cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14841461
title: The Sampling Threat when Mining Generalizable Inter-Library Usage Patterns

description: Tool support in software engineering often relies on relationships, regularities, patterns, or rules mined from other users’ code. Examples include approaches to bug prediction, code recommendation, and code autocompletion. Mining is typically performed on samples of code rather than the entirety of available software projects. While sampling is crucial for scaling data analysis, it might influence the generalization of the mined patterns. This paper focuses on sampling software projects filtered for specific libraries and frameworks, and on mining patterns that connect different libraries. We call these inter-library patterns.

We observe that limiting the sample to a specific library may hinder the generalization of inter-library patterns, posing a threat to their use or interpretation. Using a simulation and a real case study, we demonstrate this threat for different sampling methods. Our simulation shows that only when sampling for the disjunction of both libraries involved in the implication of a pattern, the implication generalizes well. Additionally, we demonstrate that real empirical data sampled using the GitHub search API does not behave as expected from our simulation. This identifies a potential threat relevant for many studies that use the GitHub search API for studying inter-library patterns.
description: The data is under the Creative Commons Attribution Share-Alike 4.0 license. The source code is under the GNU General Public License.
DOI: 10.13130/rd_unimi/2hb4wc/nk4bca
title: outd
DOI: 10.13130/rd_unimi/2hb4wc/nwqnls
title: clevels
DOI: 10.13130/rd_unimi/2hb4wc/1b0cwa
title: proc2s
DOI: 10.13130/rd_unimi/2hb4wc/ulqy6i
title: HSQC.jdf
DOI: 10.13130/rd_unimi/2hb4wc/5hct3w
title: acqus
DOI: 10.13130/rd_unimi/2hb4wc/zt3qtd
title: 1r
DOI: 10.13130/rd_unimi/2hb4wc/kdqykf
title: ser
DOI: 10.13130/rd_unimi/2hb4wc/szsypc
title: auditp.txt
DOI: 10.13130/rd_unimi/2hb4wc/7y6tju
title: procs
DOI: 10.13130/rd_unimi/2hb4wc/geildv
title: scon2
DOI: 10.13130/rd_unimi/2hb4wc/ul1ijk
title: auditp.txt
DOI: 10.13130/rd_unimi/2hb4wc/xpkqfp
title: acqu2s
DOI: 10.13130/rd_unimi/2hb4wc/6cvxhs
title: scon2
DOI: 10.13130/rd_unimi/2hb4wc/npcbez
title: pulseprogram
DOI: 10.13130/rd_unimi/2hb4wc/l7ltxs
title: audita.txt
DOI: 10.13130/rd_unimi/2hb4wc/sll1hc
title: format.temp
DOI: 10.13130/rd_unimi/2hb4wc/chkerl
title: outd
DOI: 10.13130/rd_unimi/2hb4wc/siotmr
title: pulseprogram
DOI: 10.13130/rd_unimi/2hb4wc/nvpjyj
title: text
DOI: 10.13130/rd_unimi/2hb4wc/oesj6d
title: title
DOI: 10.13130/rd_unimi/2hb4wc/eqxjvc
title: log
DOI: 10.13130/rd_unimi/2hb4wc/ocfw08
title: text
DOI: 10.13130/rd_unimi/2hb4wc/77stbj
title: log
DOI: 10.13130/rd_unimi/2hb4wc/i6jysd
title: text
DOI: 10.13130/rd_unimi/2hb4wc/7xpgtd
title: text
DOI: 10.13130/rd_unimi/2hb4wc/cta1ij
title: fid
DOI: 10.13130/rd_unimi/2hb4wc/qhqylo
title: procpar
DOI: 10.13130/rd_unimi/2hb4wc/ubwwzx
title: procpar
DOI: 10.13130/rd_unimi/2hb4wc/og89py
title: procpar
DOI: 10.13130/rd_unimi/2hb4wc/mjzwke
title: fid
DOI: 10.13130/rd_unimi/2hb4wc/mrozyc
title: fid
DOI: 10.13130/rd_unimi/2hb4wc/mxxxcl
title: log
DOI: 10.13130/rd_unimi/2hb4wc/secdis
title: fid
DOI: 10.13130/rd_unimi/2hb4wc/44ir0c
title: log
DOI: 10.13130/rd_unimi/2hb4wc/brhgqi
title: procpar
DOI: 10.13130/rd_unimi/2hb4wc/5qnmdf
title: text
DOI: 10.13130/rd_unimi/2hb4wc/8g4hww
title: fid
DOI: 10.13130/rd_unimi/2hb4wc/6bm3a7
title: procpar
DOI: 10.13130/rd_unimi/2hb4wc/q9jbff
title: log
DOI: 10.13130/rd_unimi/2hb4wc/o3w3nm
title: readme.txt

description: Please read this file for details about data collection
DOI: 10.13130/rd_unimi/5fjqwh
title: Replication data for 'Mapping the pre-translation phase in publishing'

description: This is the replication dataset of a contribution that focuses on the pre-translation phase in publishing. This phase involves all the still ‘invisible’ actors in translation history that are indispensable to the commissioning and delivery of a translation and to its eventual publication in book form and proposes an integrated database that includes both submissions and publish titles. The data focuses on a case study on the reception of contemporary Italian fiction within British publishing in the period 1945-1970. We combine four datasets: one that includes published translations, sourced from (Healey 2019), ICCU and BNB, with others containing submissions made to three British publishers: Allen & Unwin, Jonathan Cape and The Bodley Head, sourced from archival records (see data/ part of the dataset). With this data, we model a database based around event logs (code/ part of the dataset), and we subsequently employ process mining and phenomenographic exploratory visualisations to capture respectively a dynamic and static view of the data (viz/ part).

For detailed information about this dataset, see &lt;a href="https://dataverse.unimi.it/api/access/datafile/175589"&gt;README.txt&lt;/a&gt; or refer to the related publications.
DOI: 10.13130/rd_unimi/5fjqwh/rhs8a3
title: editori.tab

description: additional researcher-sourced information about emerged titles. This was validated against records in Servizio Bibliotecario Nazionale (SBN) and British Library (BL).
DOI: 10.13130/rd_unimi/5fjqwh/0zh2og
title: JC MB 1-6.csv

description: Johnatan Cape's Manuscript Entry Books
DOI: 10.13130/rd_unimi/5fjqwh/eqzfml
title: Healey.tab

description: translations extracted from (Healey 1998)
DOI: 10.13130/rd_unimi/5fjqwh/3pttsy
title: BODLEYHEAD_RR_DATI.tab

description: Bodleyhead's Reader Reports
DOI: 10.13130/rd_unimi/5fjqwh/unrztj
title: ALLENUNWIN_MEB.tab

description: Allan & Unwin's Manuscript Entry Books
DOI: 10.13130/rd_unimi/5fjqwh/96ue9w
title: dbdump-20250707.sql.gz

description: a dated copy of the extraction allowing reproducibility of the data without the use of the proprietary ERA software
DOI: 10.13130/rd_unimi/5fjqwh/ltpcff
title: people.tab

description: cleaned and standardised names for the purposes of consistency
DOI: 10.13130/rd_unimi/5fjqwh/lbdhpy
title: books.tab

description: cleaned and standardised names for the purposes of consistency
DOI: 10.13130/rd_unimi/5fjqwh/ttkdlg
title: organisations.tab

description: cleaned and standardised names for the purposes of consistency
DOI: 10.13130/rd_unimi/5fjqwh/fp3hfh
title: Fig4-process-raw.svg

description: A graph representing the process flow discovered with process mining (raw file before post-processing as generated by the code).
DOI: 10.13130/rd_unimi/5fjqwh/g9sri9
title: Fig1-integrated_data.png

description: A sample selection of the collected data. This table is a screenshot of LibreOffice of sample data exported in Open Document Format
DOI: 10.13130/rd_unimi/5fjqwh/viw797
title: Fig6-alluvial.svg

description: Flows of the individual manuscripts (modifiable post-processed file).
DOI: 10.13130/rd_unimi/5fjqwh/hh4vjk
title: Fig3-datamodel.png

description: The employed event-centred data model represented in UML class diagram. Each box represents an entity. In brackets are the generic names used by ERA as seen in Figure 2. This figure was generated with https://www.umletino.com
DOI: 10.6084/m9.figshare.28794950
title: ­­­­Dataset and analysis syntax: Mysterious illnesses have supernatural and ritualistic cures: Evidence from 3,655 century-old Irish folk cures.

description: Dataset and analysis syntax associated with a project on religious and supernatural themes in folk medical cures.
DOI: 10.6084/m9.figshare.28794950.v2
title: ­­­­Dataset and analysis syntax: Mysterious illnesses have supernatural and ritualistic cures: Evidence from 3,655 century-old Irish folk cures.

description: Dataset and analysis syntax associated with a project on religious and supernatural themes in folk medical cures.
DOI: 10.13130/rd_unimi/5fjqwh/pszqzl
title: Fig5-author-reader.png

description: Which authors do readers read?
DOI: 10.13130/rd_unimi/5fjqwh/rfjbaj
title: Fig2-era-screenshot.png

description: A screenshot from the data entry screen of ERA. In the expanded menu at the left side, the generic data model of the application is visible. The ERA application is accessbile at http://era.islab.di.unimi.it
DOI: 10.6084/m9.figshare.28794950.v1
title: ­­­­Mysterious illnesses have supernatural and ritualistic cures: Evidence from 3,655 century-old Irish folk cures.

description: Dataset and analysis syntax associated with a project on religious and supernatural themes in folk medical cures.
DOI: 10.13130/rd_unimi/5fjqwh/bgivcp
title: Fig5-author-reader-raw.svg
DOI: 10.13130/rd_unimi/5fjqwh/h8lapi
title: Fig5-author-reader.svg

description: Which authors do readers read? (modifiable file)
DOI: 10.13130/rd_unimi/5fjqwh/7rng52
title: Fig4-process.svg

description: A graph representing the process flow discovered with process mining (modifiable post-processed file).
DOI: 10.13130/rd_unimi/5fjqwh/jrtvkq
title: Fig6-alluvial-raw.svg

description: Flows of the individual manuscripts (raw file before post-processing as generated by the code).
DOI: 10.13130/rd_unimi/5fjqwh/ty0whc
title: Fig4-process.png

description: A graph representing the process flow discovered with process mining.
DOI: 10.13130/rd_unimi/5fjqwh/4ckmcf
title: Fig3-datamodel.uxf

description: The modifiable raw file that can be imported in the tool and various formats could be exported, as was done with Fig3-datamodel.png
DOI: 10.13130/rd_unimi/5fjqwh/orhuzv
title: Fig6-alluvial.png

description: Flows of the individual manuscripts.
DOI: 10.13130/rd_unimi/5fjqwh/csqauv
title: extract-people-AU_MB.ipynb

description: append to the people.csv file
DOI: 10.13130/rd_unimi/5fjqwh/ppyksj
title: phenomenography-sankey.ipynb

description: generate Figure 6
DOI: 10.13130/rd_unimi/5fjqwh/ti1bo3
title: settings.py
DOI: 10.13130/rd_unimi/5fjqwh/uwrpq0
title: process-sqlalchemy.ipynb

description: perform analysis with process mining
DOI: 10.13130/rd_unimi/5fjqwh/0lcw9v
title: phenomenography-heatmap-person-from-to.ipynb

description: generate Figure 5
DOI: 10.13130/rd_unimi/5fjqwh/owpqo5
title: alias.py
DOI: 10.13130/rd_unimi/5fjqwh/hswhhl
title: db.py
DOI: 10.13130/rd_unimi/5fjqwh/y8fjfb
title: extract-books-healey.ipynb

description: create the books.csv file
DOI: 10.13130/rd_unimi/5fjqwh/fnm4l5
title: setup_db_sqlalchemy.ipynb

description: load clean people and book information
DOI: 10.13130/rd_unimi/5fjqwh/zqpz75
title: extract-agents-AU.ipynb

description: create the agents.csv file
DOI: 10.13130/rd_unimi/5fjqwh/6vxoq8
title: import_db_sqlalchemy_JC.ipynb

description: convert raw to DB
DOI: 10.13130/rd_unimi/5fjqwh/6z48en
title: extract-agents-JC.ipynb

description: append to the agents.csv file
DOI: 10.13130/rd_unimi/5fjqwh/emzegg
title: import_db_sqlalchemy_Healey.ipynb

description: convert raw to DB
DOI: 10.13130/rd_unimi/5fjqwh/gd0aja
title: import_db_sqlalchemy_BH.ipynb

description: convert raw to DB
DOI: 10.13130/rd_unimi/5fjqwh/qdi1jp
title: enrich-isni-wikidata.ipynb

description: adds the bulk of ISNI information to people.csv. The rest was inserted manually
DOI: 10.13130/rd_unimi/5fjqwh/laccxg
title: model.py
DOI: 10.13130/rd_unimi/5fjqwh/va9dfm
title: persist.py
DOI: 10.13130/rd_unimi/5fjqwh/ayd4qk
title: util.py
DOI: 10.13130/rd_unimi/5fjqwh/plw17c
title: extract-orgs-healey.ipynb

description: append to the organisations.csv file
DOI: 10.13130/rd_unimi/5fjqwh/08q1cg
title: extract-books-editori.ipynb

description: append to the books.csv file
DOI: 10.13130/rd_unimi/5fjqwh/a49yk2
title: extract-people-editori.ipynb

description: create the people.csv file
DOI: 10.13130/rd_unimi/5fjqwh/ssczmv
title: import_db_sqlalchemy_italian.ipynb

description: convert raw to DB
DOI: 10.13130/rd_unimi/5fjqwh/vmcyon
title: extract-people-healey.ipynb

description: append to the people.csv file
DOI: 10.13130/rd_unimi/5fjqwh/a6mtkx
title: extract-people-JC_MB.ipynb

description: append to the people.csv file
DOI: 10.13130/rd_unimi/5fjqwh/zxy5pc
title: compose.yml

description: simple database setup
DOI: 10.13130/rd_unimi/5fjqwh/dfqmua
title: import_db_sqlalchemy_ALLENUNWIN.ipynb

description: convert raw to DB
DOI: 10.13130/rd_unimi/5fjqwh/wt3set
title: extract-orgs-editori.ipynb

description: create the organisations.csv file
DOI: 10.13130/rd_unimi/5fjqwh/aznulw
title: README.txt
DOI: 10.13130/rd_unimi/3xccqu/jjyrur
title: DISEGNI1992-1986.pdf

description: DISEGNI1992-1986.pdf
DOI: 10.13130/rd_unimi/gijbvh
title: Replication Data For 'Giacomo Verde installazioni, tv interattive, net art, tecnoteatro (1992-2002)'
title: I disegni

description: Disegni di Giacomo Verde discussi nel volume di Anna Monteverdi sui disegni di Giacomo Verde 1992-2002
description: Giacomo Verde (Cimitile 1956-Lucca 2020), videoartista e tecnoperformer, ha dedicato tutta la vita alla creazione di un’arte sociale, impegnata e partecipata con uso delle tecnologie analogiche, digitali e della rete; Verde è stato un instancabile sperimentatore delle nuove tecnologie, pur privilegiando sempre l’uso di una tecnologia povera, alla portata di tutti, ogni volta reinventata in relazione alle mutate esigenze espressive. Il presente volume segue, a distanza di poco più di un anno, il precedente testo intitolato Giacomo Verde. Attraversamenti tra teatro e video (1986-1992), pubblicato sempre per Milano University Press. La ricerca è continuata in questo volume che intende mostrare il lavoro dell’artista nel periodo 1993-2003 attraverso materiali preparatori per le opere e le performance interattive che permettono di evidenziare l’importanza del disegno come medium sostanziale del processo creativo tecnologico di Verde. Il volume è preceduto da una pubblicazione analoga dal titolo Giacomo Verde. Attraversamenti tra teatro e video (1992-1986).
description: Disegni di libera diffusione. Citare la fonte @Archivio GiacomoVerde
DOI: 10.13130/rd_unimi/4vbvxt
title: CRAFTWORK_WP1_TwitterDataset__v01

description: The “Twitter Dataset” was developed within the framework of the CRAFTWORK project, coordinated by Alessandro Gandini at the University of Milan and funded by the European Union under the ERC Starting Grants 2020 (Horizon 2020 Programme). The overarching aim of the project is to investigate how identity and work intersect in the evolving context of the future of work, particularly focusing on the artisanal sector.

This dataset contains content collected from Twitter via the official Twitter API (v2), using the hashtags “#artisanal” and “#artisan” as search queries. The material includes textual, audiovisual, and numerical data extracted from posts, which were then manually reviewed and coded by the research team to identify themes relevant to the project’s goals.

The dataset is stored in a .csv file, formatted for use with spreadsheet software such as Microsoft Excel, and uses UTF-8 character encoding and comma delimiters. It consists of a curated collection of tweets from users based in the 27 European Union member states, focusing exclusively on accounts linked to commercial or artisanal activities.

Each entry in the dataset has been categorized according to several qualitative variables. These include the type of product associated with the tweet (such as food, ceramics, clothing, or woodwork), the presence of intermediary businesses, and thematic markers like “resignification” and “particularisation,” which relate to how artisanal work is framed in terms of authenticity, cultural value, and social distinction. Furthermore, each case was assessed for its relevance to the study and either included or excluded from the final sample based on specific criteria, which are also documented.

While the metadata is freely available under a CC0 license, access to the dataset itself requires a motivated request submitted directly to the principal investigator, and any use beyond the initial request must be explicitly authorized.
DOI: 10.13130/rd_unimi/bb90pj
title: CRAFTWORK_WP1_TikTokDataset__v01

description: The “TikTok Dataset” was developed as part of the CRAFTWORK research project, coordinated by Alessandro Gandini at the University of Milan and supported by the European Union through the ERC Starting Grants 2020 under the Horizon 2020 Programme. The project explores the evolving relationship between identity and work in contemporary society, with a particular emphasis on artisanal labor and its cultural significance.

This dataset comprises content collected from the social media platform TikTok, using an ad-hoc scraper that leverages the TikTok Web API to extract media and related metadata. The data was gathered by identifying posts that include the hashtags “#artisanal” and “#artisan” in the video captions. After collection, the dataset was manually reviewed and analyzed by the research team to identify patterns and themes consistent with the project’s research objectives.

The material is stored in a UTF-8 encoded, comma-separated .csv file, which can be opened using standard spreadsheet software such as Microsoft Excel. The file contains audiovisual, textual, and numerical data gathered from relevant TikTok posts published by users based in the 27 European Union member states. The dataset focuses exclusively on cases where the TikTok account is linked to a commercial or artisanal activity.

Each entry is categorized using a structured set of variables, including a pseudonymized ID, the country of origin, and the type of product featured, such as food, beauty items, clothing, ceramics, or woodcraft. The dataset also identifies narrative markers, including “resignification,” referring to how artisanal labor is framed as culturally valuable work, and “particularisation,” which signals references to authenticity and uniqueness. Each case is evaluated for its relevance to the study, and the reasons for inclusion or exclusion in the final analysis are documented.

While the metadata is publicly available under a CC0 license, full access to the dataset requires a motivated request addressed to the project’s principal investigator and cannot be shared beyond the initial requester without explicit permission.
DOI: 10.13130/rd_unimi/o1jnji
title: CRAFTWORK_WP1_FacebookDataset__v01

description: The “Facebook Dataset” was created as part of the CRAFTWORK research initiative, a project led by Alessandro Gandini at the University of Milan and funded by the European Union through the ERC Starting Grants 2020 within the Horizon 2020 framework. The project seeks to explore the evolving relationship between identity and work, particularly through the lens of artisanal production in the contemporary digital landscape.

This dataset contains data collected from Facebook using CrowdTangle, a dashboard owned by Meta that provides access to public content. The collection process focused on posts containing the hashtags “#artisanal” and “#artisan,” selected for their relevance to the project's thematic focus. The resulting data includes audiovisual, textual, and numerical information derived from Facebook posts made by users operating within the 27 member states of the European Union.

The dataset is saved in a UTF-8 encoded .csv file, which can be opened using Microsoft Excel or other spreadsheet tools. It was compiled using Office 16 Excel with English as the designated language and comma as the field delimiter. The content was then manually reviewed by the research team, which applied a set of predefined variables to categorize and analyze the posts.

Each entry includes a pseudonymized ID, geographic origin, and identification of whether the Facebook account is linked to a commercial or artisanal activity. The dataset also classifies the type of product featured—such as food, ceramics, fashion, hospitality, or woodworking—and assesses the presence of narrative features like “resignification” and “particularisation.” These concepts relate to how artisanal labor is culturally framed in terms of authenticity, creativity, and value. The dataset also documents whether each case was considered “interesting” for final inclusion, along with an explanation for that decision.

While the metadata is publicly available under a CC0 license, access to the dataset itself requires a motivated request and explicit approval from the principal investigator, and the data cannot be further shared without authorization.
DOI: 10.13130/rd_unimi/s2d0gh
title: README_CRAFTWORK_WP1_InstagramDataset__v01

description: This dataset includes content collected from Instagram via CrowdTangle, a dashboard owned by Meta that enables access to public posts. The data was gathered by searching for posts containing the hashtags “#artisanal” and “#artisan,” which were selected for their relevance to the project’s thematic focus. The collected material encompasses audiovisual, textual, and numerical data and reflects content published by users based in the 27 EU member states.

The data is organized in a UTF-8 encoded comma-separated (.csv) file, which can be opened using Microsoft Excel or other spreadsheet programs. The file was created using Office 16 Excel and follows standard formatting conventions. After data collection, the research team manually analyzed and coded the posts according to a defined set of variables designed to capture relevant sociocultural and commercial aspects.

Each case in the dataset is associated with a pseudonymized ID, geographic location, and an indication of whether the Instagram account is linked to a commercial activity. It also includes the type of product showcased—ranging from food and fashion to ceramics and woodwork—and identifies whether the post contains elements of “resignification” or “particularisation.” These narrative indicators reflect how artisanal work is positioned as culturally meaningful or uniquely authentic. The dataset also specifies which cases were deemed “interesting” for final inclusion, along with the reasons behind those decisions.

The metadata is openly licensed under CC0, but access to the dataset itself requires a motivated request and the explicit authorization of the project’s principal investigator.
DOI: 10.13130/rd_unimi/xzylzf
title: CRAFTWORK_WP1_NCIDirectory__v01

description: The “NCI Directory Dataset” is part of the CRAFTWORK research project, led by Alessandro Gandini at the University of Milan and funded by the European Union through the ERC Starting Grants 2020 under the Horizon 2020 Programme. The project investigates how identity and work intersect in the contemporary context of artisanal production and the digital economy, with a focus on new forms of craft and their representation on social media.

This dataset comprises two distinct but complementary files. The first file presents a curated selection of 346 “neo-craft” cases identified and analyzed by the research team. These cases were sourced from five major digital platforms—YouTube, Instagram, Twitter, TikTok, and Facebook—and include textual, audiovisual, and numerical data. The second file contains a list of cultural intermediaries, such as influencers or bloggers, primarily identified through Instagram, who play a role in promoting or mediating the visibility of artisanal work online.

Both files are stored in comma-separated (.csv) format with UTF-8 encoding and are compatible with spreadsheet software like Microsoft Excel. Each dataset was compiled and manually analyzed using a consistent set of variables designed to categorize and interpret the content in relation to the project’s research themes.

The first dataset includes variables such as a pseudonymized ID, the EU country and location of the profile, the associated product or activity, the platform it was sourced from, and whether it was considered relevant to the study’s definition of neo-craft. The second dataset includes similar fields but adds a measure of popularity (number of followers) and classifies whether the profile operates as a commercial intermediary.

While the metadata is openly licensed under CC0, access to the full dataset is restricted to those who submit a motivated request to the principal investigator.