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367 results for “finnish”
Nitrogen fertilization plot level data - a Finnish case study
<p>The data is based on the fertilization study where we evaluated the spatial evenness of nitrogen (N) fertilization (measured fertilization dose on circular plots with radius of 7,98 m) in fertilized treatments and effects of fertilization treatments (target of 0, 150 and 200 kg N /ha) on short-term volume growth responses in two ground-fertilized (2018) Scots pine and in two airborne-fertilized (2019) Norway spruce study sites on medium fertile (Myrtillus-type, MT) upland forest sites in Eastern Finland. It was also studied the relationships between measured fertilization dose, N concentrations in needles and soil organic (humus) layer, and volume growth of trees (calculated based on diameter at breast height and height of sample trees) based on block level averages (based on data measured for three circular plots in each block). In each study area, we established three one hectare replicate blocks (with three circular study plots of 200 m² in each) for fertilizer treatments with target of 0, 150 and 200 kg N /ha. Spatial evenness of the fertilization was measured with textile funnels. Height, breast height diameter and vitality (living/dead) of trees were measured annually in each circular plot. Nutrient concentrations in needles (analysed in Yara laboratory in United Kingdom) and soil organic (humus) layer (analysed at UEF laboratory) were measured once. </p>
Supporting data and code for: Longitudinal Study on Shiga Toxin–producing Escherichia coli and Campylobacter jejuni on Finnish Dairy Farms and in Raw Milk
<p>Supporting data and code for the article: "Longitudinal Study on Shiga Toxin–producing <em>Escherichia coli</em> and <em>Campylobacter jejuni</em> on Finnish Dairy Farms and in Raw Milk".</p>
Web tracking data for 500 websites popular among Finnish web users
<p>This dataset includes observations of trackers present on the top 500 pages popular among Finnish web users as per Alexa. The data collection was conducted using TrackerTracker in five separate requests for five subsets of 100 sites each between 19.8.2017 and 20.8.2017. The tool used a tracker database from March 24, 2017. More methodology details are described in the associated journal article <a href="https://doi.org/10.23978/inf.87841">https://doi.org/10.23978/inf.87841</a></p>
Observations for intensive stations in the Finnish Archipelago Sea 2006-2015
<p>Calibration data for the FICOS water quality simulator. To use them with the ficosUQ package, download the intensiveStationsData.xlsx file and place it in the ficosUQ/data folder.</p> <p>First sheet contains this description of the data, while sheets 2 to 4 contain data from stations in Brändö, Seili and Utö.</p> <p>Curated by Elina Miettunen, Finnish Environment Institute, 2.3.2023</p> <p>Description translated by Karel Kaurila, University of Helsinki, 2024</p> <p>This data set contains medians for the observations collected from intensive stations in Brändö, Seili and Utö between 2006-2015 for the surface and deep layers. The data set was curated such that its observations can be meaningfully compared to the predictions from the FICOS model in the water formation resolution. Data from each station is on its own sheet. The columns describing the time and place of the obsevations as follows:</p> <p>- Date : day the of the observation, dd/mm/yyyy<br>- VPD_name : official code for the water formation<br>- Block : internal code for the water formation in FICOS<br>- Lat, Lon : latitude and longitude</p> <p>In each table, the columns use the same names as the results.hdf5 file produced by FICOS and all observations are in the same units as the FICOS predictions. The column names ending in 0 correspond to observations on the surface layer (0-10 m), while the ones ending in 1 correspond to the deep layer (20-40 m). The observations used in calibration are the following:</p> <p>- cDIN_0(1) : Dissolved inorganic nitrogen (mg/m3)<br>- cDIP_0(1) : Dissolved inorganic phosphorus (mg/m3)<br>- Chla : Chlorophyll a (mg/m3)<br>- cC : Cyanobacteria biomass (mg N/m3)<br>- cA : Biomass for other algae (mg N/m3)</p> <p>Note that FICOS does not predict Chla directly, but instead as a combination of cA and cC.<br>The data are picked from a data set processed by Elina in December 2019 that contained all of the observation stations determined by Finnish Environment Institute to be representative of their water formations. This data was obtained from Hertta (Finnish Environment Institute’s open database, available in Finnish only) as follows:</p> <p>- Observations less than 3 m from the bottom of the sea were not included. Obvious outliers, such as very high nutrient concentrations that cannot be meaningfully compared to FICOS predictions, were also not included.</p> <p>- Observations from depths 0-10 m correspond to the FICOS model’s surface layer, while observations from depths 20-40 m correspond to FICOS model’s deep layer.</p>
Finnish DBnary archive in original Lemon format
<p>The DBnary dataset is an extract of Wiktionary data from many language editions in RDF Format. Until July 1st 2017, the lexical data extracted from Wiktionary was modeled using the lemon vocabulary.</p> <p>This dataset contains the full archive of all DBnary dumps in Lemon format containing lexical information from Finnish language edition, ranging from 3rd September 2012 to 1st July 2017.</p> <p>After July 2017, DBnary data has been modeled using the ontolex model and will be available in another Zenodo entry.<br> </p>
Data for Finnish Dialect Detection
<p>The data used in the paper "Finnish Dialect Identification: The Effect of Audio and Text".</p> <p><strong>If you use the data, please cite:</strong></p> <p>Hämäläinen, Mika; Alnajjar, Khalid; Partanen, Niko & Rueter, Jack (2021). <a href="https://aclanthology.org/2021.emnlp-main.692/">Finnish Dialect Identification: The Effect of Audio and Text</a>. In <em>Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP)</em>.</p> <p>The <strong>metadata.json </strong>contains the dialectal and normalized transcriptions, the length of the wav files in milliseconds, the path to the wav file, the role of the speaker and the dialect. The <strong>data.zip*</strong> files contain the wav files. They are partial zip files to make Zenodo upload easier. <strong>Code_models.zip</strong> contains the code for training the bimodal model and the final trained model presented in the paper. There is also an OpenNMT model that is the text only model described in the paper. You can use it by running: <em>python3 -m onmt.bin.translate -model nmt-model_step_100000.pt -src source_test.txt -output pred.txt -replace_unk</em></p> <p>Our dataset is licensed under CC BY NC ND 4.0. Academic use only.</p> <p> </p> <p>The corpus is based on <a href="http://urn.fi/urn:nbn:fi:lb-2017020201">Suomenkielen näytteitä</a> (CC BY <a href="http://www.kotus.fi/">Kotimaisten kielten keskus</a>).</p>
Benthic macroinvertebrates of 63 northern Finnish streams along a dissolved organic carbon gradient
<p>Concentrations of dissolved organic carbon (DOC) have increased over the past few decades, causing freshwater browning. The impacts of browning on biodiversity have been little studied, despite many of the individual stressors associated with browning being known to control freshwater communities. We explored the responses of benthic invertebrates along a wide gradient of DOC concentrations (3.6 mg to 27 mg L<sup>-1</sup>) in 63 boreal streams variously impacted by peatland drainage or peat production. DOC was a prime determinant of macroinvertebrate diversity and abundance, with the strongest negative response in algal scrapers. Threshold indicator taxa analysis indicated a community change at 12-13 mg DOC L<sup>-1</sup>, with only four taxa increasing, while 13 taxa decreased along the DOC gradient. Our findings of both a gradual loss and an abrupt change of biodiversity along a browning gradient provide a benchmark against which changes to stream biodiversity relative to the predicted browning trend can be gauged.</p>
Semantically tagged Finnish parliament discussions 1991-2015
<p><strong>Semantically tagged Finnish parliament discussions 1991-2015</strong></p> <p>The original data is this (Rauh et al, 2017):</p> <p>https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/E4RSP9</p> <p>We have imported the raw text out of the original data set without speaker and party tags. The Finnish text has been first tagged with UD2 parser using the Mylly service of the Language Bank of Finland. After UD2 parse, semantic tags have been added to the text with FiST (Kettunen, 2019).</p> <p><strong>Output form</strong></p> <p># newdoc</p> <p># newpar</p> <p># sent_id = 1</p> <p># text = Arvoisa herra puhemies!</p> <p>Arvoisa arvoisa Z99 amod</p> <p>herra#herra#Noun#S2.2m S9 compound:nn</p> <p>puhemies#puhemies#Noun#G1.1/S2 root</p> <p>! PUNCT</p> <p> </p> <p>The output consists of the 1) token word form of the text, 2) lemma of the token, 3) POS, 4) semantic tag and 5) UD2 grammatical relation of the word in the sentence.</p> <p>Our semantic tagger does not resolve ambiguity. If the lexeme has multiple possible semantic tags, they are all included in the output (e.g., herra#herra#Noun#<strong>S2.2m S9</strong> compound:nn). Slash notation in the semantic tags (e.g., puhemies#puhemies#Noun#<strong>G1.1/S2</strong>) indicates that the word can belong to two or more categories (Löfbeg, 2017). If the semantic category of the word is not recognized, the word is tagged with Z99.</p> <p>The data consists of 4 036 269 sentences and ca. 65.247 million words. Lexical coverage of FiST for the data is 86.05 %, i.e. 86% of the words are known for the tagger and marked with a semantic tag.</p> <p><strong>References</strong></p> <p>Kettunen, Kimmo (2019). FiST – towards a Free Semantic Tagger of Modern Standard Finnish. IWCLUL2019, http://aclweb.org/anthology/W19-0306</p> <p>Rauh, Christian; De Wilde, Pieter; Schwalbach, Jan, 2017, "Corp_Eduskundta.Rdata", The ParlSpeech data set: Annotated full-text vectors of 3.9 million plenary speeches in the key legislative chambers of seven European states, https://doi.org/10.7910/DVN/E4RSP9/U8VZHK, Harvard Dataverse, V1.</p> <p>Lofberg, L. (2017). Creating large semantic lexical resources for the Finnish language. [Doctoral Thesis, Lancaster University]. Lancaster University. https://doi.org/10.17635/lancaster/thesis/3</p> <p>UCREL Semantic Analysis System (USAS). https://ucrel.lancs.ac.uk/usas/</p>
Data and R scripts for: Effects of hunting on genetic diversity, inbreeding and dispersal in Finnish black grouse (Lyrurus tetrix)
<p>While intensive hunting activities, such as commercial fishing and trophy hunting, can have profound influences on natural populations, less intensive recreational hunting can also have more subtle effects on animal behaviour, habitat use and movement, with implications for population persistence. Lekking species such as the black grouse (<em>Lyrurus</em> <em>tetrix</em>) may be especially prone to hunting as leks are temporally and spatially predictable, making them easy targets. Furthermore, inbreeding in black grouse is mainly avoided through female-biased dispersal, so any disruptions to dispersal caused by hunting could lead to changes in gene flow, leading to an increasing risk of inbreeding. We therefore investigated the impact of hunting on genetic diversity, inbreeding and dispersal on a metapopulation of black grouse in Central Finland. We genotyped 1,065 adult males and 813 adult females from twelve lekking sites (six hunted, six unhunted) and 200 unrelated chicks from seven sites (two hunted, five unhunted) at up to thirteen microsatellite loci. Our initial confirmatory analysis of sex-specific fine-scale population structure revealed little genetic structure in the metapopulation. Levels of inbreeding did not differ significantly between hunted and unhunted sites in both adults and chicks. However, immigration rates into hunted sites were significantly higher among adults compared to immigration into unhunted sites. We conclude that the influx of migrants into hunted sites may compensate for the loss of harvested individuals, thereby increasing gene flow and mitigating inbreeding. Given the absence of any obvious potential barriers to gene flow in Central Finland, a spatially heterogeneous matrix of hunted and unhunted regions may be crucial to ensure sustainable harvests into the future.</p>
Comparing Finnish universities' publication profiles using multidimensional field-normalized indicators - dataset
<p>This dataset from the VIRTA Publication Information Service consists of the metadata of 241,575 publications of Finnish universities (publication years 2016–2021) merged from yearly datasets downloaded from <a href="https://wiki.eduuni.fi/display/cscvirtajtp/Vuositasoiset+Excel-tiedostot">https://wiki.eduuni.fi/display/cscvirtajtp/Vuositasoiset+Excel-tiedostot</a>.</p> <p>The dataset contains following information:</p> <ul> <li>Organisation: name of the university</li> <li>Publication year: the year of publication</li> <li>Subfield: one of 66 fields of science based on Statistics Finland field of science classification (in Finnish), see the classification in English: <a href="https://www2.stat.fi/en/luokitukset/tieteenala/">https://www2.stat.fi/en/luokitukset/tieteenala/</a></li> <li>Peer-reviewed: 1=peer-reviewed publications, 0=not peer-reviewed publications</li> <li>Science communication: 1=publications aimed at professional and general audiences, 0=peer-reviewed and not peer-reviewed publications aimed at academic audience.</li> <li>Bibliodiversity: 1=peer-reviewed book publications (chapters, monographs and edited volumes) and conference articles, 0=peer-reviewed journal articles.</li> <li>Multilingualism: share of peer-reviewed publications in languages other than English (Finnish, Swedish and other languages).</li> <li>Domestic publishing: 1=peer-reviewed publications in journals and books published in Finland, 0=peer-reviewed publications in journals and books published outside Finland.</li> <li>Domestic collaboration: 1=peer-reviewed publications with co-authors from more than one Finnish university, 0=peer-reviewed publications without co-authors from more than one Finnish university.</li> <li>International collaboration: 1=share of peer-reviewed publications with co-authors affiliated with foreign institutions, 0=share of peer-reviewed publications without co-authors affiliated with foreign institutions.</li> <li>Research performance: 1=peer-reviewed outputs in JUFO levels 2 (“leading”) and 3 (“top”) publication channels, 0=peer-reviewed outputs in JUFO levels 1 (“basic”) and 0 (“other”) publication channels.</li> <li>Open access: 1=peer-reviewed open access publications, including gold, hybrid and green OA, 0=peer-reviewed closed publications.</li> </ul>
Journal metrics as predictors of Research Excellence Framework 2021 results: Comparison of impact factor quartiles and Finnish expert-ratings - dataset
<p>This dataset accompanies the conference submission 'Journal metrics as predictors of Research Excellence Framework 2021 results: Comparison of impact factor quartiles and Finnish expert-ratings'. It contains the data in CSV format, one file per unit of analysis (Units of Assessment, Higher Education Institutions, and Subject Areas).</p> <p>The format of the UoA file is as follows (the other two files are analogous):</p> <ul> <li> <p>institution_name: name of higher education institution (e.g. university)</p> </li> <li> <p>unit_of_assessment_name: UoA name in REF (https://www.ref.ac.uk/panels/units-of-assessment/)</p> </li> <li> <p>main_panel: main panel in REF</p> </li> <li> <p>multiple_submission_letter: blank unless submitted to multiple panels.Exceptionally HEIs may have requested permission to make <a href="https://ref.ac.uk/publications-and-reports/invitation-to-make-requests-for-multiple-submissions-exception-from-submission-for-small-units-and-for-impact-case-studies-requiring-security-clearance/">two submissions from the same UoA to different panels</a>.</p> </li> <li> <p>multiple_submission_name: blank unless submitted to multiple panels</p> </li> <li> <p>non_english: number of articles in language other than English</p> </li> <li> <p>jufo_score_uoa: JUFO score (see paper for calculation details) of UoA</p> </li> <li> <p>jif_score_uoa: JIF score (see paper for calculation details) of UoA</p> </li> <li> <p>ref_score_uoa: REF score (see paper for calculation details) of UoA</p> </li> </ul>
A Large-Scale AIS Datset from Finnish Water
<p>The proposed AIS dataset encompasses a substantial temporal span of 20 months, spanning from April 2021 to December 2022. This extensive coverage period empowers analysts to examine long-term trends and variations in vessel activities. Moreover, it facilitates researchers in comprehending the potential influence of external factors, including weather patterns, seasonal variations, and economic conditions, on vessel traffic and behavior within the Finnish waters.</p> <p>This dataset encompasses an extensive array of data pertaining to vessel movements and activities encompassing seas, rivers, and lakes. Anticipated to be comprehensive in nature, the dataset encompasses a diverse range of ship types, such as cargo ships, tankers, fishing vessels, passenger ships, and various other categories.</p> <p>The AIS dataset exhibits a prominent attribute in the form of its exceptional granularity with a total of 2 293 129 345 data points. The provision of such granular information proves can help analysts to comprehend vessel dynamics and operations within the Finnish waters. It enables the identification of patterns and anomalies in vessel behavior and facilitates an assessment of the potential environmental implications associated with maritime activities.</p> <p>Please cite the following publication when using the dataset:</p> <p><em>TBD</em></p> <p>The publication is available at: <em>TBD</em></p> <p>A preprint version of the publication is available at <em>TBD</em></p> <h3>csv file structure</h3> <h4><a href="#yyyy-mm-dd-locationcsv"></a>YYYY-MM-DD-location.csv</h4> <p>This file contains the received AIS position reports. The structure of the logged parameters is the following: <code>[timestamp, timestampExternal, mmsi, lon, lat, sog, cog, navStat, rot, posAcc, raim, heading]</code></p> <p><code><strong>timestamp</strong></code> I beleive this is the UTC second when the report was generated by the electronic position system (EPFS) (0-59, or 60 if time stamp is not available, which should also be the default value, or 61 if positioning system is in manual input mode, or 62 if electronic position fixing system operates in estimated (dead reckoning) mode, or 63 if the positioning system is inoperative).</p> <p><code><strong>timestampExternal</strong></code> The timestamp associated with the MQTT message received from <a href="http://www.digitraffic.fi/" target="_blank" rel="nofollow noreferrer noopener">www.digitraffic.fi</a>. It is assumed this timestamp is the Epoch time corresponding to when the AIS message was received by digitraffic.fi.</p> <p><code><strong>mmsi</strong></code> MMSI number, Maritime Mobile Service Identity (MMSI) is a unique 9 digit number that is assigned to a (Digital Selective Calling) DSC radio or an AIS unit. Check <a href="https://en.wikipedia.org/wiki/Maritime_Mobile_Service_Identity" target="_blank" rel="nofollow noreferrer noopener">https://en.wikipedia.org/wiki/Maritime_Mobile_Service_Identity</a></p> <p><code><strong>lon</strong></code> Longitude, Longitude in 1/10 000 min (+/-180 deg, East = positive (as per 2's complement), West = negative (as per 2's complement). 181= (6791AC0h) = not available = default)</p> <p><code><strong>lat</strong></code> Latitude, Latitude in 1/10 000 min (+/-90 deg, North = positive (as per 2's complement), South = negative (as per 2's complement). 91deg (3412140h) = not available = default)</p> <p><code><strong>sog</strong></code> Speed over ground in 1/10 knot steps (0-102.2 knots) 1 023 = not available, 1 022 = 102.2 knots or higher</p> <p><code><strong>cog</strong></code> Course over ground in 1/10 = (0-3599). 3600 (E10h) = not available = default. 3 601-4 095 should not be used</p> <p><code><strong>navStat</strong></code> Navigational status, 0 = under way using engine, 1 = at anchor, 2 = not under command, 3 = restricted maneuverability, 4 = constrained by her draught, 5 = moored, 6 = aground, 7 = engaged in fishing, 8 = under way sailing, 9 = reserved for future amendment of navigational status for ships carrying DG, HS, or MP, or IMO hazard or pollutant category C, high speed craft (HSC), 10 = reserved for future amendment of navigational status for ships carrying dangerous goods (DG), harmful substances (HS) or marine pollutants (MP), or IMO hazard or pollutant category A, wing in ground (WIG); 11 = power-driven vessel towing astern (regional use); 12 = power-driven vessel pushing ahead or towing alongside (regional use); 13 = reserved for future use, 14 = AIS-SART (active), MOB-AIS, EPIRB-AIS 15 = undefined = default (also used by AIS-SART, MOB-AIS and EPIRB-AIS under test)</p> <p><code><strong>rot</strong></code> ROTAIS Rate of turn</p> <ul> <li>0 to +126 = turning right at up to 708 deg per min or higher</li> <li>0 to -126 = turning left at up to 708 deg per min or higher</li> <li>Values between 0 and 708 deg per min coded by ROTAIS = 4.733 SQRT(ROTsensor) degrees per min where ROTsensor is the Rate of Turn as input by an external Rate of Turn Indicator (TI). ROTAIS is rounded to the nearest integer value.</li> <li>+127 = turning right at more than 5 deg per 30 s (No TI available)</li> <li>-127 = turning left at more than 5 deg per 30 s (No TI available)</li> <li>-128 (80 hex) indicates no turn information available (default).</li> </ul> <p>ROT data should not be derived from COG information.</p> <p><code><strong>posAcc</strong></code> Position accuracy, The position accuracy (PA) flag should be determined in accordance with the table below:</p> <ul> <li>1 = high (<= 10 m)</li> <li>0 = low (> 10 m)</li> <li>0 = default</li> </ul> <p>See <a href="https://www.navcen.uscg.gov/?pageName=AISMessagesA#RAIM" target="_blank" rel="nofollow noreferrer noopener">https://www.navcen.uscg.gov/?pageName=AISMessagesA#RAIM</a></p> <p><code><strong>raim</strong></code> RAIM-flag Receiver autonomous integrity monitoring (RAIM) flag of electronic position fixing device; 0 = RAIM not in use = default; 1 = RAIM in use. See Table <a href="https://www.navcen.uscg.gov/?pageName=AISMessagesA#RAIM" target="_blank" rel="nofollow noreferrer noopener">https://www.navcen.uscg.gov/?pageName=AISMessagesA#RAIM</a></p> <p>Check <a href="https://en.wikipedia.org/wiki/Receiver_autonomous_integrity_monitoring" target="_blank" rel="nofollow noreferrer noopener">https://en.wikipedia.org/wiki/Receiver_autonomous_integrity_monitoring</a></p> <p><code><strong>heading</strong></code> True heading, Degrees (0-359) (511 indicates not available = default)</p> <h4><a href="#yyyy-mm-dd-metadatacsv"></a>YYYY-MM-DD-metadata.csv</h4> <p>This file contains the received AIS metadata: the ship static and voyage related data. The structure of the logged parameters is the following: <code>[timestamp, destination, mmsi, callSign, imo, shipType, draught, eta, posType, pointA, pointB, pointC, pointD, name]</code></p> <p><code><strong>timestamp</strong></code> The timestamp associated with the MQTT message received from <a href="http://www.digitraffic.fi/" target="_blank" rel="nofollow noreferrer noopener">www.digitraffic.fi</a>. It is assumed this timestamp is the Epoch time corresponding to when the AIS message was received by digitraffic.fi.</p> <p><code><strong>destination</strong></code> Maximum 20 characters using 6-bit ASCII; @@@@@@@@@@@@@@@@@@@@ = not available For SAR aircraft, the use of this field may be decided by the responsible administration</p> <p><code><strong>mmsi</strong></code> MMSI number, Maritime Mobile Service Identity (MMSI) is a unique 9 digit number that is assigned to a (Digital Selective Calling) DSC radio or an AIS unit. Check <a href="https://en.wikipedia.org/wiki/Maritime_Mobile_Service_Identity" target="_blank" rel="nofollow noreferrer noopener">https://en.wikipedia.org/wiki/Maritime_Mobile_Service_Identity</a></p> <p><code><strong>callSign</strong></code> 7?=?6 bit ASCII characters, @@@@@@@ = not available = default Craft associated with a parent vessel, should use “A” followed by the last 6 digits of the MMSI of the parent vessel. Examples of these craft include towed vessels, rescue boats, tenders, lifeboats and liferafts.</p> <p><code><strong>imo</strong></code> 0 = not available = default – Not applicable to SAR aircraft</p> <ul> <li>0000000001-0000999999 not used</li> <li>0001000000-0009999999 = valid IMO number;</li> <li>0010000000-1073741823 = official flag state number.</li> </ul> <p>Check: <a href="https://en.wikipedia.org/wiki/IMO_number" target="_blank" rel="nofollow noreferrer noopener">https://en.wikipedia.org/wiki/IMO_number</a></p> <p><code><strong>shipType</strong></code></p> <ul> <li>0 = not available or no ship = default</li> <li>1-99 = as defined below</li> <li>100-199 = reserved, for regional use</li> <li>200-255 = reserved, for future use Not applicable to SAR aircraft</li> </ul> <p>Check <a href="https://www.navcen.uscg.gov/pdf/AIS/AISGuide.pdf" target="_blank" rel="nofollow noreferrer noopener">https://www.navcen.uscg.gov/pdf/AIS/AISGuide.pdf</a> and <a href="https://www.navcen.uscg.gov/?pageName=AISMessagesAStatic" target="_blank" rel="nofollow noreferrer noopener">https://www.navcen.uscg.gov/?pageName=AISMessagesAStatic</a></p> <p><code><strong>draught</strong></code> In 1/10 m, 255 = draught 25.5 m or greater, 0 = not available = default; in accordance with IMO Resolution A.851 Not applicable to SAR aircraft, should be set to 0</p> <p><code><strong>eta</strong></code> Estimated time of arrival; MMDDHHMM UTC</p> <ul> <li>Bits 19-16: month; 1-12; 0 = not available = default</li> <li>Bits 15-11: day; 1-31; 0 = not available = default</li> <li>Bits 10-6: hour; 0-23; 24 = not available = default</li> <li>Bits 5-0: minute; 0-59; 60 = not available = default</li> </ul> <p>For SAR aircraft, the use of this field may be decided by the responsible administration</p> <p><code><strong>posType</strong></code> Type of electronic position fixing device</p> <ul> <li>0 = undefined (default)</li> <li>1 = GPS</li> <li>2 = GLONASS</li> <li>3 = combined GPS/GLONASS</li> <li>4 = Loran-C</li> <li>5 = Chayka</li> <li>6 = integrated navigation system</li> <li>7 = surveyed</li> <li>8 = Galileo,</li> <li>9-14 = not used</li> <li>15 = internal GNSS</li> </ul> <p><code><strong>pointA</strong></code> Reference point for reported position.</p> <p>Also indicates the dimension of ship (m). For SAR aircraft, the use of this field may be decided by the responsible administration. If used it should indicate the maximum dimensions of the craft. As default should A = B = C = D be set to “0”</p> <p>Check: <a href="https://www.navcen.uscg.gov/?pageName=AISMessagesAStatic#_Reference_point_for" target="_blank" rel="nofollow noreferrer noopener">https://www.navcen.uscg.gov/?pageName=AISMessagesAStatic#_Reference_point_for</a></p> <p><code><strong>pointB</strong></code> See above</p> <p><code><strong>pointC</strong></code> See above</p> <p><code><strong>pointD</strong></code> See above</p> <p><code><strong>name</strong></code> Maximum 20 characters 6 bit ASCII "@@@@@@@@@@@@@@@@@@@@" = not available = default The Name should be as shown on the station radio license. For SAR aircraft, it should be set to “SAR AIRCRAFT NNNNNNN” where NNNNNNN equals the aircraft registration number.</p>
Data and R scripts for: Effects of hunting on genetic diversity, inbreeding and dispersal in Finnish black grouse (Lyrurus tetrix)
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Microsatellite data of Vincetoxicum hirundinaria offspring and their inferred mother plants from 13 populations in the South-Western Finnish Archipelago
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Benthic macroinvertebrates of 63 northern Finnish streams along a dissolved organic carbon gradient
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Finnish Court Records-sub500. A dataset of Finnish notarial records (19th Century)
<p>This dataset is a selection of 500 pages from the Renovated District Court Records (19th century), one of the largest collections in the National Archives of Finland. The documents consists of records of deeds, mortgages, traditional life-annuity, among others.<br> This dataset contains images with one or two document pages, and it is annotated at image level using six different<br> region types along with the baselines and line level transcription (Swedish). This blend of single page and double page images is a common complexity found in historical documents.</p> <p>Layout labels are:<br> 1. page-number: the page number, commonly placed on the top-right corner of the image, <br> 2. paragraph: a paragraph placed on a single page image or on the left side of a double page image.<br> 3. paragraph_2: a paragraph placed on the right side of a double page image.<br> 4. marginalia: any annotation on the margin of the document,<br> 5. table: a table placed on a single page image or on the left side of a double page image.<br> 6. table_2: a table placed on the right side of a double page image.</p> <p>The images along with their respective ground-truth was compiled in PAGE compliant XML format by the <a href="https://www.arkisto.fi">National Archives of Finland</a> and the HTR group of the <a href="http://www.prhlt.upv.es">Pattern Recognition and Human Language Technologies Research Center</a>.</p>
Anonymised dataset about Finnish teachers' digital technology usage in teaching
<p>Data have been collected in Finland in 2017–2019 from basic education teachers.The dataset is fully anonymised to make it suitable for public opening to support the reported results submitted for publication.</p> <p>Dataset contains the following variables:</p> <ol> <li>Gender (0=female, 1 = male)</li> <li>Municipality (unique numeric identifier)</li> <li>School (unique numeric identifier)</li> <li>Administrative_district (unique numeric identifier)</li> <li>Usage_of_computers_in_teaching (0 = “never”, 1 = “sometimes”, 2 = “weekly”, 3 = “daily”, 4 = “several hours per day”)</li> <li>Usage_of_tablets_in_teaching (0 = “never”, 1 = “sometimes”, 2 = “weekly”, 3 = “daily”, 4 = “several hours per day”)</li> <li>Usage_of_smartphones_in_teaching (0 = “never”, 1 = “sometimes”, 2 = “weekly”, 3 = “daily”, 4 = “several hours per day”)</li> <li>Usage_of_digital_learning_environments_in_teaching (0 = “never”, 1 = “sometimes”, 2 = “weekly”, 3 = “daily”, 4 = “several hours per day”)</li> <li>Usage_of_online_learning_materials_in_teaching (0 = “never”, 1 = “sometimes”, 2 = “weekly”, 3 = “daily”, 4 = “several hours per day”)</li> <li>Usage_of_games_in_teaching (0 = “never”, 1 = “sometimes”, 2 = “weekly”, 3 = “daily”, 4 = “several hours per day”)</li> <li>Usage_of_internet_for_information_in_teaching (0 = “never”, 1 = “sometimes”, 2 = “weekly”, 3 = “daily”, 4 = “several hours per day”)</li> <li>Usage_of_videa_sharing_services_in_teaching (0 = “never”, 1 = “sometimes”, 2 = “weekly”, 3 = “daily”, 4 = “several hours per day”)</li> <li>Usage_of_blogs_in_teaching (0 = “never”, 1 = “sometimes”, 2 = “weekly”, 3 = “daily”, 4 = “several hours per day”)</li> <li>Usage_of_networking_services_in_teaching (0 = “never”, 1 = “sometimes”, 2 = “weekly”, 3 = “daily”, 4 = “several hours per day”)</li> <li>Usage_of_digital_assessment_in_teaching (0 = “never”, 1 = “sometimes”, 2 = “weekly”, 3 = “daily”, 4 = “several hours per day”)</li> <li>Usage_of_mobileapps_in_teaching (0 = “never”, 1 = “sometimes”, 2 = “weekly”, 3 = “daily”, 4 = “several hours per day”)</li> <li>Usage_of_email_in_teaching (0 = “never”, 1 = “sometimes”, 2 = “weekly”, 3 = “daily”, 4 = “several hours per day”)</li> <li>Usage_of_office_suite_in_teaching (0 = “never”, 1 = “sometimes”, 2 = “weekly”, 3 = “daily”, 4 = “several hours per day”)</li> <li>Total_scores_in_ICTskilltest (range 0-30)</li> <li>Age (years in numbers)</li> <li>Digital_self_efficacy (perceived level of competence on a scale of 0-100% in relation to one's own work)</li> <li>In_service_training (perceived adequacy level on a scale of 0 to 100% in relation to one's own work)</li> <li>STEM_teacher (in the case of a teacher of STEM subjects = 1, otherwise = 0)</li> <li>Humanities_social_science_teacher (in the case of a teacher of humanities or social science subjects = 1, otherwise = 0)</li> <li>Arts_skills_teacher (in the case of a teacher of arts and skills subjects = 1, otherwise = 0)</li> <li>Use_of_devices_for_teaching (the sum variable of the use of digital devices, i.e., the maximum use of any type of device)</li> <li>Versatility_of_usage (the sum variable for regular (= at least weekly) use of different applications)</li> <li>Teacher_type (0 = classroom teacher, 1 = subject teacher, missing value = other teaching staff)</li> <li>Classroom_teacher in the case of a classroom teacher = 1, otherwise = 0</li> </ol>
Data from: An analysis of travel reports of the Finnish botanical expeditions to Russian Lapland (Murmansk Region and Northern Karelia) in 1861 and 1863
<p>Finnish botanical expeditions, which were made to Russian Lapland (present-day Murmansk Region and northern Karelia, Russia) in 1861 and 1863, published travel reports with preliminary information, which contained numerous floristic novelties and phytogeographical observations but have been overlooked in present-day studies. Two reports appeared in print, by Gustav Selin on the expedition made in 1861, and by Nils Isak Fellman on the expedition made in 1863. We analysed mentions of vascular plant species published in these travel reports in order to trace and evaluate first records and localities of rare and legally protected species on the basis of herbarium vouchers kept at H. In spite of high self-claims, Selin actually reported 9 species new to present-day Murmansk Region and 1 species new to Republic of Karelia, and 4 species of vascular plants that are currently under legal protection in Murmansk Region, whereas Fellman reported 11 species new to Murmansk Region and 5 species new to Karelia, with 34 species under legal protection in Murmansk Region. First records of alien plants were 7 species from Selin and 4 species from Fellman. These numbers brought the contemporary floristic knowledge in Russian Lapland to 504 species of native plants (50% of the current total) and 54 species of alien plants (11% of the current total). Fellman's report included the first phytogeographical observations from the Kola Peninsula, with the first botanical limits observed, and the first descriptions of key botanical territories which are currently under strict protection. This study contributes to botanical history, plant protection and management of plant invasions in Murmansk Region.</p>
Finnish National Election Study 2011: Telephone Interviews among Finnishspeaking Voters (example assignm.)
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Comparing Action-Oriented Language in the Assessment of EFL Writing: An Action Research for Combining the First-Year Instruction of the National Curriculum and the International Baccalaureate (IB) Diploma Program in a Finnish High School
<p>The data here were used to complete my master's thesis. Data have been anonymized and can thus be used freely. The thesis can be downloaded from the following URL:</p> <p>https://helda.helsinki.fi/handle/10138/327351</p>
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