Associated with manuscript titled: Fifty Muslim-majority countries have fewer COVID-19 cases and deaths than the 50 richest non-Muslim countriesThe objective of this research was to determine the difference in the total number of COVID-19 cases and deaths between Muslim-majority and non-Muslim countries, and investigate reasons for the disparities. Methods: The 50 Muslim-majority countries had more than 50.0% Muslims with an average of 87.5%. The non-Muslim country sample consisted of 50 countries with the highest GDP while omitting any Muslim-majority countries listed. The non-Muslim countries’ average percentage of Muslims was 4.7%. Data pulled on September 18, 2020 included the percentage of Muslim population per country by World Population Review15 and GDP per country, population count, and total number of COVID-19 cases and deaths by Worldometers.16 The data set was transferred via an Excel spreadsheet on September 23, 2020 and analyzed. To measure COVID-19’s incidence in the countries, three different Average Treatment Methods (ATE) were used to validate the results. Results published as a preprint at https://doi.org/10.31235/osf.io/84zq5(15) Muslim Majority Countries 2020 [Internet]. Walnut (CA): World Population Review. 2020- [Cited 2020 Sept 28]. Available from: http://worldpopulationreview.com/country-rankings/muslim-majority-countries (16) Worldometers.info. Worldometer. Dover (DE): Worldometer; 2020 [cited 2020 Sept 28]. Available from: http://worldometers.info

"Between October 2011 and November 2012, Pew Research Center, with generous funding from The Pew Charitable Trusts and the John Templeton Foundation, conducted a public opinion survey involving more than 30,000 face-to-face interviews in 26 countries in Africa, Asia, the Middle East and Europe. The survey asked people to describe their religious beliefs and practices, and sought to gauge respondents; knowledge of and attitudes toward other faiths. It aimed to assess levels of political and economic satisfaction, concerns about crime, corruption and extremism, positions on issues such as abortion and polygamy, and views of democracy, religious law and the place of women in society.

"Although the surveys were nationally representative in most countries, the primary goal of the survey was to gauge and compare beliefs and attitudes of Muslims. The findings for Muslim respondents are summarized in the Religion & Public Life Project's reports The World's Muslims: Unity and Diversity and The World's Muslims: Religion, Politics and Society, which are available at www.pewresearch.org. [...] This dataset only contains data for Muslim respondents in the countries surveyed. Please note that this codebook is meant as a guide to the dataset, and is not the survey questionnaire." (2012 Pew Religion Worlds Muslims Codebook)

This Religion and State-Minorities (RASM) dataset is supplemental to the Religion and State Round 2 (RAS2) dataset. It codes the RAS religious discrimination variable using the minority as the unit of analysis (RAS2 uses a country as the unit of analysis and, is a general measure of all discrimination in the country). RASM codes religious discrimination by governments against all 566 minorities in 175 countries which make a minimum population cut off. Any religious minority which is at least 0.25 percent of the population or has a population of at least 500,000 (in countries with populations of 200 million or more) are included. The dataset also includes all Christian minorities in Muslim countries and all Muslim minorities in Christian countries for a total of 597 minorities. The data cover 1990 to 2008 with yearly codings.

These religious discrimination variables are designed to examine restrictions the government places on the practice of religion by minority religious groups. It is important to clarify two points. First, these variables focus on restrictions on minority religions. Restrictions that apply to all religions are not coded in this set of variables. This is because the act of restricting or regulating the religious practices of minorities is qualitatively different from restricting or regulating all religions. Second, this set of variables focuses only on restrictions of the practice of religion itself or on religious institutions and does not include other types of restrictions on religious minorities. The reasoning behind this is that there is much more likely to be a religious motivation for restrictions on the practice of religion than there is for political, economic, or cultural restrictions on a religious minority. These secular types of restrictions, while potentially motivated by religion, also can be due to other reasons. That political, economic, and cultural restrictions are often placed on ethnic minorities who share the same religion and the majority group in their state is proof of this.

This set of variables is essentially a list of specific types of religious restrictions which a government may place on some or all minority religions. These variables are identical to those included in the RAS2 dataset, save that one is not included because it focuses on foreign missionaries and this set of variables focuses on minorities living in the country. Each of the items in this category is coded on the following scale:

0. The activity is not restricted or the government does not engage in this practice.
1. The activity is restricted slightly or sporadically or the government engages in a mild form of this practice or a severe form sporadically.
2. The activity is significantly restricted or the government engages in this activity often and on a large scale.

A composite version combining the variables to create a measure of religious discrimination against minority religions which ranges from 0 to 48 also is included.

ARDA Note: This file was revised on October 6, 2017. At the PIs request, we removed the variable reporting on the minority's percentage of a country's population after finding inconsistencies with the reported values. For detailed data on religious demographics, see the "/data-archive?fid=RCSREG2" Target="_blank">Religious Characteristics of States Dataset Project.

This dataset was derived from Swivel.com at: http://www.swivel.com/data_sets/show/1011482 Which cites the CIA Fact book as the official Source. https://www.cia.gov/library/publications/the-world-factbook/ Data is available for 60 countries around the world, and lists the Muslim Population for each. This data was collected on January 15, 2008.

Right-wing populist voices argue that Muslims do not belong in Western Europe because Islam opposes the “core Western value” of women's empowerment. Ironically, such hostilities could cause European Muslims to reject antagonistic natives and their “Western values,” potentially creating backlashes in Muslims' support for gender equality. Delving into this possibility, this study diverges from simple conceptualizations of one inherently patriarchal Islam to study the diversity among Muslims in the gendered meanings they attach to their religion in different contexts. Empirically, we use a uniquely pooled dataset covering over 9,000 European Muslims in 16 Western European countries between 2008 and 2019. Multilevel models show that while mosque attendance limits support for public-sphere gender equality, religious identifications only do so among men and individual prayer only among women. Additionally, our results tentatively indicate that in more hostile contexts, prayer's effects become more patriarchal while religious identification's connection to opposition to gender equality weakens. We conclude that Islamic religiosities shape Muslims' support for public-sphere gender equality in far more complex ways than any right-wing populist claim on one essential patriarchal Islam captures.

DOI This repository contains historical data collected in the digital humanities project Dhimmis & Muslims – Analysing Multireligious Spaces in the Medieval Muslim World. The project was funded by the VolkswagenFoundation within the scope of the Mixed Methods initiative. The project was a collaboration between the Institute for Medieval History II of the Goethe University in Frankfurt/Main, Germany, and the Institute for Visualization and Interactive Systems at the University of Stuttgart, and took place there from 2018 to 2021. The objective of this joint project was to develop a novel visualization approach in order to gain new insights on the multi-religious landscapes of the Middle East under Muslim rule during the Middle Ages (7th to 14th century). In particular, information on multi-religious communities were researched and made available in a database accessible through interactive visualization as well as through a pilot web-based geo-temporal multi-view system to analyze and compare information from multiple sources. The code for this visualization system is publicly available on GitHub under the MIT license. The data in this repository is a curated database dump containing data collected from a predetermined set of primary historical sources and literature. The core objective of the data entry was to record historical evidence for religious groups in cities of the Medieval Middle East. In the project, data was collected in a relational PostgreSQL database, the structure of which can be reconstructed from the file schema.sql. An entire database dump including both the database schema and the table contents is located in database.sql. The PDF file database-structure.pdf describes the relationship between tables in a graphical schematic. In the database.json file, the contents of the individual tables are stored in JSON format. At the top level, the JSON file is an object. Each table is stored as a key-value pair, where the key is the database name, and the value is an array of table records. Each table record is itself an object of key-value pairs, where the keys are the table columns, and the values are the corresponding values in the record. The dataset is centered around the evidence, which represents one piece of historical evidence as extracted from one or more sources. An evidence must contain a reference to a place and a religion, and may reference a person and one or more time spans. Instances are used to connect evidences to places, persons, and religions; and additional metadata are stored individually in the instances. Time instances are connected to the evidence via a time group to allow for more than one time span per evidence. An evidence is connected via one or more source instances to one or more sources. Evidences can also be tagged with one or more tags via the tag_evidence table. Places and persons have a type, which are defined in the place type and person type tables. Alternative names for places are stored in the name_var table with a reference to the respective language. For places and persons, references to URIs in other data collections (such as Syriaca.org or the Digital Atlas of the Roman Empire) are also stored, in the external_place_uri and external_person_uri tables. Rules for how to construct the URIs from the fragments stored in the last-mentioned tables are controlled via the uri_namespace and external_database tables. Part of the project was to extract historical evidence from digitized texts, via annotations. Annotations are placed in a document, which is a digital version of a source. An annotation can be one of the four instance types, thereby referencing a place, person, religion, or time group. A reference to the annotation is stored in the instance, and evidences are constructed from annotations by connecting the respective instances in an evidence tuple.

The Carnegie Middle East Governance and Islam Dataset was created by "https://lsa.umich.edu/polisci/people/faculty/tessler.html" Target="_blank">Mark Tessler at the "https://umich.edu/" Target="_blank">University of Michigan. The data set includes both individual-level and country-level variables. Data on individual-level variables are drawn from 35 surveys carried out in 12 Arab countries, Turkey and Iran. Most of the surveys were carried out either as the first wave of the "https://www.arabbarometer.org/" Target="_blank">Arab Barometer, the third, fourth and fifth waves of the "https://www.worldvaluessurvey.org/wvs.jsp" Target="_blank">World Values Survey, or a project on attitudes related to governance carried out by Mark Tessler with funding from the "https://www.nsf.gov/" Target="_blank">National Science Foundation.

This dataset is a research outcome of a European Research Council, Starting Grant funded (Grant Number 679097, Industrialisation and Urban Growth from the mid-nineteenth century Ottoman Empire to Contemporary Turkey in a Comparative Perspective, 1850-2000, UrbanOccupationsOETR) project. It contains a mid-nineteenth-century urban Ottoman population micro dataset for the city of Bursa.

In recent decades, a "big microdata revolution" has revolutionized access to transcribed historical census data for social science research. Despite this, the population records of the Ottoman Empire, spanning Southeastern Europe, Western Asia, and Northern Africa, remained absent from the big microdata ecosystem due to their prolonged inaccessibility. In fact, like other modernizing states in the nineteenth century, the Ottoman Empire started to enumerate its population in population registers (nüfus defterleri) in 1830, which recorded only males of all ages for conscription and taxation purposes. These registers were completed and updated in two waves, one in 1830-1838 and the other in the 1839-1865 period. Following this experience, the Empire implemented its first modern census, which included females, in 1881/1882 for more comprehensive statistical and governance reasons to converge with European census-taking practices and account for the increasing participation of females in economic and social spheres.

The pre-census population registers were opened to researchers in 2011. There are around 11.000 registers today. The microdata of the late Ottoman censuses is still not available. Still, unfortunately, the majority of the existing literature using the population registers superficially utilized and failed to tabulate the microdata. Most works using these valuable sources contented with transcribing the microdata from Ottoman to Latin script and presenting their data in raw and unstyled fashion without publishing them in a separate repository.

Our dataset marks the inaugural release of complete population data for an Ottoman urban center, the city of Bursa, derived from the 1839 population registers. It presents originally non-tabulated register data in a tabular format integrated into a relational Microsoft Access database. To ensure that our dataset is more accessible, we are also releasing the dataset in Microsoft Excel format.

The city of Bursa, a major cosmopolitan commercial hub in modern northwestern Turkey, is selected from the larger UrbanOccupationsOETR project database as an exemplary case to represent the volume, value, variety, and veracity of the population data. Furthermore, since urban areas are usually the most densely populated locations that attract the most migration in any country, they are attractive locations for multifold reasons in historical demography. Bursa is not the only urban location in the UrbanOccupationsOETR database. As it focused on urbanization and occupational structural change, it collected the population microdata on major urban centers (chosen as primary locations) and towns (denoted as secondary locations), which pioneered the economic development of post-Ottoman nation-states. What makes the city of Bursa’s data more advantageous than other cities is that it has been cleaned and validated multiple times and used elsewhere for demographic and economic analyses.

The Ottoman population registers of 1830 and 1839 classified the population under the commonly and officially recognized ethnoreligious identities- Muslim, Orthodox Christian, Armenian, Catholic, Jewish, and (Muslim and non-Muslim) Roma. Muslim and non-Muslim populations were counted in separate registers. The registers were organized along spatial and temporal lines. The standard unit of the register was the quarter (mahalle) in urban and village (karye) in rural settings. Within these register units, populated public and non-household spaces such as inns, dervish lodges, monasteries, madrasas, coffeehouses, bakeries, mills, pastures (of nomads), and large private farms (çiftlik) were recorded separately.

The household (menzil/hane) was the unit of entry, which sometimes took different forms depending on the context, such as the room for inns and the tent for nomads. Each household recorded its members on a horizontal line. The variables of male individuals inhabiting them were self-reported biographical information (names, titles/family names, ages, and occupations), physical description (height and facial hair), relationships with other household members (kinship, tenancy, and employment ties), infirmities, and military and poll tax status, including the reasons for exemption, military post, and poll tax category (high-ala, medium-evsat, and small-edna). Households with no inhabitants were differentiated. At the same time, if a resident was known to be absent during registration due to reasons such as military service or migration, he was recorded in his household with a note stating that reason. If he was missing and appeared later, he was added to the household during updates with a note like “not recorded previously” (e.g., hin-i tahrirde taşrada olub) or “newly recorded” (tahrir-mande).

In addition to the permanent residents of a given location, migrant/temporary non-local (yabancı) residents such as laborers, inn-stayers, and unskilled bachelors (bî-kâr) were recorded along with their place of origin and for how long they had been in the migrated place. Non-Muslim migrants were registered with information regarding the last location where they got their poll tax certificate and if they would make their next poll tax payment in the migrated location.

Updates were made mainly to births, deaths, migrations, and military and poll tax status. No other variables, such as age, were renewed except for occupations in a limited number of cases. Updates are easily identifiable since they were written in siyakat, a special Ottoman chancery shorthand script, and occasionally in red ink. Births were specified with newborns’ names added next to the father’s entry. Deaths were updated by crossing out the deceased person’s record. Migrations were added with a description of the migrated place (including the military branch if the person was conscripted). Military and poll tax status was updated by crossing out the old category and adding the new one next to it. Updates were usually expressed in hijri years, sometimes in month-year, and rarely in day-month-year fashion. It is important to note that since updates were made once every few months, these dates may reflect their registration date rather than giving the exact time of the events. Equally crucial is that many events, especially births, were not reported, so their quality is limited.

Modeled after the way information was contained in the population registers, this relational database has two tables, “tblHouse” and “tblIndividual.” Each table categorizes and standardizes the register variables. To make the data easier to use, the dataset also includes a query “Query_InnerJoin” that combines all the variables from each table in a separate sheet.

Given Bursa’s important place in Ottoman history, our dataset serves as a large and crucial resource for comprehending historical societal, economic, and demographic trends within the Empire in the early stages of globalization. The dataset has 8391 household entries (HouseID) and 19,186 individual (IndivID) entries. This data includes the population registered in all of Bursa’s quarters and other location categories in 1839 and the updates until and including 1843 (Figure 2). The ethno-religious breakdown of the total population is 12462 Muslims (65%), 3315 Armenians (17%), 2466 Orthodox Christians (13%), 749 Jews (4%), and 194 Catholics (1%).

To broaden access and use of our data and bring it more in line with findability, accessibility, interoperability, and reusability (FAIR) data guidelines, the variables of “tblHouse” and “tblIndividual” are sorted into general categories and described in detail in the following tables. As the variables indicate, the dataset and population registers, in general, could serve to formulate unprecedented, hitherto impossible research questions related to major demographic dynamics, i.e., household size and composition, ethnoreligious differences, population density, occupational structure, intergenerational mobility and status transfer, mortality, fertility, migration, age-heaping/human capital, conscription, settlement patterns within and across urban locations, onomastics, toponymy, etc.

Table 1: Categories and descriptions of the variables of tblHouse

IndQNER

IndQNER is a Named Entity Recognition (NER) benchmark dataset that was created by manually annotating 8 chapters in the Indonesian translation of the Quran. The annotation was performed using a web-based text annotation tool, Tagtog, and the BIO (Beginning-Inside-Outside) tagging format. The dataset contains:

3117 sentences

62027 tokens

2475 named entities

18 named entity categories

Named Entity Classes

The named entity classes were initially defined by analyzing the existing Quran concepts ontology. The initial classes were updated based on the information acquired during the annotation process. Finally, there are 20 classes, as follows:

Allah

Allah's Throne

Artifact

Astronomical body

Event

False deity

Holy book

Language

Angel

Person

Messenger

Prophet

Sentient

Afterlife location

Geographical location

Color

Religion

Food

Fruit

The book of Allah

Annotation Stage

There were eight annotators who contributed to the annotation process. They were informatics engineering students at the State Islamic University Syarif Hidayatullah Jakarta.

Anggita Maharani Gumay Putri

Muhammad Destamal Junas

Naufaldi Hafidhigbal

Nur Kholis Azzam Ubaidillah

Puspitasari

Septiany Nur Anggita

Wilda Nurjannah

William Santoso

Verification Stage

We found many named entity and class candidates during the annotation stage. To verify the candidates, we consulted Quran and Tafseer (content) experts who are lecturers at Quran and Tafseer Department at the State Islamic University Syarif Hidayatullah Jakarta.

Dr. Eva Nugraha, M.Ag.

Dr. Jauhar Azizy, MA

Dr. Lilik Ummi Kultsum, MA

Evaluation

We evaluated the annotation quality of IndQNER by performing experiments in two settings: supervised learning (BiLSTM+CRF) and transfer learning (IndoBERT fine-tuning).

Supervised Learning Setting

The implementation of BiLSTM and CRF utilized IndoBERT to provide word embeddings. All experiments used a batch size of 16. These are the results:

Maximum sequence length Number of e-poch Precision Recall F1 score

256 10 0.94 0.92 0.93

256 20 0.99 0.97 0.98

256 40 0.96 0.96 0.96

256 100 0.97 0.96 0.96

512 10 0.92 0.92 0.92

512 20 0.96 0.95 0.96

512 40 0.97 0.95 0.96

512 100 0.97 0.95 0.96

Transfer Learning Setting

We performed several experiments with different parameters in IndoBERT fine-tuning. All experiments used a learning rate of 2e-5 and a batch size of 16. These are the results:

Maximum sequence length Number of e-poch Precision Recall F1 score

256 10 0.67 0.65 0.65

256 20 0.60 0.59 0.59

256 40 0.75 0.72 0.71

256 100 0.73 0.68 0.68

512 10 0.72 0.62 0.64

512 20 0.62 0.57 0.58

512 40 0.72 0.66 0.67

512 100 0.68 0.68 0.67

This dataset is also part of the NusaCrowd project which aims to collect Natural Language Processing (NLP) datasets for Indonesian and its local languages.

How to Cite

@InProceedings{10.1007/978-3-031-35320-8_12,author="Gusmita, Ria Hariand Firmansyah, Asep Fajarand Moussallem, Diegoand Ngonga Ngomo, Axel-Cyrille",editor="M{\'e}tais, Elisabethand Meziane, Faridand Sugumaran, Vijayanand Manning, Warrenand Reiff-Marganiec, Stephan",title="IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran",booktitle="Natural Language Processing and Information Systems",year="2023",publisher="Springer Nature Switzerland",address="Cham",pages="170--185",abstract="Indonesian is classified as underrepresented in the Natural Language Processing (NLP) field, despite being the tenth most spoken language in the world with 198 million speakers. The paucity of datasets is recognized as the main reason for the slow advancements in NLP research for underrepresented languages. Significant attempts were made in 2020 to address this drawback for Indonesian. The Indonesian Natural Language Understanding (IndoNLU) benchmark was introduced alongside IndoBERT pre-trained language model. The second benchmark, Indonesian Language Evaluation Montage (IndoLEM), was presented in the same year. These benchmarks support several tasks, including Named Entity Recognition (NER). However, all NER datasets are in the public domain and do not contain domain-specific datasets. To alleviate this drawback, we introduce IndQNER, a manually annotated NER benchmark dataset in the religious domain that adheres to a meticulously designed annotation guideline. Since Indonesia has the world's largest Muslim population, we build the dataset from the Indonesian translation of the Quran. The dataset includes 2475 named entities representing 18 different classes. To assess the annotation quality of IndQNER, we perform experiments with BiLSTM and CRF-based NER, as well as IndoBERT fine-tuning. The results reveal that the first model outperforms the second model achieving 0.98 F1 points. This outcome indicates that IndQNER may be an acceptable evaluation metric for Indonesian NER tasks in the aforementioned domain, widening the research's domain range.",isbn="978-3-031-35320-8"}

Contact

If you have any questions or feedback, feel free to contact us at ria.hari.gusmita@uni-paderborn.de or ria.gusmita@uinjkt.ac.id

This dataset contains the Arab-West Report special reports that were published in 2007. This dataset mainly contains the writings of Cornelis Hulsman, Drs., among other authors on topics related to Muslim- Christian relations and interfaith dialogue. Additionally, this dataset features certain reports related to the Christian faith in Egypt, Monastic life and Coptic traditions.Some of the articles address the media coverage of Muslim-Christian incidents and sectarian tensions, and how biased media reporting can often exacerbate existing tensions between groups. These articles feature a number of interviews conducted by Arab West Report with prominent social figures and scholars.Additionally, reports from this dataset discuss conversion cases and interfaith meetings that were held at the time. This dataset also contains media critique from Arab West Report Editor-in-Chief Cornelis Hulsman, Drs.Some of the themes that characterize this dataset include:- Authors report on their trip to see the celebration of the Holy Family crossing the Nile River in a village in Upper Egypt. They reflect on their experiences and the need to improve dialogue between Muslims and Christians in Egypt.- An overview of a forum organized by the Center for Civilizational Studies and Dialogue between Cultures at Cairo University to introduce a book written by Father Christian van Nispen, sj, entitled, ‘Christians and Muslims: Brothers before God.’ van Nispen’s principle argument is that both Muslims and Christians worship one and the same God, but according to different understandings.- Another report highlighted the second conference on bias, entitled: ‘The International Conference for Dialogue between Civilizations and the Different Tracks of Knowledge.’ The 4-day conference, was sponsored by the Program for Civilizational Studies and Dialogue between Cultures at Cairo University, and the International Institute of Islamic Thought.- The Arab West Report annual report: The Center for Arab-West Understanding presents its annual report for 2006.Media critique:- “Minister Of Awqaf Dr. Hamdi Zakzouk Falsely Accused Of Calling For The Death Penalty For Apostates From Islam”: Arab-West Report responds to media claims that Dr. Hamdi Zakzouk called for the death penalty for apostates from Islam.-In another report, the authors stress that misguided media reporting often only serves to further tensions, particularly in cases of sectarian strife. Another article presents the transcript of a lecture for the Arab Thought Forum. It considers media distortions and mis-representation in the media that only serve to further antagonize Muslim-Christian relations and the perception of Islam / the Arab world in the West. Cornelis Hulsman, Drs., explains the role of the Center for Arab West Understanding, and the importance of constructive, unbiased, and fully researched journalism.-Hulsman stressed in one of his articles that media frequently manipulate headlines in an effort to present stories in the context they desire. Headlines are also frequently sensationalized in an effort to attract a larger number of readers, but if this also distorts a story this should be questioned. Cornelis Hulsman, Drs., stresses the danger of ignorant media reporting, and the damage that inaccurate fact-checking can cause. He provides a number of examples from various intellectuals, commenting on stories that have been sensationalized in the media, and the negative effects this reporting had on Arab-West relations and on furthering dialogue between the Islamic and Arab world and the West.Interviews:-“An interview With Father Basilius About Father Matta Al-Maskin”: Father Basilius discusses the history and theological philosophies of Father Mattá al-Maskīn. The interview is mainly focused on theology and the practices of clergymen.- An interview with Tarek Heggy at CIDT where Drs. Cornelis Hulsman and staff members discuss sensitive issues throughout the Arab world.- An interview by AWR/ CIDT interns with Dr. Hala Mustafa, where she comments on her role in the National Democratic Party’s Policies Committee, her opinions on reform in Egypt, critiques the role of Egyptian security, and outlines the necessary steps needed for reform to take effect.- “Saad Eddin Ibrahim Meets With CIDT Interns To Discuss How Islamists Have Changed”: Saad Eddin Ibrahim, is one of the most outspoken critics of the Egyptian government, who was imprisoned from 2000-2003 for his critique. Saad Eddin Ibrahim is a liberal secularist, but as a result of his strong democratic stance, he defends the rights of all groups in society, including Islamists, to participate in the politics of the country. CIDT-interns met with him for a talk about his life and his views.-A review of the Annual Anglican-Al Azhar Interfaith Meeting Dialogue held in All-Saints Cathedral which implicitly dealt with dialogue and means of furthering it.-A report on church response to poverty in Egypt and specifically how this issue is being addressed by the Coptic Orthodox Church in an attempt to alleviate the suffering of Egyptians.-The following presents an investigative report authored by Mads Akselbo Holm, an intern for Arab-West Report, on the issue of Muslims leaving their faith. This study provides an excellent background to the commotion caused by Muḥammad Ḥijāzī announcing his conversion to Christianity. In addition to that, another article discussed “The Freedom to Change One’s Religion Or Belief”; and another spoke of “Article 18 Of The Universal Declaration Of Human Rights”, indicating that although Egyptian civil law does not prohibit conversion from one religion to another, there are discrepancies in an individual’s ability to convert.-Debates about freedom of religion and conversion in Egypt focusing on legal cases of conversions, specifically changing one’s religious identity on identification cards.- A report by Hulsman discussed the state of past and present relations between Muslims and Christians in Egypt. The paper opens by giving information about Pope Shenouda III and the most important incidents that have taken place during his reign. The second half of the paper then looks at specific examples of Christian contributions to Christian-Muslim tensions in contemporary Egypt.- An article discusses the exaggerated interpretations of some Western Christians about the position of Christians in Egypt.Authors featured in this dataset are:Cornelis Hulsman, Drs., Ane Skov Birk, Salmā Ānwar, Drs. Sawsan Jabrah Ayyub Khalil, Katrin Koehler, Christian Fastenrath, Dr. Larry F. Levine, Wisām Muhammad al-Duwīnī, Maria Rezzonico, Mads Akselbo Holm, and Susan Richards-Benson

Aggregated figures for natural hazard related events in EM-DAT: Iran (Islamic Republic of)

Documentation on the Country Profiles available here

How to cite the EM-DAT Project here

Main dataset on HDX: EM-DAT - Country Profiles

More on the EM-DAT database : website / data portal

Each line corresponds to a given combination of year, country, disaster subtype and reports figures for :

• number of disasters
• total number of people affected
• total number of deaths
• economic losses (original value and adjusted)

Interview Data Nativism, Islamophobism and Islamism in the Age of Populism dataset Transcripts of 302 interviews conducted with self-identified Muslim youth of migrant origin and native youth with affiliation or sympathy with movements labeled far-right in Belgium, France, the Netherlands, and Germany.[1] Local researchers conducted the interviews using the same interview guide, including 17 questions. Interviews were not audio-recorded. The researchers took notes, verifying their transcriptions with the research participant during and after the interview. Originally, the research consisted 307 interviews but five participants (1 French native; 2 German Muslims; 2 German natives) did not want their interview transcriptions to be made public on the ERC data repository site. In accordance with our ethical guidelines, we anonymized the transcripts. The dataset also includes the summary output (as an excel file) of the values analysis of the 307 interviews. Please visit the attachment named Data Summary to learn more about our method of analysis and how to use the attached documents. As a complementary file, we hope that the additional excel sheet detailing the demographic characteristics of our research participants (sex, age, educational background, etc.) helps advance researchers’ understanding of our participant profile. Additional information: 302 transcription files (zipped), 2 data summary files, 2 documentation files Cadmus permanent link: https://hdl.handle.net/1814/76159 Series/Number: EUI; RSC; Research Data; 2023 Publisher: European University Institute Keyword(s): Deprivation, Radicalism, Nativism, Populism, Islamism Sponsorship and Funder information: ERC Advanced Grant research project "Nativism, Islamophobism and Islamism in the Age of Populism: Culturalisation and Religionisation of what is Social, Economic and Political in Europe" (No: 785934). The project’s details and output can also be accessed at the project website, https://bpy.bilgi.edu.tr/en/ [1] ERC Advanced Grant research project "Nativism, Islamophobism and Islamism in the Age of Populism: Culturalisation and Religionisation of what is Social, Economic and Political in Europe" (No: 785934). The project’s details and output can also be accessed at the project website, https://bpy.bilgi.edu.tr/en/ .

(UNCLASSIFIED) The Liberian population is religiously heterogeneous, comprised 85.6 percent Christian, 12.6 percent Muslim, 0.6 percent adherents of tribal or indigenous traditions, 1.5 percent non-religious, and less than 1 percent a combination of Bahais, Hindus, Sikhs, and Buddhists. Primary denominations within the country’s Christian majority include Lutheran, Baptist, Episcopal, Presbyterian, Roman Catholic, United Methodist, African Methodist Episcopal (AME), AME Zion, and Pentecostal. Many individuals identified as "Christian" retain a mix of Christian and indigenous (often animistic) beliefs. Both Christian and Muslim Liberians are dispersed throughout the country. Most Muslims belong to two distinct ethnic groups, the Mandingo—who are widely distributed—and the Vai who live mostly in western areas.Christianity reached Liberia in the 19th century with the arrival of freed slaves from the United States. Missionaries of various Protestant denominations started arriving in the 1820s, eventually forming what became one of the highest per capita missionary populations in the world. The first permanent Catholic mission in the country was established in the early 1900s. A Liberian Council of Churches composed of Lutheran, Episcopal, Methodist, and other similar groups now exists, and an evangelical association of churches and missions has operated on and off since 1966. Though religiously-motivated violence in Liberia is relatively uncommon, tensions between Christians and Muslims have escalated in the past. In October 2004, approximately 25 people were killed and several churches and mosques were destroyed in Monrovia during clashes between Christians of several ethnic groups and Mandingo Muslims. The Liberian constitution provides religious freedom for all inhabitants, and in practice, the government respects minority religious groups. According to a 2013 document published by the U.S. Department of State, the Liberian government does not discriminate based on religious affiliation, belief, or worship. Although there is no state religion in the country, government ceremonies commonly begin and end with prayers or hymns, the majority of which are Christian, though some are Muslim. Most private schools in the country are operated by churches or missions. The majority receive government funding, though non-religious schools are also heavily subsidized. Religious education is available as an elective in public schools, but is not required. Social welfare institutions are largely managed or affiliated with religious organizations, often in conjunction with international aid agencies. As regards the ongoing Ebola crisis in West Africa, some religious leaders in Liberia have cited “immoral acts” as the cause of the outbreak. In August 2014, Liberia’s Council of Churches agreed, “God is angry with Liberia,” and urged Liberians to seek forgiveness for corruption and immorality by staying indoors and fasting for three days.Attribute Table Field DescriptionsISO3 - International Organization for Standardization 3-digit country code ADM0_NAME - Administration level zero identification / name ADM1_NAME - Administration level one identification / name ADM2_NAME - Administration level two identification / name NAME - Name of religious institution TYPE - Classification in the geodatabase (type of institution) CITY - City location available SPA_ACC - Spatial accuracy of site location (1 – high, 2 – medium, 3 – low) COMMENTS - Comments or notes regarding the religious institution SOURCE_DT - Source one creation date SOURCE - Source one SOURCE2_DT - Source two creation date SOURCE2 - Source two CollectionThe feature class was generated utilizing data from OpenStreetMap, Wikimapia, GeoNames and other sources. OpenStreetMap is a free worldwide map, created by crowd-sourcing. Wikimapia is open-content mapping focused on gathering all geographical objects in the world. GeoNames is a geographical places database maintained and edited by the online community. Consistent naming conventions for geographic locations were attempted but name variants may exist, which can include historical or less widespread interpretations.The data included herein have not been derived from a registered survey and should be considered approximate unless otherwise defined. While rigorous steps have been taken to ensure the quality of each dataset, DigitalGlobe is not responsible for the accuracy and completeness of data compiled from outside sources.Metadata information was collected form U.S. Department of State publications as well as news media articles. Sources (HGIS)"Cathedral of St. Therese of The Child Jesus." GCatholic. July 2014. Accessed October 7, 2014. http://www.gcatholic.org.DigitalGlobe, "DigitalGlobe Imagery Archive." Accessed October 01, 2014. GeoNames, "Liberia." September 23, 2014. Accessed October 01, 2014. http://www.geonames.org.Google, September 2014. Accessed October 01, 2014. www.google.com.OpenStreetMap, "Liberia." September 2014. Accessed October 01, 2014. http://www.openstreetmap.org.Wikimapia, "Liberia." September 2014. Accessed October 01, 2014. http://wikimapia.org.Sources (Metadata)Baden, Joel and Candida Moss. “Ebola Is Not God’s Wrath: Religious leaders are perpetuating dangerous, dehumanizing beliefs about sin and disease.” Slate. August 20, 2014. Accessed October 01, 2014. http://www.slate.com.“Country Profile: Liberia.” Soudan Interior Mission. January 01, 2014. Accessed October 01, 2014. http://www.sim.org.“Education System in Liberia.” Classbase. January 01, 2012. Accessed October 01, 2014. http://www.classbase.com.“Liberia 2005 International Religious Freedom Report.” United States Department of State: Bureau of Democracy, Human Rights, and Labor. January 01, 2005. Accessed October 01, 2014. http://www.state.gov.“Liberia 2012 International Religious Freedom Report.” United States Department of State: Bureau of Democracy, Human Rights, and Labor. January 01, 2005. Accessed October 01, 2014. http://www.state.gov.“Liberia 2014 International Religious Freedom Report.” United States Department of State. January 01, 2014. Accessed October 01, 2014. http://www.state.gov.

India Census: Population: by Religion: Muslim: Urban data was reported at 68,740,419.000 Person in 2011. This records an increase from the previous number of 49,393,496.000 Person for 2001. India Census: Population: by Religion: Muslim: Urban data is updated yearly, averaging 59,066,957.500 Person from Mar 2001 (Median) to 2011, with 2 observations. The data reached an all-time high of 68,740,419.000 Person in 2011 and a record low of 49,393,496.000 Person in 2001. India Census: Population: by Religion: Muslim: Urban data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE001: Census: Population: by Religion.

This data collection provides comprehensive data on all Hindu-Muslim riots reported in the major Indian newspaper of record (THE TIMES of India, Bombay edition), from January 1950 through December 1995. The dataset includes information on location (town, village, state, district, country), casualties, duration, reported causes, official involvement, policing arrangements, and other characteristics.

This dataset is designed for training and evaluating deep learning models for recognizing the various postures (steps) of Muslim prayer (salat). Each image was meticulously labeled with bounding boxes encompassing the individual performing the specific salat posture. This dataset involved: Selecting images: A few pictures were taken from different places to show various moves that comprise salat positions (1). Internet augmentation: More pictures showing people praying were added to the data set from the internet. The seven classes correspond to the essential positions in Islamic prayer: 1. raising: Standing posture. 2. ruku: Bowing posture. 3. sitting: Sitting position during prayer. 4. sujud: Prostration posture. 5. takbeer: Hands raised. 6. tashhud: Sitting posture for final supplications. 7. tasleem: Final salutation posture. Reference Koubâa, A., Ammar, A., Benjdira, B., Al-Hadid, A., Kawaf, B., Al-Yahri, S.A., Babiker, A., Assaf, K. and Ras, M.B., 2020, March. Activity Monitoring of Islamic Prayer (Salat) Postures using Deep Learning. In 2020 6th Conference on Data Science and Machine Learning Applications (CDMA) (pp. 106-111). IEEE.

The aim of the EURISLAM research project is to provide a systematic analysis of cross-national differences and similarities in countries’ approaches to the cultural integration of immigrants in general and Muslims in particular. The countries studied in the research project are Belgium, France, Germany, The Netherlands, Switzerland and the United Kingdom. The core research question can be formulated as follows: ‘How have different traditions of national identity, citizenship and church-state relations affected European immigration countries’ incorporation of Islam, and what are the consequences of these approaches for patterns of cultural distance and interaction between Muslim immigrants and their descendants, and the receiving society?’ In order to answer this question, policy differences are related to cross-national variation in cultural distance and interaction between Muslims and the receiving society population. Three more specific research questions have been designed which are the focus in 7 different Work packages of the EURISLAM research project. The different methodologies used in the Work packages are later combined in the research project, allowing for a triangulation of research findings and a combination of quantitative and qualitative insights.In Work package 3 of the EURISLAM project a survey questionnaire has been developed which enabled a study of the individual characteristics of Muslim immigrants. This survey is designed to answer one of the three specific research questions used in this project: ‘To what extent do we find differences across immigration countries in cultural distance and patterns of interaction between various Muslim immigrant groups and the receiving society population?’ On the one hand, we focussed on attitudes, norms, and values, particularly those relating to democratic norms, gender relations and family values, ethnic, religious, and receiving society identification, and attitudes towards relations across ethnic and religious boundaries. On the other hand, the study looked at cultural and religious resources and practices, such as language proficiency, adherence to various religious practices (e.g., attendance of religious services or wearing of a headscarf), interethnic and interreligious partnerships and marriages, the frequency and quality of interethnic and interreligious relationships with neighbours, friends, and colleagues, and memberships in social and political organisations of the own ethnic and religious group as well as of the receiving society. Both types of questions have been asked – of course where relevant in an adapted format – with regard to members of the dominant ethnic group of the receiving society, because, obviously, cultural distance and interactions are determined by the perceptions, attitude, and practices at both ends of the relationship. All these variables were gathered by way of a survey in each of the countries of a number of selected Muslim immigrant groups, as well as a sample of receiving society ethnics. The data of this survey is now published together with a Codebook.In the revised edition of the codebook new information is added on the religion group variables in Block 3. In retrospect ambiguity appeared in the survey questionnaire specifically in the religion questions which (may) imply missing values for respondents of the ‘Atheist/agnostic/Do not belong to any denomination’ religious faith denomination group. These missing values may lead to distortions when using variables of the religion group. More details on this issue can be found on page 16 (3.2 Information on religion variables) of the revised codebook.Specific information on the project duration has been added on page 8 (1.3 Project Duration) of the revised codebook.The EURISLAM Dataset Survey-data published on October 6, 2015 has not been revised.

Context

A Hadith is a report describing the words, actions, intentions or habits of the last Prophet and Messenger Muhammed (Peace Be Upon Him). The term literally means report, account or narrative.

Ṣaḥīḥ al-Bukhārī (صحيح البخاري‎‎), is one of the six major hadith collections books. It was collected by a Muslim scholar Imam Muhammad al-Bukhari, after being transmitted orally for generations. There are 7,658 full hadiths in this collection narrated by 1,755 narrators/transmitters.

Imam Bukhari finished his work around 846 A.D.

Content

The two main sources of data regarding hadith are works of hadith and works containing biographical information about hadith narrators. The dataset contains 7,658 hadiths in Arabic and the names of 1,755 transmitters. Imam Bukhari followed the following criterion to include a hadith in this book.

1. Quality and soundness of chain of narrators - the lifetime of a narrator should overlap with the lifetime of the authority from whom he narrates.

2. Verifiable - it should be verifiable that narrators have met with their source persons. They should also expressly state that they obtained the narrative from these authorities.

3. Piousness – he only accepted the narratives from only those who, according to his knowledge, not only believed in Islam but practiced its teachings.

Acknowledgements

More information on Hadith and Sahih Bukhari can be found from this link - Hadith Books

Inspiration

Here are some ideas worth exploring:

1. The traditional criteria for determining if a hadith is Sahih (authentic) requires that there should be an uninterrupted chain of narrators; that all those narrators should be highly reliable and there should not be any hidden defects. Can we make a social network graph of all the narrators and then timestamp it with their age and era to see who overlaps who?

2. The name of a transmitter mentioned in a given hadith is not the full name, and many transmitters have similar names. So identifying who is the transmitter of a given hadith based on the names mentioned in the text might be a good problem to tackle

3. Can we analyze the chains of transmitters for entire collections using Neo4j or some other graph database

4. There exist different chains that reports the same hadith with little variation of words, can you identify those

5. Can you link the text with other external data sources?

6. Can we produce the word cloud for each chapter of the book?

7. Can we train a neural network to authenticate if the hadith is real or not?

8. Can we find out the specific style or vocabulary of each narrator?

9. Can we develop a system for comparing variant wordings for the same hadith to identify how reliable a given transmitter is.

Please also help me extend this dataset. If you have any other hadith book in CSV or text format, please send me a message and I will add.

This study explores the phenomenon of Muslim apostasy from the perspective of self-described Muslim apostates. Drawing on life-history interviews with a group of ex-Muslims in Britain, it will provide a detailed qualitative account of what it means and what it is like for apostates to disaffiliate from Islam. It will also conduct interpretive narrative analysis of ex-Muslim published and online personal testimony, as well as semi-structured interviews with politically active Muslim 'career apostates'. The main focus of the study will be on the leaving-process and its ramifications as they are experienced and understood by apostates themselves. The key aims of the study are: to provide a close understanding of the experiences and narratives of Muslim apostates living in Britain to illuminate the dynamics by which individuals become Muslim apostates to describe the ramifications of apostatizing from Islam for the apostate and to document the various responses which the apostate's leave-taking provokes to map the political activities of Muslim 'career apostates', and to offer an account of their role. This study will be of interest not only to a broad range of sociologists, but also to policy-makers interested in the question of religious freedom, and social cohesion more broadly, in contemporary multicultural societies.

Accepted by NeurIPS 2024 Datasets and Benchmarks Track

We introduce the RePair puzzle-solving dataset, a large-scale real world dataset of fractured frescoes from the archaelogical campus of Pompeii. Our dataset consists of over 1000 fractured frescoes. The RePAIR stands as a realistic computational challenge for methods for 2D and 3D puzzle solving, and serves as a benchmark that enables the study of fractured object reassembly and presents new challenges for geometric shape understanding. Please visit our website for more dataset information, access to source code scripts and for an interactive gallery viewing of the dataset samples.