Find research datasets worth reusing

opencc-by-4.0Dec 2021View details →

Text-fig. 6. Briveichthys chantepieorum gen. et sp. nov. a: reconstruction of the skull roof and the nasal in dorsal view, scale bar 5 mm; b: reconstruction of the skull in lateral view (parts of the skull which are not clearly retained are in grey colour), scale bar 5 mm. Abbreviations: ana – anterior nasal opening, Aop – antoperculum, De – dentalosplenial, Dpt – dermopterotic, Dsph – dermosphenotic, Fr – frontal, Gul – lateral gular, ioc – infraorbital canal, Ju – jugal, Mx – maxilla, Na – nasal, Op – operculum, Pa – parietal, pl – pit line, Pop – preoperculum, Pt – posttemporal, Rbr – branchiostegal ray, Scl – supracleithrum, soc – supraorbital canal, Sop – suboperculum, sr – sclerotical ring. in New Actinopterygians From The Permian Of The Brive Basin, And The Ichthyofaunas Of The French Massif Central

Text-fig. 6. Briveichthys chantepieorum gen. et sp. nov. a: reconstruction of the skull roof and the nasal in dorsal view, scale bar 5 mm; b: reconstruction of the skull in lateral view (parts of the skull which are not clearly retained are in grey colour), scale bar 5 mm. Abbreviations: ana – anterior nasal opening, Aop – antoperculum, De – dentalosplenial, Dpt – dermopterotic, Dsph – dermosphenotic, Fr – frontal, Gul – lateral gular, ioc – infraorbital canal, Ju – jugal, Mx – maxilla, Na – nasal, Op – operculum, Pa – parietal, pl – pit line, Pop – preoperculum, Pt – posttemporal, Rbr – branchiostegal ray, Scl – supracleithrum, soc – supraorbital canal, Sop – suboperculum, sr – sclerotical ring.

opencc-zeroJun 2024View details →

Dataset: Pop Culture Group Co., Ltd (CPOP) Stock Performance

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

Text-fig. 3. Progyrolepis speciosus (FRIČ, 1875). Reconstruction of the dermal skull in lateral view, x 0.7. After Štamberg (1991). Ang – angular; cl – cleithrum; Dent – dentalosplenial; Epi – epipreoperculum; Fr – frontal; Gul – gular lateral; La – lacrimal; Mx – maxilla; Na – nasal; Op – operculum; Pop - preoperculum; Pt – posttemporal; Ptr – postrostral; Rbr – branchiostegal rays; Rpm – rostropremaxillar; Sbo – suborbital; Scl – supracleithrum; Sop – suboperculum. in Knowledge Of The Carboniferous And Permian Actinopterygian Fishes Of The Bohemian Massif - 100 Years After Antonín Frič

Text-fig. 3. Progyrolepis speciosus (FRIČ, 1875). Reconstruction of the dermal skull in lateral view, x 0.7. After Štamberg (1991). Ang – angular; cl – cleithrum; Dent – dentalosplenial; Epi – epipreoperculum; Fr – frontal; Gul – gular lateral; La – lacrimal; Mx – maxilla; Na – nasal; Op – operculum; Pop - preoperculum; Pt – posttemporal; Ptr – postrostral; Rbr – branchiostegal rays; Rpm – rostropremaxillar; Sbo – suborbital; Scl – supracleithrum; Sop – suboperculum.

Text-fig. 1. Letovichthys tuberculatus ŠTAMBERG, 2007. Reconstruction of the dermal skull in lateral view, x 3. After Štamberg (2007). Dent – dentalosplenial; Dhy – dermohyal; dlac – dorso-lateral-anterior sensory canal; Dpt – dermopterotic; Dsph – dermosphenotic; Ext.l – extrascapular lateral; Ext.m – extrascapular medial; Fr – frontal; Gu.l – gular lateral; ifc – infraorbital canal; Io.s – infraorbital superior; mdc – mandibular canal; Na – nasal; Op – operculum; Pa – parietal; Pmx – premaxillar; Pop - preoperculum; Pscs – postspiracular; Pt – posttemporal; Ptr – postrostral; Rbr – branchiostegal rays; Sbo – suborbital; Scl – supracleithrum; Sop – suboperculum; stc – supratemporal commisural sensory canal. in Knowledge Of The Carboniferous And Permian Actinopterygian Fishes Of The Bohemian Massif - 100 Years After Antonín Frič

Text-fig. 1. Letovichthys tuberculatus ŠTAMBERG, 2007. Reconstruction of the dermal skull in lateral view, x 3. After Štamberg (2007). Dent – dentalosplenial; Dhy – dermohyal; dlac – dorso-lateral-anterior sensory canal; Dpt – dermopterotic; Dsph – dermosphenotic; Ext.l – extrascapular lateral; Ext.m – extrascapular medial; Fr – frontal; Gu.l – gular lateral; ifc – infraorbital canal; Io.s – infraorbital superior; mdc – mandibular canal; Na – nasal; Op – operculum; Pa – parietal; Pmx – premaxillar; Pop - preoperculum; Pscs – postspiracular; Pt – posttemporal; Ptr – postrostral; Rbr – branchiostegal rays; Sbo – suborbital; Scl – supracleithrum; Sop – suboperculum; stc – supratemporal commisural sensory canal.

Text-fig. 3. "Glossanodon" musceli A – nearly complete specimen NM Pc 02875a; B – caudal skeleton of specimens NM Pc 02871b and NM Pc 02871a (B-1 and B-2 respectively; part and counterpart) and its tentative reconstruction (B-3); C – specimen NM Pc 02873a, general view (C-1) and detail of the head (C-2); D – specimen NM Pc 02874a (the white arrow shows normally developed neural spine on the anterior abdominal vertebra). Abbreviations: ao – antorbitale; d – dentale; epu – epurale; fr – frontale; hp1-6 – hypurals 1-6; io – infraorbitals; mx – maxillare; npu2 – neural spine of second preural vertebra; ph – parhypurale; pu1 – first preural vertebra; pop – preoperculum; psp – parasphenoideum; stu – stegurale; u1 – urale 1; u2 – urale 2. in An Annotated List Of The Oligocene Fish Fauna From The Osíčko Locality (Menilitic Fm.; Moravia, The Czech Republic)

Text-fig. 3. "Glossanodon" musceli A – nearly complete specimen NM Pc 02875a; B – caudal skeleton of specimens NM Pc 02871b and NM Pc 02871a (B-1 and B-2 respectively; part and counterpart) and its tentative reconstruction (B-3); C – specimen NM Pc 02873a, general view (C-1) and detail of the head (C-2); D – specimen NM Pc 02874a (the white arrow shows normally developed neural spine on the anterior abdominal vertebra). Abbreviations: ao – antorbitale; d – dentale; epu – epurale; fr – frontale; hp1-6 – hypurals 1-6; io – infraorbitals; mx – maxillare; npu2 – neural spine of second preural vertebra; ph – parhypurale; pu1 – first preural vertebra; pop – preoperculum; psp – parasphenoideum; stu – stegurale; u1 – urale 1; u2 – urale 2.

Text-fig. 1. Amblypterus latus AGASSIZ, 1833. Pen and ink drawing (A) and photo (B) of the skull in lateral view. Mb. F. 3809b, scale bar represents 10 mm. Cl – cleithrum; Dent – dentalosplenial; Dhy – dermohyal; Dpt – dermopterotic; Dsph –dermosphenotic; Extl – extrascapular lateral; Fr –frontal; Gu – gular; Infs – infraorbital superior; Ju – jugal; La – lacrimal; Mx – maxilla; Na – nasal; Op – operculum; Pa – parietal; Pmx – premaxillar; Pop – preoperculum; Pp – postparietal; Pt – posttemporal; Rbr – branchiostegal rays; Sbo – suborbital; Scl – supracleithrum; Soant – supraorbital anterior; Sop – suboperculum; Spi – spiracular; sr – sclerotical ring. in New Data On The Osteology Of The Actinopterygian Fish Amblypterus And The Relationship Between Amblypterus And Paramblypterus

Text-fig. 1. Amblypterus latus AGASSIZ, 1833. Pen and ink drawing (A) and photo (B) of the skull in lateral view. Mb. F. 3809b, scale bar represents 10 mm. Cl – cleithrum; Dent – dentalosplenial; Dhy – dermohyal; Dpt – dermopterotic; Dsph –dermosphenotic; Extl – extrascapular lateral; Fr –frontal; Gu – gular; Infs – infraorbital superior; Ju – jugal; La – lacrimal; Mx – maxilla; Na – nasal; Op – operculum; Pa – parietal; Pmx – premaxillar; Pop – preoperculum; Pp – postparietal; Pt – posttemporal; Rbr – branchiostegal rays; Sbo – suborbital; Scl – supracleithrum; Soant – supraorbital anterior; Sop – suboperculum; Spi – spiracular; sr – sclerotical ring.

opencc-by-4.0Jul 2021View details →

EMOPIA: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation

EMOPIA (pronounced ‘yee-mò-pi-uh’) dataset is a shared multi-modal (audio and MIDI) database focusing on perceived emotion in pop piano music, to facilitate research on various tasks related to music emotion. The dataset contains 1,087 music clips from 387 songs and clip-level emotion labels annotated by four dedicated annotators.  For more detailed information about the dataset, please refer to our paper: <a href="https://arxiv.org/abs/2108.01374">EMOPIA: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation</a>.  File Description <ul> <li>midis/: midi clips transcribed using GiantMIDI. <ul> <li>Filename `Q1_xxxxxxx_2.mp3`: Q1 means this clip belongs to Q1 on the V-A space; xxxxxxx is the song ID on YouTube, and the `2` means this clip is the 2nd clip taken from the full song.</li> </ul> </li> <li>metadata/: metadata from YouTube. (Got when crawling)</li> <li> songs_lists/: YouTube URLs of songs. </li> <li> tagging_lists/: raw tagging result for each sample. </li> <li> label.csv: metadata that records filename, 4Q label, and annotator. </li> <li> metadata_by_song.csv: list all the clips by the song. Can be used to create the train/val/test splits to avoid the same song appear in both train and test. </li> <li> scripts/prepare_split.ipynb: the script to create train/val/test splits and save them to csv files. </li> </ul> ------ 2.2 Update <ul> <li>Add tagging files in tagging_lists/ that are missing in the previous version.</li> <li>Add timestamps.json for easier usage. It records all the timestamps in dict format. You can see scripts/load_timestamp.ipynb for the format example.</li> <li>Add scripts/timestamp2clip.py: After the raw audio are crawled and put in audios/raw, you can use this script to get audio clips. The script will read timestamps.json and use the timestamp to extract clips. The clips will be saved to audios/seg folder.</li> <li>remove 7 midi files that were added by mistake, and also corrected the number in metadata_by_song.csv.</li> </ul>   2.1 Update Add one file and one folder: <ul> <li>key_mode_tempo.csv: key, mode, and tempo information extracted from files.</li> <li>CP_events/:  CP events used in our paper. Extracted using this <a href="https://github.com/YatingMusic/compound-word-transformer/blob/main/dataset/representations/uncond/cp/corpus2events.py">script</a>, and add the emotion event to the front.</li> </ul> Modify one folder: <ul> <li>The REMI_events/ files in version 2.0 contain some information that is not related to the paper, so remove it.</li> </ul>   2.0 Update Add two new folders: <ul> <li>corpus/:  processed data that following <a href="https://github.com/YatingMusic/compound-word-transformer/blob/main/dataset/Dataset.md">the preprocessing flow</a>. (Please notice that although we have <code>1078</code> clips in our dataset, we lost some clips during steps 1~4 of the flow, so the final number of clips in this <code>corpus</code> is <code>1052</code>, and that's the number we used for training the generative model.)</li> <li>REMI_events/: REMI event for each midi file. They are generated using this <a href="https://github.com/YatingMusic/compound-word-transformer/blob/main/dataset/representations/uncond/remi/corpus2events.py">script</a>.</li> </ul> --------        Cite this dataset <pre><code>@inproceedings{{EMOPIA}, author = {Hung, Hsiao-Tzu and Ching, Joann and Doh, Seungheon and Kim, Nabin and Nam, Juhan and Yang, Yi-Hsuan}, title = {{MOPIA}: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation}, booktitle = {Proc. Int. Society for Music Information Retrieval Conf.}, year = {2021} }</code></pre>

dryad40/100

Data from: Pop‐off data storage tags reveal niche partitioning between native and non‐native predators in a novel ecosystem

Open the record for dataset details and reuse information.

publicApr 2022View details →

opencc-by-4.0Nov 2016View details →

Listening preferences for variations of pop mixes in a circular Wave Field Synthesis system

This data set includes results for the listening tests described in http://doi.org/10.5281/zenodo.61000, but this time applying the real loudspeakers and not binaural synthesis. The folder `results/` contains the single results of the 41 test participants. The folder `analisys/` contains the script `pc_matrices.py` for creating paired comparison matrices across the participants for all conditions, that are stored under `analysis/pc_matrices/`. It also contains the script `btl.R`, which calculates a Bradley-Terry-Luce model after Wickelmayer et al. [1]. Its results are stored under `analysis/btl/` and plotted in `analysis/btl_systems.pdf` and `analysis/btl_mixing.pdf` for comparing the different reproduction systems together for all conditions and independent for the different mixing parameters, respectively. All steps to recreate the plot are listed in the script `run_all.sh` in the `analysis/` folder. [1] https://cran.r-project.org/web/packages/eba/index.html

opencc-by-4.0Nov 2023View details →

2DVD dataset for GMD publication - Simulated prognostic approach of graupel density in a bulk-type cloud microphysics scheme and evaluation during the ICE-POP field campaign

This archive contains the 2DVD measurement of graupel particles used in the GMD paper "Simulated prognostic approach of graupel density in a bulk-type cloud microphysics scheme and evaluation during the ICE-POP field campaign".For each identified graupel particle, the following are included:<ul><li>Volume-equivalent diameter (mm)</li><li>Density (g cm-3)</li><li>Fall velocity (m s-1)</li></ul>

opencc-by-4.0Dec 2023View details →

FreeMe EU Project: Sprayable resins utilization for PoP process

The FreeMe project aims to eliminate the use of hexavalent chromium (Cr6+) and palladium (Pd) from the Plating on Plastics (PoP) process, based on REACH compliant chemicals, avoiding toxic compounds and ensuring long-term sustainability. This video is an early demonstration of the spray apparatus for the application of resins in substrates in the context of the Plating on Plastics (PoP) process of the FreeMe Project.

dryad36/100

Dynamics of leaching of POPs and additives from plastic in a Procellariiform gastric model: Diet and polymer dependent effects and implications for long-term exposure

Procellariiform seabirds are known to have high rates of plastic ingestion. We investigated the bioaccessibility of plastic-associated chemicals [plastic additives and sorbed persistent organic pollutants (POPs)] leached from plastic over time using an in vitro Procellariiform gastric model. High-density polyethylene (HDPE) and polyvinyl chloride (PVC), commonly ingested by Procellariiform seabirds, were manufactured with one additive [decabrominated diphenyl ether (PBDE-209) or bisphenol S (BPS)]. HDPE and PVC added with PBDE-209 were additionally incubated in salt water with 2,4,4'-trichloro-1,1'-biphenyl (PCB-28) and 2,2',3,4,4',5'-hexachlorobiphenyl (PCB-138) to simulate sorption of POPs on plastic in the marine environment. Our results indicate that the type of plastic (nature of polymer and additive), presence of food (i.e., lipids and proteins) and gastric secretions (i.e., pepsin) influence the leaching of chemicals in a seabird. In addition, 100% of the sorbed POPs were leached from the plastic within 100 hours, while only 2-5% of the additives were leached from the matrix within 100 hours, suggesting that the remaining 95% of the additives could continue to be leached. Overall, our study illustrates how plastic type, diet and plastic retention time can influence a Procellariform's exposure risk to plastic-associated chemicals.

opencc-zeroDec 2023View details →

opencc-byJun 2021View details →

Bocca della verità scanned with Revopoint POP

Bocca della verità sur l'église Santa Maria in Cosmedin de Rome, Italie. Scanné avec Revopoint POP à partir d'une reproduction achetée sur place. Source: Objaverse 1.0 / Sketchfab

opencc-by-4.0Mar 2024View details →

Alice in Quantum Land — Quantum Mechanics and its influence in (pop) culture

In this seminar we will discuss Quantum Mechanics (QM) not so much from the traditional point of view of Physics, but to assess the inevitable “reverberations” that this discipline has had, and still has, in popular culture. Indeed, one of the aspects known even to the layman is the strangeness of the laws that govern the subatomic world, where totally counterintuitive things happen. Those who are used to doing science in the traditional way, resting their research on solid epistemological foundations, when confronted with QM must “suspend judgment” and very often use it – very pragmatically – as a simple tool (which Physicists have shown they can do very well). The seminar will focus on the bewilderment that the forerunners of this discipline already had to overcome to accept the “rules” it imposed, and we will see that among them even eminent minds made an enormous effort to accept these rules, when not even going so far as to reject this “new Physics” altogether. The seminar will then briefly explore the more “pop” side, which is how, from the point of view of popularizing science, QM offers excellent tools to intrigue a lay audience.

opencc-by-4.0Feb 2022View details →

Dataset for "Pop Quiz! Can a Large Language Model Help WIth Reverse Engineering?"

Source files and scripts for the test framework used in evaluating OpenAI's code-davinci-001 (also known as davinci-codex) model for reverse engineering tasks. All results presented in the associated manuscript are preserved in this dataset, or you can use it to perform additional experiments or re-generate the results.

opencc-by-4.0Feb 2022View details →

Laboratory capability Survey - POPs in Food and Feed, VSCHT

POPs analysis capabilities at University of Chemistry and Technology (VSCHT), Prague, Czech Republic

opencc-byJun 2021View details →

Wooden Camel by Revopoint POP

Another scan I made with the POP scanner. I did some cleanup in Meshmixer where I removed excessive noise and in Blender where I added leather belts that weren't captured. I think the result is pretty good :> Source: Objaverse 1.0 / Sketchfab

opencc-by-4.0Dec 2023View details →

UrbanOccupationsOETR_1840s_Ottoman_Bursa_pop_micro_dataset

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, <a href="https://urbanoccupations.ku.edu.tr/">UrbanOccupationsOETR</a>) 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 <table> <tbody> <tr> <td> tblHouse </td> <td> </td> <td> </td> </tr> <tr> <td> Category </td> <td> Variable </td> <td> Description </td> </tr> <tr> <td> Unique key/ID </td> <td> “HouseID” </td> <td> Unique and consecutive ID belonging to a specific household, automatically generatead by Microsoft Access </td> </tr> <tr> <td> Geographic unit of entry </td> <td> “Province” & “District” & “SubDistrict” & “Village” & “Quarter” </td> <td> Geographic unit of entry from province to quarter as it appears in the register </td> </tr> <tr> <td> Register specifics </td> <td> “DefterNo” </td> <td> Archival code of the register whose data is being entered </td> </tr> <tr> <td> </td> <td> “FileNo” </td> <td> JPEG number of the register page of the household being entered </td> </tr> <tr> <td> </td> <td> “Menzil” </td> <td> Number of the household (specified by the registers as Menzil, Persian word for house), as appears in the register </td> </tr> <tr> <td> </td> <td> “Note” </td> <td> When a household is annotated with a note, e.g. it is empty </td> </tr> <tr> <td> </td> <td> “LocationCtg” </td> <td> Specifies if the household refers to a  dwelling like inn or madrasa </td> </tr> </tbody> </table>   Table 2: Categories and descriptions of the variables of tblIndividual <div> <table> <tbody> <tr> <td> tblIndividual </td> <td> </td> <td> </td> </tr> <tr> <td> Category </td> <td> Variable </td> <td> Description </td> </tr> <tr> <td> Unique key/ID </td> <td> "HouseID" </td> <td> Unique ID belonging to a specific household, automatically generated by Microsoft Access, which links the individuals to households and connects the "tblHouse" and "tblIndividual" </td> </tr> <tr> <td> </td> <td> "IndivID" </td> <td> Unique ID belonging to a specific individual, automatically generated by Microsoft Access </td> </tr> <tr> <td> Ethno-religious identity </td> <td> “ER” </td> <td> Ethnoreligious identity of the individual as given in the register </td> </tr> <tr> <td> Tax information </td> <td> “Cizye” (Poll tax / jizya) </td> <td> Poll tax category of the individual when it was first recorded </td> </tr> <tr> <td> </td> <td>“DateToPayCizyeDay” & “DateToPayCizyeMonth” & “DateToPayCizyeYear” & “DateToPayCizyeCtg”</td> <td> When the individual will be eligible for poll tax in hijri dates and the tax category to be paid </td> </tr> <tr> <td> Occupation </td> <td> “EmploymentStatus” </td> <td> Specific references to one’s non-working status such as retirement [tekaüd, amelmande] </td> </tr> <tr> <td> </td> <td> “OccupationIRegistered” </td> <td> Occupation as registered in the record [e.g., barber’s apprentice in someone’s shop] </td> </tr> <tr> <td> </td> <td> “OccupationI” </td> <td> Standardized version of the occupation [e.g.,barber] </td> </tr> <tr> <td> </td> <td> “OccupationIStatus” </td> <td> Status of the occupation [e.g., apprentice]. If an occupation did not have a status, then “statüsüz” (no status) was entered. </td> </tr> <tr> <td> </td> <td> “OccupationIIRegistered” & “OccupationII” & “OccupationIIStatus” & “OccupationIIIRegistered” & “OccupationIII” & “OccupationIIIStatus” </td> <td> Versions of the descriptors above if the individual is employed in multiple occupations </td> </tr> <tr> <td> Individual interrelationships </td> <td> “RelTo” </td> <td> Short for “Related To,” and shows the individual’s relationship or lack thereof to the first recorded male within the household. If he was the “_firstRegisteredMale,” then he is recorded as such. The type of relationship to the “_firstRegisteredMale”, such as son (oğlu), grandson (hafidi/torunu), tenant (kiracı), or slave (gulamı/kölesi), or lack of it (in the case of a new individual moved to the household) are specified. </td> </tr> <tr> <td> </td> <td> “ILTAFM” </td> <td> Short for “Is Linked to Another Family Member.” When the individual is related to someone other than the “_firstRegisteredMale,” only “Yes” or “No” is chosen here </td> </tr> <tr> <td> </td> <td> “LTW” </td> <td> Short for “Linked to Whom.” If the “ILTAFM” is “Yes,” "LTW" specifies the “IndivID” of the household member an individual is related to </td> </tr> <tr> <td> </td> <td> “RelToFM” </td> <td> Short for “Relationship to the Family Member,” and shows the relationship of the person to the “LTW” </td> </tr> <tr> <td> Individual data </td> <td> “PersonNumberRegistered” </td> <td> Number assigned to an individual that is automatically generated and can be manipulated by the data entry person if needed (e.g., if the number does not match the one in the register) </td> </tr> <tr> <td> </td> <td> “FamilyName” </td> <td> The individual's family name, in the rare occasion before the official introduction of family names (not to be confused with title) </td> </tr> <tr> <td> </td> <td> “Title1” </td> <td> Title(s) appearing before an individual’s name </td> </tr> <tr> <td> </td> <td> “NameI” </td> <td> The individual's name(s) </td> </tr> <tr> <td> </td> <td> "Title2” </td> <td> Title(s) appearing after an individual’s name </td> </tr> <tr> <td> </td> <td> “Conjunction” </td> <td> Arabic patronymic ibn, bin, and veled (equivalent to the “-son” suffix in English, meaning the son of "NameII") and Turkish patronymic oğlu (the opposite, meaning the son of "NameI", appearing rarely), that links "NameI" and "NameII" </td> </tr> <tr> <td> </td> <td> “FathersTitle1" </td> <td> Title(s) appearing before the father’s name (if the conjunction is "oğlu", then the title of the son (the individual himself) </td> </tr> <tr> <td> </td> <td> “NameII” </td> <td> The father's name(s) (if the conjunction is "oğlu", then the name of the son (the individual himself) </td> </tr> <tr> <td> </td> <td> “FathersTitle2” </td> <td> Title(s) appearing after the father’s name (if the conjunction is "oğlu", then the title of the son (the individual himself) </td> </tr> <tr> <td> </td> <td> “FatherOccupation” </td> <td> The father’s occupational information </td> </tr> <tr> <td> </td> <td> “FatherOccupationStatus” </td> <td> The father’s occupational status </td> </tr> <tr> <td> </td> <td> “Age” </td> <td> Ages expressed in years. If the ages are given in months or days for under-one age children in the register, they are converted to years and shown in fractional form (e.g. 6/12 for a six-months-old child and 2/354 for two-days-old baby) </td> </tr> <tr> <td> </td> <td> “PlaceOfBirth” </td> <td> The individual’s birthplace or place of origin </td> </tr> <tr> <td> </td> <td> “Note” </td> <td> If the individual is annotated with a note, or a data entry person needs to highlight an issue regarding an individual’s data, they are entered to this column </td> </tr> <tr> <td> Birth Updates </td> <td> “BirthDay” & “BirthMonth” & “BirthYear” </td> <td> A newborn’s birth date as expressed in hijri dates, in the available detail </td> </tr> <tr> <td> Death Updates </td> <td> “DeathDay” & “DeathMonth” & “DeathYear” </td> <td> The individual’s death date as expressed in hijri dates </td> </tr> <tr> <td> Migration Updates </td> <td> “Transfer” </td> <td> Specified by the registers as nakil (Arabic word for "transfer") and refers to the movement destination within a location, like from one household to another </td> </tr> <tr> <td> </td> <td> “TransferDay” & “TransferMonth” & “TransferYear” </td> <td> The individual's “Transfer” date as expressed in hijri dates </td> </tr> <tr> <td> </td> <td> “Reft" </td> <td> Destination of emigration (specified by the registers as reft, Persian word for "going") </td> </tr> <tr> <td> </td> <td> “ReftDay” & “ReftMonth” & “ReftYear” </td> <td> The individual's “Reft” date as expressed in hijri dates </td> </tr> <tr> <td> </td> <td> “Amed” </td> <td> Where an individual came from (specified by the registers as amed - Persian word for "coming"). If an individual is exempted from military service and returned home, this information was entered here. </td> </tr> <tr> <td> </td> <td> “AmedDay” & “AmedMonth” & “AmedYear” </td> <td> The individual's “Amed” date as expressed in hijri dates </td> </tr> <tr> <td> </td> <td>   </td> <td> Note: If there were multiple migration events for an individual, multiple “Transfer,” “Reft,” and Amed” data and their dates were separated by a slash (“/”). </td> </tr> <tr> <td> Military updates </td> <td> “Askerlik” (Turkish word for military service) </td> <td> The individual’s military status, including eligibility (recorded as tuvana, meaning strong, and shortened as “t” when presented along with other information), and/or reasons for exemption e.g., old age (recorded as müsin, meaning aged, and shortened as “m” when presented along with other information), infirmities (e.g, yekçeşm meaning one-eyed), and retirement (tekaüd, mütekaid) </td> </tr> <tr> <td> </td> <td> “AskerlikDay” & “AskerlikMonth” & “AskerlikYear” </td> <td> Specifies data such as when an individual’s service started, when an eligible (“t”) male was to be conscripted, and when a male was exempted or would be exempt (“m”) as expressed in hijri dates </td> </tr> <tr> <td> </td> <td>   </td> <td> Note: If there were multiple military data for an individual, they are given together (e.g. "yekçeşm m" [one-eyed and (m)üsin/exempt]). </td> </tr> <tr> <td> Special day, month, and year abbreviations </td> <td> “Evail” & “Evasıt” & “Evahir” & “Gurre” & “Selh” </td> <td> Hijri dates are sometimes shown with special abbreviations. For days, “Evail” refers to the first ten days of a month; “Evasıt” to the middle ten days and “Evahir” to the last ten days of a month. “Gurre(-i)” is used for the first day of a hijri month and “Selh(-i)” is for the last day. </td> </tr> <tr> <td> </td> <td>  (M) & (S) & (RA) & (CA.) & (C) & (B) & (Ş) & (N) & (L) & (ZA) & (Z) </td> <td> Months can be shown in Latin letters referring to the hijri month: Muharrem: (M), Safer: (S), Rebiül-evvel: (RA), Rebiül-ahir: (R) Cemaziyel-evvel: (CA), Cemaziyel-ahir: (C), Receb: (B), Şaban: (Ş), Ramazan: (N), Şevval: (L), Zilkade: (ZA), Zilhicce: (Z). </td> </tr> <tr> <td> </td> <td> Two and three-digit years </td> <td> Years are sometimes expressed in two or three digits instead of four by ignoring the millennium or the century when the registers were completed. In this case, for example, year “58” should be read as 1258 and “259” as 1259 </td> </tr> <tr> <td> Special terms </td> <td> “_undeciphered” </td> <td> If a variable could not be read, "_undeciphered" was entered </td> </tr> <tr> <td> </td> <td> “_unspecified” </td> <td> If a variable was not given, such as the age of the newborn, "_unspecified" was entered </td> </tr> <tr> <td> </td> <td> “2000” </td> <td> If one part of a variable could not be read, then "2000" was entered in its place (e.g., "2000oğlu" [“2000son”] in place of a family name where only "oğlu" part is legible) </td> </tr> <tr> <td> </td> <td> "kz" & "nh" & “ks” & "kr" & "h" & "mdrs" & "m" </td> <td> In "Birthplace," "Reft," "Amed," and "Transfer," the following codes were used if they were specified in these sections in the registers: "kz" or kaza (subdistrict), "nh" for nahiye (township), “ks” for kasaba (little town/borough), "kr" for karye (village), "h" for han (inn), "mdrs" for madrasa, and "m" for mahalle (quarter). If these variables could not be read, then "_undeciphered_" was entered before these codes, and if they were not specified, then "_unspecified_" was entered before them (e.g., “_undeciphered_kz”) </td> </tr> </tbody> </table> </div>   We would like to mention all researchers who contributed to the urban Bursa population dataset, Tuna Başıbek, Sinan Kaya, and Zeynep Arslan, and especially thank Dzenaida Gicic, the computer scientist, who took over from Mehmet Can Yavuz and further developed the data entry template and maintained a controlled construction of the datasets. Lastly, if you encounter a pop-up message stating, "The active content in this file is blocked. Review your Trust Center settings or contact your IT administrator," please be assured that this is a standard security feature in Microsoft Office applications, triggered by security settings on your local machine or the platform. Microsoft Access uses these measures to protect users from potential risks associated with macros or active content within databases. To resolve this issue promptly, kindly click "OK" on the pop-up message. This action will allow you to proceed and access the database without any interruption. If you would like to use the dataset, please use the credentials specified below: M. Erdem Kabadayi and Efe Erünal, “UrbanOccupationsOETR_1840s_Ottoman_Bursa_pop_micro_dataset” (Zenodo, December 29, 2023), <a href="https://doi.org/10.5281/zenodo.10441019">https://doi.org/10.5281/zenodo.10441019</a>.

opencc-by-4.0Aug 2018View details →

Help wanted identifying hams in Swarm-E (e-POP) RRI data

In the spirit of making data from the <a href="https://epop.phys.ucalgary.ca/rri/">Radio Receiver Instrument (RRI)</a> onboard <a href="http://www.esa.int/Our_Activities/Observing_the_Earth/Swarm/Swarm_trio_becomes_a_quartet">Swarm-E</a> (formally known as <a href="https://epop.phys.ucalgary.ca/">e-POP</a>) more accessible to the ham radio community via the Ham Radio Science Citizen Investigation (<a href="http://hamsci.org/about-hamsci">HamSCI</a>), we have converted RRI's data into a ".raw" format so that it can be ingested into open source software such as <a href="http://gqrx.dk/">Gqrx</a> or <a href="https://www.gnuradio.org/">GNU Radio</a>.  We have done this for all RRI data related to the 2015, 2017, and 2018 ARRL Field Days. We encourage everyone to help us identify hams in RRI's signal.  You can use the Gqrx tool discussed here, or you can use your own technique.  If you decode a ham's call sign, if you would like to share your technique, or if you have any comments or suggestion <a href="mailto:perry@phys.ucalgary.ca?subject=HamSCI%3A%20RRI%20ARRL%20%22raw%22%20data%20dump">contact us</a> and let us know!  Data Rules of the Road Please acknowledge the HamSCI project and Gareth Perry when using data from this archive in presentations and publications. Swarm-E RRI Swarm-E RRI is a digital radio receiver with 4 3-m monopole antennas.  In most cases, the monopoles are electronically configured into a crossed-diople configuration.  In this configuration, RRI records I/Q samples for the two dipoles.  RRI has a sampling rate of 62500.33933 Hz, and a ~40 kHz bandpass, and can be tuned to anywhere between 10 Hz and 18 MHz.  More information on Swarm-E RRI can be found in the <a href="https://link.springer.com/article/10.1007/s11214-014-0130-y">Swarm-E RRI instrument paper</a> or Gareth Perry's recent <a href="http://hamsci.org/article/field-day-cassiope-2015-results-published-radio-science">Radio Science article</a>. Data Format Each data file contains raw 32 bit complex I/Q samples for a given RRI dipole at a given frequency.  The samples are interleaved, e.g., IQIQIQIQ... The data files do not contain any metadata.  Any information regarding the time, frequency, and corresponding RRI dipole is in the file name.   Filename Format The filename format gives information about the time and data of the recording, the tuned frequency, and which of RRI's dipoles the recording corresponds too.  For example, gqrx_20150628_011614_3525000_62500_RRI_Dipole1 contains data recorded on Dipole 1, starting at 01:16:14 UT on June 28, 2015, at 3525000 Hz (3.525 MHz), at a sampling rate of 62500 Hz (RRI's 62500.33933 Hz sampling rate). Gqrx We have opted to convert the data into the .raw format so that it can be ingested into <a href="http://gqrx.dk/">Gqrx</a>.  There are other ways of analyzing RRI's data; this is just one way which we felt was as easy first step.  We are open to posting about other techniques on the HamSCI site as well.  To help get started with Gqrx, we have developed a <a href="http://hamsci.org/resource/how-play-rri-raw-iq-file-gqrx">How to play an RRI raw IQ file on Gqrx</a> page.