini/blessedfruit/blob/main/data/mashupDS/MD1_18.csv"
target="_blank">MD1_18</a>,
<a href="https://github.com/OrsolaMBorrini/blessedfruit/blob/main/data/mashupDS/MD1_19.csv"
target="_blank">MD1_19</a><br>
<b>License</b>: CC BY 4.O<br>
<b>Download</b>:
<a href="data/mashupDS/MD1_17.csv" download>MD1_17</a>,
<a href="data/mashupDS/MD1_18.csv" download>MD1_18</a>,
<a href="data/mashupDS/MD1_19.csv" download>MD1_19</a>
</p>
</div>
</div>
<div class="col-lg-3 col-md-4 portfolio-item mashup-dataset">
<div class="icon-box">
<div class="dataset-title">
<i class="bi bi-database" style="color: #b74d3a;"></i>
<h3>MD2 - Pregnancy rates in young women</h3>
</div>
<p style="border-top: #b74d3a solid 1px;">
<b>ID</b>: MD2<br>
<b>Creation date</b>: 16 January 2023<br>
<b>Format</b>: .csv<br>
<b>Metadata</b>: Provided<br>
<b>URI</b>: <a href="https://github.com/OrsolaMBorrini/blessedfruit/blob/main/data/mashupDS/MD2_17.csv"
target="_blank">MD2_17</a>,
<a href="https://github.com/OrsolaMBorrini/blessedfruit/blob/main/data/mashupDS/MD2_18.csv"
target="_blank">MD2_18</a>,
<a href="https://github.com/OrsolaMBorrini/blessedfruit/blob/main/data/mashupDS/MD2_19.csv"
target="_blank">MD2_19</a><br>
<b>License</b>: CC BY 4.0<br>
<b>Download:</b>
<a href="data/mashupDS/MD2_17.csv" download>MD2_17</a>,
<a href="data/mashupDS/MD2_18.csv" download>MD2_18</a>,
<a href="data/mashupDS/MD2_19.csv" download>MD2_19</a>
</p>
</div>
</div>
<div class="col-lg-3 col-md-4 portfolio-item mashup-dataset">
<div class="icon-box">
<div class="dataset-title">
<i class="bi bi-database" style="color: #b74d3a;"></i>
<h3>MD3 - Education leavers' rates in young women</h3>
</div>
<p style="border-top: #b74d3a solid 1px;">
<b>ID</b>: MD3<br>
<b>Creation date</b>: 15 January 2023<br>
<b>Format</b>: .csv<br>
<b>Metadata</b>: Provided<br>
<b>URI</b>: <a href="https://github.com/OrsolaMBorrini/blessedfruit/blob/main/data/mashupDS/MD3_17.csv"
target="_blank">MD3_17</a>,
<a href="https://github.com/OrsolaMBorrini/blessedfruit/blob/main/data/mashupDS/MD3_18.csv"
target="_blank">MD3_18</a>,
<a href="https://github.com/OrsolaMBorrini/blessedfruit/blob/main/data/mashupDS/MD3_19.csv"
target="_blank">MD3_19</a><br>
<b>License</b>: CC BY 4.0<br>
<b>Download:</b>
<a href="data/mashupDS/MD3_17.csv" download>MD3_17</a>,
<a href="data/mashupDS/MD3_18.csv" download>MD3_18</a>,
<a href="data/mashupDS/MD3_19.csv" download>MD3_19</a>
</p>
</div>
</div>
</div>
<div class="row content">
<div class="" data-aos="fade-up" data-aos-delay="150">
<p>
<a href="documentation/CLEAN.ipynb"
target="_blank" style="vertical-align: middle;"><span
class="material-symbols-outlined">download</span></a>
Download the Jupyter Noteboook on the clean up phase<br>
<a href="documentation/MASHUP.ipynb"
target="_blank" style="vertical-align: middle;"><span
class="material-symbols-outlined">download</span></a>
Download the Jupyter Noteboook on the mashup phase
</p>
</div>
</div>
</div>
</section><!-- End Datasets Section -->
<!-- ======= Analyses Section ======= -->
<section id="analyses" class="services">
<div class="container">
<div class="section-title" data-aos="fade-up">
<h2>Analyses</h2>
<p>The 7 source datasets have been analysed for four aspects.</p>
</div>
<div class="row">
<!-- === Quality Analysis === -->
<div class="col-md-6 col-lg-3 d-flex align-items-stretch mb-5 mb-lg-0" type="button" data-bs-toggle="collapse"
data-bs-target="#target1" aria-expanded="false">
<div class="icon-box" data-aos="fade-up" data-aos-delay="100">
<div class="icon"><i class="bi bi-patch-check"></i></div>
<h4 class="title"><a>Quality analysis</a></h4>
<p class="description">Following the National Guidelines for the Improvement of Public Information Assets
and its four factors: accuracy, completeness, coherence and promptness.</p>
</div>
</div>
<!-- === Legal Analysis === -->
<div class="col-md-6 col-lg-3 d-flex align-items-stretch mb-5 mb-lg-0" type="button" data-bs-toggle="collapse"
data-bs-target="#target2" aria-expanded="false">
<div class="icon-box" data-aos="fade-up" data-aos-delay="200">
<div class="icon"><i class="bi bi-shield-shaded"></i></div>
<h4 class="title"><a href="">Legal Analysis</a></h4>
<p class="description">To assess possible imbalances and risks regarding the long-term viability of the
data generation and dissemination regarding the topics of: privacy, intellectual property, release
license, limitation on public access, economical conditions, and other temporary aspects.</p>
</div>
</div>
<!-- === Ethical Analysis === -->
<div class="col-md-6 col-lg-3 d-flex align-items-stretch mb-5 mb-lg-0" type="button" data-bs-toggle="collapse"
data-bs-target="#target3" aria-expanded="false">
<div class="icon-box" data-aos="fade-up" data-aos-delay="300">
<div class="icon"><i class="bi bi-universal-access"></i></div>
<h4 class="title"><a href="">Ethical Analysis</a></h4>
<p class="description">Evaluating the ethical aspects of the datasets using the Data
Ethics Principles and Guidelines: human being at the centre, transparency, accountability, and
individual data protection.
</p>
</div>
</div>
<!-- === Technical Analysis === -->
<div class="col-md-6 col-lg-3 d-flex align-items-stretch mb-5 mb-lg-0" type="button" data-bs-toggle="collapse"
data-bs-target="#target4" aria-expanded="false">
<div class="icon-box" data-aos="fade-up" data-aos-delay="400">
<div class="icon"><i class="bi bi-wrench"></i></div>
<h4 class="title"><a href="">Technical Analysis</a></h4>
<p class="description">On the metadata provided by Istat and other possible information on the datasets:
format, provenance, IRI. Moreover, an RDF assertion and metadata for the mashup datasets and an analysis
of the project from the perspective of the FAIR principles.</p>
</div>
</div>
</div>
</div>
<!-- Quality box -->
<div class="container collapse analysis-card" id="target1" data-bs-parent="#analyses">
<div class="align-items-stretch mb-5 mb-lg-0">
<div class="analysis-box">
<div class="analysis-box-title">
<i class="bi bi-patch-check"></i>
<h2 class="analysis-title">Quality analysis</h2>
</div>
<p class="analysis-text">
Following the Italian <a
href="https://docs.italia.it/italia/daf/lg-patrimonio-pubblico/it/stabile/aspettiorg.html#qualita-dei-dati"
target="_blank"><b>National
Guidelines</b></a> ("Linee guida nazionali per la valorizzazione del patrimonio informativo
pubblico"), developed in the context of the Data & Analytics
Framework project by AgID and the Digital Transformation Team, we have performed a quality analysis of our
source datasets to ensure their <span class="underlined--bg underlined--offset--bg"><b>good
condition</b></span> and their <span
class="underlined--bg underlined--offset--bg"><b>suitability</b></span> for the intended use.<br>
Specifically, there are four main factors to look for when analysing data quality:
<ul class="list-group list-group-flush">
<li class="list-group-item"><b>Accuracy (syntactic and semantic)</b>: the data and its attributes
correctly represent the real value of the concept or event they refer to</li>
<li class="list-group-item"><b>Coherence</b>: the data and its attributes do not present any
contradictions with respect to other data in the context of use by the administration owner</li>
<li class="list-group-item"><b>Completeness</b>: the data are exhaustive for what concerns every expected
value and with respect to the related entities (sources) that contribute to the definition of the
procedure</li>
<li class="list-group-item"><b>Timeliness (or promptness of updating)</b>: the data and its attributes
refer to the "correct time" (up to date) with respect to the procedure they refer to</li>
</ul>
The following table showcases the quality of each of the source datasets and highlights possible flaws.
</p>
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<th scope="col">ID Dataset</th>
<th scope="col">Accuracy</th>
<th scope="col">Coherence</th>
<th scope="col">Completeness</th>
<th scope="col">Timeliness</th>
</tr>
</thead>
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<th scope="row">D1 - Population 2017</th>
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<th scope="row">D2 - Population 2018, 2019</th>
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<th scope="row">D3 - Religious observance</th>
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<th scope="row">D4 - Live births</th>
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<th scope="row">D5 - Spontaneous abortions</th>
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<th scope="row">D6 - Induced abortions</th>
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<th scope="row">D7 - Early leavers from education</th>
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<h2 class="analysis-title">Legal analysis</h2>
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