Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
89
datasets available to search
ShareScore release 0.9.0
Dataset results
89 results for “Authorship”
Figure 1 in The taxonomic catalog of the Brazilian fauna: Dermaptera and Phasmatodea (Insecta), with commentaries on species list, types, authorship and distribution
Figure 1. Number of species by biome: (A) Dermaptera; (B) Phasmatodea.
Dataset of "Gender analysis and co-authorship networks in the scientific production of oncology in Spain (2011–2021)"
Open the record for dataset details and reuse information.
A visualization of co-authorship network of mathematicians with an Erdős number of at most 2
<p>Co-authorship network of mathematicians with an Erdős number of at most 2</p> <p>Based on the data available at: https://oakland.edu/enp/thedata/erdos1.</p> <p>As can be seen, Erdős has collaborated directly or through an intermediary with different groups of scientists.<br> Researchers in the field of graph and computer science (gold), specialists in number theory (pink), mathematicians in the field of set theory (blue), researchers in the field of computer engineering (green) and the isolated group of Peter Salamon and his colleagues are the main groups of these researchers.<br> The names of researchers with more than 190 colleagues in the network (the first 10% of researchers) are written in the figure.</p> <p>See https://sites.google.com/oakland.edu/grossman/home/the-erdoes-number-project/the-erdoes-number-project-data-files.</p> <p>This artifact is a part of https://math-sci.ui.ac.ir/article_25684.html.</p>
Reproducible Authorship Attribution Benchmark Tasks
<p>Reproducible Authorship Attribution Benchmark Tasks (RAABT) consists of five closed-set authorship identification experiments.</p> <p>Each task features fixed train and test sets. Four of the five tasks have a test set consisting of writing samples on fixed topics, guaranteeing that test set examples do not overlap with training set examples in terms of subject matter. Data for all tasks is available for download without any restrictions.</p> <p>The file README.md contains a full description of the data.</p>
'Psyché' as a Rosetta stone? Assessing collaborative authorship in the French 17th century theatre -- supplementary material
<p>Supplementary material for the paper:</p> <p>‘Psyché’ as a Rosetta Stone? Assessing Collaborative Authorship in the French 17th Century Theatre</p> <p>presented at Computational Humanities Research 2021.</p>
Authorship Attribution - Twitter - 2019
<p>Dataset of tweets used for the research of authorship attribution of small messages. It was used in the work <a href="https://ieeexplore.ieee.org/document/8683747"><em>A Needle in a Haystack? Harnessing Onomatopoeia and User-specific Stylometrics for Authorship Attribution of Micro-messages</em></a> published at <a href="https://2019.ieeeicassp.org/"><em>2019 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP</em></a></p> <p> </p> <p>Format:</p> <p>A single file with one tweet ID per line. Total of 130,141,590 tweet IDs from more than 55,000 Twitter users.</p> <p>The tweets can be recovered from Twitter (hydrated) using the Twitter API or the code at <a href="https://github.com/theocjr/twitter-reader">twitter-reader</a>.</p>
Dataset for proceedings paper: How international is co-authorship outside of Web of Science? The case of social sciences and humanities in Flanders, Belgium
<p>This is an anonymized dataset containing data on international collaboration in the social sciences and humanities (SSH) in Flanders, Belgium. It is based on all peer-reviewed publications in <a href="https://www.ecoom.be/en/data-collections/vabb-shw">VABB-SHW</a>, regardless of their indexation in WoS or other databases.</p> <p>The dataset accompanies the conference paper 'How international is co-authorship outside of Web of Science? The case of social sciences and humanities in Flanders, Belgium,' which was submitted to <a href="https://cns-iu.github.io/workshops/2023-07-02_issi/index.html">ISSI 2023</a>.</p>
Data on Authorship Gender in Ranked, Unranked, and Interdisciplinary Philosophy Journals (JSTOR Database, 1900-2010)
Open the record for dataset details and reuse information.
Data from: Games academics play and their consequences: how authorship, h-index, and journal impact factors are shaping the future of academia
Open the record for dataset details and reuse information.
International comparison of cross-disciplinary integration in industry 4.0: A co-authorship analysis using academic literature databases
Open the record for dataset details and reuse information.
PAN19 Authorship Analysis: Cross-Domain Authorship Attribution
<p>Authorship attribution is an important problem in information retrieval and computational linguistics but also in applied areas such as law and journalism where knowing the author of a document (such as a ransom note) may enable e.g. law enforcement to save lives. The most common framework for testing candidate algorithms is the closed-set attribution task: given a sample of reference documents from a restricted and finite set of candidate authors, the task is to determine the most likely author of a previously unseen document of unknown authorship. This task may be quite challenging in <strong>cross-domain conditions</strong>, when documents of known and unknown authorship come from different domains (e.g., thematic area, genre). In addition, it is often more realistic to assume that the true author of a disputed document is not necessarily included in the list of candidates.</p> <p><strong>Fanfiction</strong> refers to fictional forms of literature which are nowadays produced by admirers ('fans') of a certain author (e.g. J.K. Rowling), novel ('Pride and Prejudice'), TV series (Sherlock Holmes), etc. The fans heavily borrow from the original work's theme, atmosphere, style, characters, story world etc. to produce new fictional literature, i.e. the so-called <strong>fanfics</strong>. This is why fanfiction is also known as transformative literature and has generated a number of controversies in recent years related to the intellectual rights property of the original authors (cf. plagiarism). Fanfiction, however, is typically produced by fans without any explicit commercial goals. The publication of fanfics typically happens online, on informal community platforms that are dedicated to making such literature accessible to a wider audience (e.g. <a href="https://www.fanfiction.net/">fanfiction.net</a>). The original work of art or genre is typically refered to as a <strong>fandom</strong>.</p> <p>This edition of PAN focuses on cross-domain attribution in fanfiction, a task that can be more accurately described as <strong>cross-fandom attribution in fanfiction</strong>. In more detail, all documents of unknown authorship are fanfics of the same fandom (target fandom) while the documents of known authorship by the candidate authors are fanfics of several fandoms (other than the target-fandom). In contrast to the PAN-2018 edition of this task, we focus on <strong>open-set attribution</strong> conditions, namely the true author of a text in the target domain is not necessarily included in the list of candidate authors.</p> <p>Each problem consists of a set of known fanfics by each candidate author and a set of unknown fanfics located in separate folders. The file <code>problem-info.json</code> that can be found in the main folder of each problem, shows the name of folder of unknown documents and the list of names of candidate author folders.</p> <p>The fanfics of known authorship belong to several fandoms (excluding the target fandom). The file <code>fandom-info.json</code> (it can be found in the main folder of each problem) provides information about the fandom of all fanfics of known authorsihp, as follows.</p> <p>The true author of each unknown document can be seen in the file <code>ground-truth.json</code>, also found in the main folder of each problem. Note that all unknown documents that are not written by any of the candidate authors belong to the <code><UNK></code> class.</p> <p>In addition, to handle a collection of such problems, the file <code>collection-info.json</code> includes all relevant information. In more detail, for each problem it lists its main folder, the language (either <code>"en"</code>, <code>"fr"</code>, <code>"it"</code>, or <code>"sp"</code>), and the encoding (always <code>UTF-8</code>) of documents.</p>
PAN20 Authorship Analysis: Celebrity Profiling
<p><strong>Synopsis</strong></p> <ul> <li>Task: Given the Twitter feeds of the followers, determine the occupation, age, and gender of a celebrity.</li> <li>Evaluation: [<a href="https://github.com/pan-webis-de/pan-code/tree/master/clef20/celebrity-profiling">code</a>]</li> <li>Baselines: [code]</li> <li>See the full Shared Task [<a href="https://pan.webis.de/clef20/pan20-web/celebrity-profiling.html">here</a>]</li> </ul> <p>The datasets contain three files: a <code>follower-feeds.ndjson</code> as input, a <code>labels.ndjson</code> as output, and a <code>celebrity-feeds.ndjson</code> for additional study. Each file lists all celebrities as JSON objects, one per line and identified by the <code>id</code> key. The training dataset contains 1,920 celebrities and is balanced towards gender and occupation. The supplement dataset contains the remaining 8,265 celebrities but is not balanced in any way.</p> <p> </p> <p>The <code>follower-feeds.ndjson</code> contains the English tweets of at least 10 followers for each celebrity, with at least 50 tweets each excluding retweets.</p> <pre><code class="language-json">{"id": 1234, "text": [["a tweet of follower 1", "another tweet of follower 1", ...], ["a tweet of follower 2", ...], ...]} {"id": 5678, "text": [["a tweet of follower 1", "another tweet of follower 1", ...], ["a tweet of follower 2", ...], ...]}</code></pre> <p> </p> <p>The <code>celebrity-feeds.ndjson</code> contains the Twitter timelines of the original celebrities, formatted as:</p> <pre><code class="language-json">{"id": 1234, "text": ["a tweet of celebrity 1", "another tweet of celebrity 1", ...]} {"id": 5678, "text": ["a tweet of celebrity 2", "another tweet", ...]}</code></pre> <p> </p> <p>The <code>labels.ndjson</code> contains the classes that should be predicted. A valid submission has to produce a <code>labels.ndjson</code> given the <code>follower-feeds.ndjson</code> and contain an entry for each <code>id</code> given in the input.</p> <pre><code class="language-json">{"id": 1234, "occupation": "sports", "gender": "female", "birthyear": 2002} {"id": 5678, "occupation": "professional", "gender": "male", "birthyear": 1990}</code></pre> <p>The following values are possible for each of the traits:</p> <pre><code>occupation := {sports, performer, creator, politics} birthyear := {1940, ..., 1999} gender := {male, female}</code></pre> <p> </p>
FIGURE 3 in On the identity, nomenclatural status and authorship of Coluber monticolus Cantor, 1839 (Reptilia: Serpentes)
FIGURE 3. Oligodon arnensis, adult, from Palakkad, Kerala state, India, ~ 90 m a.s.l.; courtesy K. P. Rajkumar.
FIGURE 2 in On the identity, nomenclatural status and authorship of Coluber monticolus Cantor, 1839 (Reptilia: Serpentes)
FIGURE 2. Original painting (referred to as Fig. 11 in Cantor's manuscript, but no. 13 on the sheet) of the holotype of Coluber monticolus Cantor, 1839 from his original manuscript entitled "Indian Serpents–Innocuous–Collected, figured & described (1831–1837)", kept in the Bodleian Library, Oxford, U.K. (see Appendix Note 1). Reproduced with permission from the Bodleian Library, Oxford, U.K.
FIGURE 5 in On the identity, nomenclatural status and authorship of Coluber monticolus Cantor, 1839 (Reptilia: Serpentes)
FIGURE 5. Boiga multifasciata, adult female, grey morphotype, from near Birethanti, Kaski District, Gandaki Zone, Nepal, 1055 m a.s.l.
FIGURE 4 in On the identity, nomenclatural status and authorship of Coluber monticolus Cantor, 1839 (Reptilia: Serpentes)
FIGURE 4. Boiga multifasciata, adult female, brown morphotype, from Phulchoki Mountain, Lalitpur District, Bagmati Zone, Nepal, ~ 2000 m a.s.l.
FIGURE 1. Virtual extract from a water-colour painting from Brian H in On the identity, nomenclatural status and authorship of Coluber monticolus Cantor, 1839 (Reptilia: Serpentes)
FIGURE 1. Virtual extract from a water-colour painting from Brian H. Hodgson`s collection of drawings kept in the Zoological Library of the Natural History Museum, London, U.K. The depicted specimen from the "Hills at Nipal" was determined by Albert C. L. Günther as "? Simotes russelli", a taxon presently regarded as a synonym of Oligodon arnensis (Shaw, 1802). In fact, the drawing shows a specimen of the brown morphotype of the Many-banded cat snake, Boiga multifasciata (Blyth, 1860). Artist unknown. Source: Library and Archives, Natural History Museum, London.
ELTeC for Authorship Attribution
<p>Selected texts from multiple ELTeC collections, prepared as simple test datasets for authorship attribution. Each set contains between 24 and 33 novels by 8 to 11 different authors (3 novels per author) in plain text. The languages represented are English, German, French, Hungarian, Portuguese, Slovenian, Romanian. </p>
FIGURE 1 in Authorship and date of publication of the name Scarabaeus stercorosus (currently Anoplotrupes stercorosus) (Coleoptera: Scarabaeoidea: Geotrupidae)
FIGURE 1. Wrapper of the third issue of "Journal für die Liebhaber der Entomologie", held by the Bayerische Staatsbibliothek, Munich, Germany.
FIGURE 1. A in The works on echinoids by Klein and Leske, the confusion concerning the authorship of Klein (1778), and the problem of citation of some species
FIGURE 1. A: Title page of Klein's Naturalis Dispositio Echinodermatum, 1734. B: Portrait of Klein, aged 59 in 1743, from the French Edition, 1754. C: Title page of the1778 Edition of Klein's Naturalis Dispositio Echinodermatum. D: Title page of Leske's Additamenta, 1778. All from the author's copies of the original works. A, C, and D are Crown Quarto size, B is Crown Octavo.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.