Find research datasets worth reusing

opencc-by-4.0Jun 2017View details →

Sketches and Diagrams in Practice — Supplementary Material

Sketches and diagrams play an important role in the daily work of software developers. In our paper "Sketches and Diagrams in Practice" we present the results of our research on the usage of sketches and diagrams in software engineering practice. We focused especially on their relation to the core elements of a software project, the source code artifacts. Furthermore, we wanted to assess how helpful sketches are for understanding the related source code. We intended to find out if, how, and why sketches and diagrams are archived and are thereby available for future use. Software is created with and for a wide range of stakeholders. Since sketches are often a means for communicating between these stakeholders, we were not only interested in sketches and diagrams created by software developers, but by all software practitioners, including testers, architects, project managers, as well as researchers and consultants. In a survey with 394 software ‘practitioners’, we mainly asked questions about the the last sketch or diagram that they had created. Contrary to our expectations and previous work, the majority of sketches and diagrams contained at least some UML elements. However, most of them were informal. The most common purposes for creating sketches and diagrams were designing, explaining, and understanding, but analyzing requirements was also named often. More than half of the sketches and diagrams were created on analog media like paper or whiteboards and have been revised after creation. Most of them were used for more than a week and were archived. About half of the sketches were rated as helpful to understand the related source code artifact(s) in the future. Our study complements a number of existing studies on the use of sketches and diagrams in software development, which analyzed the above aspects only in parts and often focused on an academic environment, a single company, open source projects, or were limited to a small group of participants. The questionnaire for the online survey was online from August 28, 2013 until December 31, 2013. Further information on our research design and research questions can be found in the referenced paper. This dataset contains the questionnaire, the data we collected during this survey, and a basic R script that can be used as a starting point for validating our results and further exploring the data. This data set has been reviewed and accepted by the Artifact Evaluation Committee of FSE 2014. Since we assured our participants that their data is handled confidentially, only the quantitative data is directly available here. If you are also interested in the qualitative data from our survey, don’t hesitate to contact the authors.

opencc-by-4.0Aug 2023View details →

Phlorest phylogeny derived from Lee 2015 'A Sketch of Language History in the Korean Peninsula'

Cite the source of the dataset as: <blockquote> Lee S (2015) A Sketch of Language History in the Korean Peninsula. PLoS ONE 10(5): e0128448. doi:10.1371/journal.pone.0128448 </blockquote>

opencc-by-4.0Apr 2024View details →

A SAT Benchmark Suite for LTL Specification Sketching

<h1>LTL_Sketcher-SAT_Benchmark</h1> This repository contains a set of formulas in Propositional Boolean Logic. These formulas are generated during the execution of our <a href="https://github.com/rajarshi008/LTLSketcher/tree/master" target="_blank" rel="noopener">LTLSketcher tool</a>. Given an LTL sketch (i.e., a partial LTL formula) and a sample (i.e., a set of program executions labeled desired and undesired), the tool solves the LTL sketching problem, i.e., complete the sketch to a specification consistent with the data. (feel freet to check out our <a href="https://link.springer.com/chapter/10.1007/978-3-031-45332-8_2" target="_blank" rel="noopener">paper</a> for more information on this problem) In essence, this is done by reducing the problem to a series of formulas in Propositional Boolean Logic and checking their satisfiability. <h2>Naming convention:</h2> This repository contains each formula both in the DIMACS and SMTLib format. Each file follows the same naming convention: type__sample-file__sketch__size__algorithm-configuration__satisifability type: indicates whether the formula is stored in the DIMACS or SMTLib format sample-file: refers to the sample (cf., <a href="https://github.com/rajarshi008/LTLSketcher/tree/master/experiment_results/generated_files/final_benchmark" target="_blank" rel="noopener">here</a>) used by the LTLSketcher tool sketch: refers to the sketch (cf., See experimental evaluation of our <a href="https://link.springer.com/chapter/10.1007/978-3-031-45332-8_2" target="_blank" rel="noopener">paper</a>) used by the LTLSketcher tool size: refers to the size of the complete solution (i.e., the number of subformulas of the complete specification) algorithm-configuration: our algorithm can be extended by two heuristics (BMC and suffix), this indicates which combination of heuristics was used (none, either one of the two, both) satisfiability: indicates whether the formula is satisfiable or not

opencc-by-4.0Jul 2021View details →

CLDF dataset derived from Lee's "Sketch of Language History in the Korean Peninsula" from 2015

Cite the source of the dataset as: <blockquote> Lee, Sean (2015). A Sketch of Language History in the Korean Peninsula. PLoS ONE 10(5): e0128448. doi:10.1371/journal.pone.0128448 </blockquote>

opencc-by-4.0Oct 2024View details →

The I.Sicily Sketch Engine corpus (early imperial funerary inscriptions)

The dataset covers the 723 early imperial (1 BC to AD 401) funerary and honorific inscriptions in Greek, Latin, and Hebrew from the I.Sicily database. These are provided in the .conllu and .vert formats.

opencc-by-4.0Dec 2021View details →

Text-fig. 1. a: Idealised section of the Intra-Sudetic Basin (from Opluštil et al. 2016); b: Geological sketch map of the IntraSudetic Basin, here simplified (after Prouza and Tásler 2001, Pešek 2004). Explanations: 1 – Bohdašín Formation (Triassic), 2 – Bohuslavice Formation (Thuringian), 3 – Trutnov Formation (Saxonian), 4–13 Broumov Formation (Autunian): 4 – Martínkovice Member, 5 – Martínkovice Member with Jetřichovice, Hejtmánkovice and Vižňov horizons, 6–13 – Olivětín Member: 6 – Walchia bone coal facies, 7 – Basaltoides of the Šonov Group, 8 – Volcanoclastic facies, 9 – Aleuropelites, 10 – Ignimbrites, 11 – Rhyolite tuffs, 12 – Ruprechtice Limestone Horizon, 13 – Otovice Limestone Horizon. Localities: O1 – Otovice "Černý potok", O2 – Otovice "Stěnava", O3 – Otovice "Chmelnice", O4 – Otovice "Vápenka", R1 – Ruprechtice "Vápencové lomy", R2 – Ruprechtice "Pod Světlinou", R3 – Olivětín "Nad náhonem". in Actinopterygians Of The Broumov Formation (Permian) In The Czech Part Of The Intra-Sudetic Basin (The Czech Republic)

Text-fig. 1. a: Idealised section of the Intra-Sudetic Basin (from Opluštil et al. 2016); b: Geological sketch map of the IntraSudetic Basin, here simplified (after Prouza and Tásler 2001, Pešek 2004). Explanations: 1 – Bohdašín Formation (Triassic), 2 – Bohuslavice Formation (Thuringian), 3 – Trutnov Formation (Saxonian), 4–13 Broumov Formation (Autunian): 4 – Martínkovice Member, 5 – Martínkovice Member with Jetřichovice, Hejtmánkovice and Vižňov horizons, 6–13 – Olivětín Member: 6 – Walchia bone coal facies, 7 – Basaltoides of the Šonov Group, 8 – Volcanoclastic facies, 9 – Aleuropelites, 10 – Ignimbrites, 11 – Rhyolite tuffs, 12 – Ruprechtice Limestone Horizon, 13 – Otovice Limestone Horizon. Localities: O1 – Otovice "Černý potok", O2 – Otovice "Stěnava", O3 – Otovice "Chmelnice", O4 – Otovice "Vápenka", R1 – Ruprechtice "Vápencové lomy", R2 – Ruprechtice "Pod Světlinou", R3 – Olivětín "Nad náhonem".

opencc-by-4.0Aug 2022View details →

Text-fig. 2. Nymphaea sp. from the Miocene Clarkia Lake flora, Locality P-33. a: Photograph of the fossil leaf. b: Sketch of leaf showing the salient features of shape, basal lobes and margin, eccentric insertion point of the abaxial petiole, and primary actinodromous venation. Dashed lines represent torn edge of lamina; dotted line is outline of right basal lobe. Line drawing by P. Martin Sander. Scale bar applies to both photo and drawing. in First Water Lily, A Leaf Of Nymphaea Sp., From The Miocene Clarkia Flora, Northern Idaho, Usa: Occurrence, Taphonomic Observations, Floristic Implications

Text-fig. 2. Nymphaea sp. from the Miocene Clarkia Lake flora, Locality P-33. a: Photograph of the fossil leaf. b: Sketch of leaf showing the salient features of shape, basal lobes and margin, eccentric insertion point of the abaxial petiole, and primary actinodromous venation. Dashed lines represent torn edge of lamina; dotted line is outline of right basal lobe. Line drawing by P. Martin Sander. Scale bar applies to both photo and drawing.

opencc-by-4.0Dec 2019View details →

Рис. 2. Laternula elliptica: А – раковина вЗрослого моллюска иЗ морЯ Дейвиса, L=87 мм, вид сбоку; Б – вид с дорсальной стороны (по: Егорова [1982]); В – расположение пустых раковин Laternula elliptica в осыпаюЩемсЯ песчаном грунте на склоне подводного холма (по рисунку иЗ полевого дневника Б.И. Сиренко, ЗИН РАН); Г – наружные отверстиЯ вводного и выводного сифонов Laternula elliptica (King, 1832) на поверхности грунта. Fig. 2. Laternula elliptica: А – shell of adult mollusc from the Davis Sea, L=87 mm, lateral view; Б – dorsal view (after: Егорова [1982]); В – empty shells of Laternula elliptica in friable sand on a slope of underwater hill (after sketch in the field journal of Dr. B.I. Sirenko, Zool. Inst. RAS); Г – external openings of inhalant and exhalant siphons of Laternula elliptica on surface of bottom deposits. in Species of warm-water origin Laternula elliptica (King, 1832) (Mollusca: Bivalvia: Laternulidae), a widespread mollusk in recent Antarctica

Рис. 2. Laternula elliptica: А – раковина вЗрослого моллюска иЗ морЯ Дейвиса, L=87 мм, вид сбоку; Б – вид с дорсальной стороны (по: Егорова [1982]); В – расположение пустых раковин Laternula elliptica в осыпаюЩемсЯ песчаном грунте на склоне подводного холма (по рисунку иЗ полевого дневника Б.И. Сиренко, ЗИН РАН); Г – наружные отверстиЯ вводного и выводного сифонов Laternula elliptica (King, 1832) на поверхности грунта. Fig. 2. Laternula elliptica: А – shell of adult mollusc from the Davis Sea, L=87 mm, lateral view; Б – dorsal view (after: Егорова [1982]); В – empty shells of Laternula elliptica in friable sand on a slope of underwater hill (after sketch in the field journal of Dr. B.I. Sirenko, Zool. Inst. RAS); Г – external openings of inhalant and exhalant siphons of Laternula elliptica on surface of bottom deposits.

opencc-by-4.0Apr 2024View details →

Sketch With the Robot - data

This repository holds the data collected during the experimental sessions for the project "Sketch it for the robot! How child-like robots' joint attention affects humans' drawing strategies" accepted at ICDL (2024) Conference.  The repository contains the drawings of the categories, the raw data file, the quantitative data file and elaborated data for the analysis. <ul> <li>The folder /Experimental_data  contains: <ul> <li>The folder /no_robot contains all the the drawings (.png format), produced in the individual condition, organized in subfolders. Each subfolder corresponds to a participant and the presence of the 'i' in the name means the partcipant was Italian , while the presence of the 's' means that the participant was Slovakian.</li> <li>The folder /robot contains all the the drawings (.png format), produced in the robot condition, organized in subfolders. As the previous case, the letter 'i' and 's' stands for the nationality of the participant.</li> <li>The file all_drawings.ndjson contains all the raw data (all the coordinates and timestamp of each drawing), where we also included the features extraction data. Thanks to the raw data (triplets (x, y, t)) it is possible to extract all the features needed.</li> <li>The file quantitative_data.ndjson contains all the quantitative rankings data collected during the experiment (category, condition, latency time, total time, number of strokes, enjoyment_rank, difficulty_rank, likeability_rank).</li> </ul> </li> <li>The folder /Analysis_data contains the datasets used for the analysis. They are basically subsets specifically generated for the different analysis, containing all the features extraction and questionnaires data: <ul> <li>The file all_drawings_social_influence_all.csv is the 'mother' file containing all the relevant data.</li> <li>The file all_drawings_social_influence_no_repetitions.csv contains the data relative to the categories that were drawn just 1 time. The file has been generated to study the effects of the social influence due to the robot's presence.</li> <li>The file all_drawings_social_influence_only_repetitions.csv contains data relative just to the categories that were drawn more than 1 time. This file has been generated to compare results between categories repeated 2 and 3 times, to highlight the effect introduced by repeating a category for the third time.</li> <li>The file all_drawings_repetition_influence.csv contains data relative to just the categories repeated 3 times, to study the repetition effect.</li> </ul> </li> </ul> It is possible to finde the code used to collect the data at the DOI: 10.5281/zenodo.10944480

opencc-by-4.0Jan 2018View details →

Fig. 5. Microstomum rubromaculatum von Graff, 1882, composite sketches. A in Microstomum (Platyhelminthes, Macrostomorpha, Microstomidae) from the Swedish west coast: two new species and a population description

Fig. 5. Microstomum rubromaculatum von Graff, 1882, composite sketches. A. Ventral view of entire body. B. Lateral view of posterior end. C. Lateral view of stylet. D. Ventral view of stylet. Abbreviations: a = auricles (ciliary pits); am = antrum masculinum; ap = adhesive papillae; b = brain; eg = egg; fp = female pore; i = intestine; m = mouth; mp = male pore; o = ovary; ph = pharynx; s = sperm; st = male stylet; t = testis; vs = vesicula seminalis.

BRAIN Journal-Image Finder Mobile Application Based on Neural Networks-Figure 8. Training Neural Network for Sketches

It is described in the previous section that a mobile application is used to collect data about the sketches and the data is converted to 20x20=400 integer numbers to give it as input to Weka. Our experimentation includes only two objects for recognition i.e. trees and cars. Total tree sketches used = 175 Total car sketches used = 72 Learning rate = 0.3 Momentum = 0.2 Number of epochs = 500 70% of data is used to train the neural network and the remaining 30% is used for testing the trained neural network. Figure 8 shows the neural network for sketches. The results are shown in Figure 9 and are as follows: Total Correct Recognition = 100%

BRAIN Journal-Image Finder Mobile Application Based on Neural Networks-Figure 5. Cropped Sketch

Figure 5 shows the interface of the mobile application that is created to collect the data of the sketches. It contains a drawing canvas; where drawings are made and it also contains few text boxes which are filled with the information of the drawing. For example, if the drawing is a tree, ‘1’ is written in the tree text box. Furthermore, the undo and redo buttons help modify the drawing and the clear button clears everything drawn onto the drawing canvas.  The drawing of a tree is shown on the drawing canvas in Figure 4. It is clear from the figure that there is some empty area on top, right, left and bottom of the drawing sketch, which can cause problems while using this image for training the neural network. Therefore, there is implemented a crop function which crops the image very minutely and removes the empty space as shown in Figure 5.

BRAIN Journal-Image Finder Mobile Application Based on Neural Networks-Figure 4. Mobile Application to collect Sketch data

The drawing of a tree is shown on the drawing canvas in Figure 4. It is clear from the figure that there is some empty area on top, right, left and bottom of the drawing sketch, which can cause problems while using this image for training the neural network.

BRAIN Journal-Image Finder Mobile Application Based on Neural Networks-Figure 6. Reducing size of Sketch

As previously described, there are a total of 1600 integers, which can be the input to the dataset for neural networks. But it is a huge number, so in order to minimize the size of inputs to the neural network the 40x40 matrix is reduced to 20x20 by skipping odd rows and columns of the original matrix. Figure 6 shows a matrix containing green and red rows and columns. If this was the 40x40 matrix, then the red part of this matrix would be skipped to convert it into a 20x20 sized matrix. Now there are only 20x20=400 values, which is a reasonable input size for the neural network.  The other part of the developed approach is to collect the data about the same two objects of the real pictures taken by the camera. These images are converted into black and white pictures and then treated the same way as the sketches, i.e. black and white pictures are also converted into integers based on the color of each pixel.

BRAIN Journal-Image Finder Mobile Application Based on Neural Networks-Figure 9. Weka Results for Sketches

the sketches and the data is converted to 20x20=400 integer numbers to give it as input to Weka. Our experimentation includes only two objects for recognition i.e. trees and cars. Total tree sketches used = 175 Total car sketches used = 72 Learning rate = 0.3 Momentum = 0.2 Number of epochs = 500 70% of data is used to train the neural network and the remaining 30% is used for testing the trained neural network. Figure 8 shows the neural network for sketches. The results are shown in Figure 9 and are as follows: Total Correct Recognition = 100%

opencc-by-4.0Dec 2013View details →

Text-fig. 1a. Frič's first sketch of the new building and its internal layout. (ANM, fund A. Frič, PK 4, fol. 23). / První Fričovy nákresy budovy muzea a jeho vnitřního uspořádání. (ANM, fond A. Frič, PK 4, fol. 23). in Frič Museum In Lázně Bělohrad

Text-fig. 1a. Frič's first sketch of the new building and its internal layout. (ANM, fund A. Frič, PK 4, fol. 23). / První Fričovy nákresy budovy muzea a jeho vnitřního uspořádání. (ANM, fond A. Frič, PK 4, fol. 23).

opencc-by-4.0Dec 2008View details →

Text-fig. 2. Sketch map of the Żytawa / Zittau Basin showing the Polish (Turów) and Czech (Hrádek) parts. Bogatynia (E of Rybarzowice) and Hrádek sites refer to the areas of the deepest depressions of the eastern and southern parts of the basin. in Some Monocot Pollen Taxa From The Lower Miocene Basal Coaly Deposits Of The Czech And Polish Parts Of The Żytawa (Zittau) Basin

Text-fig. 2. Sketch map of the Żytawa / Zittau Basin showing the Polish (Turów) and Czech (Hrádek) parts. Bogatynia (E of Rybarzowice) and Hrádek sites refer to the areas of the deepest depressions of the eastern and southern parts of the basin.