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zenodo40/100

Data analysis Protocol for a Joint Study into the Impacts of AI on professional Competencies of IT Professionals and Implications for Computing Students. ITiCSE 2024 Working Group 02.

<h1><a name="_Toc169648661"></a>Overview</h1>   The purpose of this protocol is to help us define a common protocol for sharing and analysing data for the ITiCSE 2024 working group: “WG02: A Multi-Institutional-Multi-National Study into the Impacts of AI on Work Practices of IT Professionals and Implications for Computing Students”.  Excerpts from the working group plan to place the protocol in context (Clear et al., 2024) are given below.   Background and Related Work As Artificial Intelligence (AI) continues to make its presence felt in transforming workplaces around the world [1,10], and the Information Technology industry in particular, it is essential to understand its impact on the work practices of IT professionals, and the implications for computing students and curricula. This research project builds on work initiated jointly, in Sweden, New Zealand and Scotland, investigating concerns about the increasing impacts of Artificial Intelligence in IT Sector workplaces for employee work engagement [11,13,1] and the implications for tertiary study, assessment and curricula in computing [4, 8, 10, 9].  “Work engagement”, has been defined as the positive inner state where employees are fully present and engaged in their work, and is closely linked to motivation, learning, productivity, and accountability [11, 13]. Within the context of (Generative) AI at work, IT professionals have been noted as early adopters of AI [10, 1]. Their involvement in implementing and utilising AI technologies can provide valuable insights into the interplay between AI and work engagement.  The implications for students are significant as future IT professionals, who must acquire and enhance competencies to adapt and thrive in digital workplaces.   2           Goals of the Working Group By exploring the relationship between work engagement and learning, this study aims to shed light on the dynamics that drive employee engagement and its connection to the professional development of competencies. The previous study has interviewed IT professionals with the following research questions (RQ):   RQ1: How does AI influence work engagement for IT professionals? RQ2: How does AI affect the socio-technical work dynamics for IT professionals? RQ3: What are the implications of integrating AI on the acquisition and enhancement of professional competencies and the learning processes of IT professionals?   3           Methodology This working group aims to analyse the corpus of interview data collected from multiple countries to better understand the implications for computing students, tertiary computing education curricula and assessment of the new professional competencies emerging from this work. This study informed by the literature on work engagement, automation and motivation for IT professionals [11, 13], will use a combination of multi-vocal literature review [7] and qualitative research methods [2, 5], including thematic analysis of the interviews, to investigate the state of the practice in and challenges IT Professionals face within their local/global work contexts. The literature on professional competencies in computing [4, 3, 6] will be drawn upon to characterise the new needs identified in this analysis.  Further implications for computing curricula design and assessment will be developed from this analysis. REFERENCES [1]    ACM Technology Policy Council. 2023. Principles for the development, deployment, and use of generative AI technologies, ACM New York. [2]    Braun, V. and Clarke, V. 2021. One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qualitative research in psychology, 18 (3). 328-352. [3]    Clear, A., Clear, T., Vichare, A., Charles, T., Frezza, S., Gutica, M., Lunt, B., Maiorana, F., Pears, A. and Pitt, F. 2020. Designing Computer Science  Competency Statements: A Process and Curriculum Model for the 21st Century in Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education, ACM, New York. [4]    Clear, A., Parrish, A. and CC2020 Task Force. 2020. Computing Curricula 2020 - CC2020 - Paradigms for Future Computing Curricula ACM and IEEE-CS eds. A Computing Curricula Series Report ACM, New York. [5]    Cruzes, D.S. and Dyba, T. 2011. Recommended steps for thematic synthesis in software engineering. in 2011 international symposium on empirical software engineering and measurement, IEEE, 2011, 275-284. [6]    Frezza, S., Clear, T. and Clear, A. 2020. Unpacking Dispositions in the CC2020 Computing Curriculum Overview Report in 2020 IEEE Frontiers in Education Conference (FIE), IEEE, Uppsala, Sweden. [7]    Garousi, V., Felderer, M., & Mäntylä, M. V. 2019. Guidelines for including grey literature and conducting multivocal literature reviews in software engineering. Information and Software Technology, 106. 101-121 [8]    Jacques, L. 2023. Teaching CS-101 at the Dawn of ChatGPT. ACM Inroads, 14 (2). 40-46. [9]    Liffiton, M., Sheese, B., Savelka, J. and Denny, P. 2023. CodeHelp: Using Large Language Models with Guardrails for Scalable Support in Programming Classes. arXiv preprint arXiv:2308.06921. [10]  Prather, J., Denny, P., Leinonen, J., Becker, B.A., Albluwi, I., Craig, M., Keuning, H., Kiesler, N., Kohn, T. and Luxton-Reilly, A. 2023. The robots are here: Navigating the generative ai revolution in computing education. arXiv preprint arXiv:2310.00658. [11]  Roto, V., Palanque, P. and Karvonen, H., 2019. Engaging automation at work–a literature review. in Human Work Interaction Design. Designing Engaging Automation: 5th IFIP WG 13.6 Working Conference, HWID 2018, Espoo, Finland, August 20-21, 2018, Revised Selected Papers 5, Springer, 158-172. [12]  SFIA Foundation. 2023. SFIA skills aligned to EU ICT Profiles, SFIA Institute, London. [13]  Sharp, H., Baddoo, N., Beecham, S., Hall, T. and Robinson, H. 2009. Models of motivation in software engineering. Information and software technology, 51 (1). 219-233.

opencc-by-4.0Sep 2024View details →

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Data set from: Can laboratory-based XAFS compete with XRD and Mössbauer spectroscopy as a tool for quantitative species analysis?

Abstract: This work investigated the capability of quantitative laboratory X-ray Absorption Fine Structure Spectroscopy (lab-XAFS) via Linear Combination Fitting (LCF) of reference spectra in comparison with quantitative X-ray diffraction (XRD) and Mössbauer spectroscopy. While lab-XAFS already show good results when performing LCF with significant different spectra of the species to be identified, the method is challenging when the reference spectra and possibly species in the sample are very similar as it is the case for α-Fe2O3, γ- Fe2O3 and Fe3O4. For this investigation an iron oxide mineral with origin from Mexico (here named Mexican Magnetite) with different iron oxide phases was used and measured using all three methods.   This data set contains the raw data of the work “Can laboratory-based XAFS compete with XRD and Mössbauer spectroscopy as a tool for quantitative species analysis? Critical evaluation using the example of a natural iron ore” of XAFS, XRD and Mössbauer measurements. This includes XAFS, Mössbauer and XRD spectra of the reference materials α-Fe2O3, Fe3O4 and the sample Mexican magnetite, the XAFS spectra of the reference material γ- Fe2O3 and the XAFS, XRD and Mössbauer spectra of three different α-Fe2O3/Fe3O4 mixtures.   Sample information/sample list sample/references: The sample and the corresponding short cut name used in the data files is listed. Furthermore the method the sample was measured with is also listed. <table> <tbody> <tr> <td> Short cut name </td> <td>  Sample/reference </td> <td> Measured with </td> </tr> <tr> <td> MexicanMagnetite </td> <td>  Iron oxide mineral with origin in Mexico </td> <td> XAFS, XRD, Mössbauer </td> </tr> <tr> <td> Fe2O3 </td> <td> Fe2O3-alpha / Hematite </td> <td> XAFS, XRD, Mössbauer </td> </tr> <tr> <td> Fe3O4 </td> <td> Fe3O4 / Magnetite </td> <td> XAFS, XRD, Mössbauer </td> </tr> <tr> <td> Fe </td> <td> Iron powder </td> <td> XAFS </td> </tr> <tr> <td> Fe2O3-alpha </td> <td> Fe2O3-alpha / Hematite </td> <td> XAFS </td> </tr> <tr> <td> Fe2O3-gamma </td> <td> Fe2O3-gamma / Maghemite </td> <td> XAFS </td> </tr> <tr> <td> 30-70 </td> <td> Mixture of  30 % Fe2O3-alpha/ 70 %Fe3O4 </td> <td> XAFS, XRD, Mössbauer </td> </tr> <tr> <td> 50-50 </td> <td> Mixture of  50 % Fe2O3-alpha/ 50 %Fe3O4 </td> <td> XAFS, XRD, Mössbauer </td> </tr> <tr> <td> 70-30 </td> <td> Mixture of  70 % Fe2O3-alpha/ 30 %Fe3O4 </td> <td> XAFS, XRD, Mössbauer </td> </tr> </tbody> </table>   Mixtures ratios: The prepared Fe2O3-Fe3O4 model mixtures with the weight-in ratios and the actual achieved mass percentage ratio between the two iron species, taken impurities of the used materials into account, are listed below. The short cut name is the name used in the data files (see table above). <table> <tbody> <tr> <td> Short cut name </td> <td> Actual achieved weigh-in ratios m(Fe2O3)/m(Fe3O4)* </td> <td> Actual achieved mass percentage ratios ωrel(Fe2O3) / ωrel(Fe3O4) </td> </tr> <tr> <td> 30-70 </td> <td> 0.31380 g / 0.7059 g </td> <td> 31.8 / 68.2 </td> </tr> <tr> <td> 50-50 </td> <td> 0.5140 g / 0.5174 g </td> <td> 50.6 / 49.4 </td> </tr> <tr> <td> 70-30 </td> <td> 0.7037 g / 0.3041 g </td> <td> 70.5 / 29.5 </td> </tr> </tbody> </table> *the given masses here, ar the masses of the materials of the mixtures before sampel prepration. For the sample prepration the mass  applied on the tape or mixed with wax is about 5-10 mg. Spectrometer Specifications XAFS: The experimental setup for the laboratory XAFS measurement is based on the Highly Annealed Pyrolytic Graphite (HAPG) von Hámos spectrometer with the use of a cylindrically shaped crystal. As detector unit the pixelated X-ray hybrid-CMOS detector Dectris Eiger2 R 500k was used. The area of detection is 77.3 mm x 38.6 mm with a pixel size of 75 µm x 75 µm. The X-ray source was a water-cooled micro focus X-ray tube with molybdenum as anode material, a power of 30 Watt optimised at 15 kV and a spot size of 70 µm. Sample preparation: α-Fe2O3, Fe3O4, the three α-Fe2O3/Fe3O4 mixtures and the sample Mexican magnetite were applied on adhesive tape, sliced in 1cm x 1cm pieces characterized with XRF to determine the iron content as [Q] = mg/cm² and then stacked by taking the iron content of each slice into account to achieve an absorption of µ*Q of about 1 at the edge. The γ- Fe2O3 and also the three α-Fe2O3/Fe3O4 mixtures were prepared as Pellet. Here the sample material was mixed with Hoechst Wax C in a ratio of 1:6, mixed in a vortex shaker and then pressed with a hydraulic press with a Pellet diameter of 13 mm. The amount of the wax/sample powder material was weight before inserting in the press to the amount of Q to achieve a µ*Q of about 1 with a 13 mm Pellet. Shifts of the energy axis as well as a widening or compression of this axis could be present when comparing the data with other data sets of other spectrometer or synchrotron radiation facilities, since no precise energy calibration was carried out due to the reason that the samples were compared to the measured references and would have the same shift, widening or compression.   XRD: Two different commercial XRD set ups have been used. For the Mexican magnetite the Benchtop XRD spectrometer Bruker D2Phaser with a Cobalt X-ray source and a SSD160 detector (active length = 12 mm) was used. The measurement range was 10°- 90° 2theta with 0.014° step size and 4.8 s/step, resulting in a total measurement time of 8h. During the measurement the sample was rotated with 10 rpm. The sample was filled in PMMA-holders (Ø 2.5 mm) using the top-loading technique. The analysis was carried out using a 1-mm fixed divergence slit, a 2.5° primary and a 4° secondary soller collimator, a fixed knife edge (3 mm above the sample surface), and an Fe Kβ filter (2.5). For the X-ray diffraction measurements of the α-Fe2O3/Fe3O4 mixtures and the pure references a Panalytical X’Pert PRO diffractometer with a Bragg-Brentano setup was used. The diffractometer operates with a Cu anode and without a monochromator (Cu-Kalpha radiation) at 40 kV and 30 mA. The diffraction data were obtained over a measurement range of 10–120° 2theta. Samples were applied flat on a cut-off Si wafer attached to the sample holder.   Mössbauer: Mössbauer spectroscopy was performed at a MIMOS II type spectrometer with a 57Co source (in rhodium matrix). For the analyses the 57Fe-γ-line E = 14.4 keV was used and α-iron (α-Fe foil) was applied for the velocity calibration before the samples were analyzed. The samples were prepared in plastic powder sample holders and measured in transmission mode at room temperature. The measurement time varied between 12 h and 120 h depending on the sample.   Information on data sets XAFS - this folder contains the XAFS spectra as intensity file with I0 (without the sample) and the It (transmission signal through the sample) for each sample. Multiple samples (It) share the same I0 and are therefore in the same data set. The Number in the filename between “XAFS“ and “data-set..” is the date of the measurement in the following format: YYYY_MM_DD. The first column in each file is the energy in unit eV. The abbreviation “WP” after each sample name in the header means “Wax Pellet” and indicates that the measurement was performed on a sample prepared as a wax pellet, the number (WP1) indicates the number of the pellet. Two pellets of each mixture were prepared to investigate the influence of the sample preparation. If the sample name is missing “WP#” the sample was prepared on adhesive tape as described above. The information on the contents of each data set as well as the measurement time (t = #h) for each It of the sample/reference can be found in data_dictionary_v2.txt. The intensity is normalized to counts per 1800 seconds in a 0.25 eV (for data-set-1) and 1 eV (for data-set-2, data-set-3 and data-set-4) energy interval with the indicated central bin energy.   XRD - this folder contains the raw intensity files over 2theta (ASC-file). Each sample has its own file with the first column for the 2theta in unit degree and the second column for the measured intensity. The Number in the file name between XRD and sample name (e. g. Fe2O3, 30-70) is the date of the measurement in the following format: YYYY_MM_DD.   MOESSBAUER - this folder contains the recoil Lorentz site analysis fit data of the samples. The files  consist of the observed intensity (Iobs) over the velocity (v (mm/s)), including the calcucalted intensity (Icalc) and the fits of the subspectra (Sextet Site 1, etc. ).  Each sample has it owns file. While the references substances  Fe2O3 and Fe3O4 were measured between 2016 and 2019, the MexicanMagnetite was measured 2020. An exact measurement date can’t be determined anymore.   The corresponding sample to the short cut name (e. g. Fe2O3, 30-70,..) in the files can be found above and is listed in the data_dictionary.txt file as well.

opencc-by-4.0May 2024View details →

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RESEARCH OVERVIEW ABOUT COMPETENCIES OF STARTUPS

Front the current scenario of scientific research about startups, the question that this study focuses on answering is: “How is the current research panorama of competencies used in ventures classified as startups?” To answer the research problem described, the general objective of this study is: (i) to show the current research panorama about startup competencies. As a secondary objective: (ii) to map the main competencies of startups present in the literature. The scientific gap that this work seeks to response is create a competency framework for early-stage enterprises, in this case, startups. A group of competencies of startups operationalized in the literature were founded and can guide the theoretical framework of future works about the startup business environments, the association with their life cycle and main research themes. The database was did to help the systematic review according to these principles [1]: (i) create a research problem that guides the research; (ii) choose the aspect to be analyzed in the literature; (iii) filter the collected data according to their relevance to the research problem; and (iv) analyze and interpret the data. The databases chosen were "Scopus" and "Web of Science" taking into account the areas "business", "business finance", "economics" and "management" in the Web of Science, and "business, management and accounting" and “economics, econometric and finance” in the Scopus. The research was carried out between January and April 2020 and January 2022. The choice for these databases occurred due to their databases contain most relevant journals in these areas in the literature [2,3]. There was no predetermined period of time in this research, but the authors only considered publications that used “blind review” process by peers. The authors used the keywords “startups”, “startup capabilities”, “startup competence”, “startup competencies” and “competencies” to collect the data and obtain the largest possible number of publications about the subject proposed. A total of 1,953 scientific articles published between 1938 and 2021 were found. Firstly, the authors excluded works that had duplication between the two platforms (the same work appearing on both) or that had no relationship with the area of administration, reducing the number of scientific articles to 1,205 published between 1976 and 2021. Next, works that did not specifically deal with topics related to startups were excluded, obtaining 148 articles published between 1996 and 2021. Finally, works that did not deal with startup competencies were excluded, obtaining 71 articles published between 2000 and 2021, that were described in detail in the database. In a bibliometric view, the articles described in this data base were classified according to descriptive (most cited journals, country of origin and year of publication) and methodological (research method) characteristics; in addition to the results (main research topic) and citations (most cited journals). All selected articles were managed by this database plotted in Microsoft Excel with the reference of each publication and its basic information (abstract, keywords, database, type of study and so on). From the reading of the selected papers, the main competences related to startups were mapped and identified.

opencc-by-4.0Jan 2022View details →

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Data Steward Professional: Reference dataset of Data Steward related job vacancies for competences assessment

Data Stewardship vacancies collection to support FAIRsFAIR Data Stewardship Professional Competence Framework This dataset is provided to validate and support the analysis of Data Stewardship competences. The dataset includes a collection of vacancies from the popular job search website <a href="http://indeed.com/">indeed.com</a> that responded to the search term "Data Steward". Acknowledgment The research leading to these results has received funding from the Horizon2020 projects FAIRsFAIR (grant number 831558) References FAIRsFAIR Project Deliverable D7.3 Data Stewardship Professional Competence Framework, Work in Progress. To be published Feb 2021 Yuri Demchenko, Lennart Stoy, Research Data Management and Data Stewardship Competences in University Curriculum, In Proc. Data Science Education (DSE), Special Session, EDUCON2021 – IEEE Global Engineering Education Conference, 21-23 April 2021, Vienna, Austria

opencc-by-4.0Feb 2022View details →

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Artificial Intelligence: Professional reference dataset of Artificial Intelligence professional competences analysis based on the job market

Artificial Intelligence vacancies collection to support FAIRsFAIR Artificial Intelligence Professional Competences This dataset is provided as validation and support for the analysis of Artificial Intelligence competences. The dataset includes a collection of vacancies from the job application website <a href="http://indeed.com/">indeed.com</a> that responded to the search term "Artificial Intelligence". The used search term could be easily adjusted in the provided code at <a href="https://github.com/atomcracker/Competence_analysis.git">Github Repository</a>. The heavy extensive research analysis is reflected in graphs, described and reflected in <a href="https://scripties.uba.uva.nl/search?id=727184">Thesis</a>.

opencc-by-4.0Mar 2022View details →

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Dataset for paper titled: Conceptual preferences can be transmitted via selective social information use between competing wild bird species

<a name="_Hlk66629591"></a>Concept learning is considered a high-level adaptive ability. Thus far, it has been studied in laboratory via asocial trial and error learning. Yet, social information use is common among animals but it remains unknown whether concept learning by observing others occurs. We tested whether pied flycatchers (Ficedula hypoleuca) form conceptual relationships from the apparent choices of nest-site characteristics (geometric symbol attached to the nest box) of great tits (Parus major). Each wild flycatcher female (n = 124) observed one tit pair that exhibited an apparent preference for either a large or a small symbol and was then allowed to choose between two nest boxes with a large and a small symbol, but the symbol shape was different to that on the tit nest. Older flycatcher females were more likely to copy the symbol size preference of tits than yearling flycatcher females when there was a high number of visible eggs or a few partially visible eggs in the tit nest. However, this depended on the phenotype; copying switched to rejection as a function of increasing body size. Possibly the quality of and overlap in resource use with the tits affected flycatchers' decisions. Hence, our results suggest that conceptual preferences can be horizontally transmitted across co-existing animals, which may increase the performance of individuals that utilize concept learning abilities in their decision-making.

opencc-zeroMay 2022View details →

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Challenges of the New Accreditation in Digital Competences for Citizens (ACTIC): Update, Validation and Results

The aim of this study is to explain the process used to update and validate the Catalan Accreditation of Information and Communications Technology Skills (ACTIC), conducted by the Open University of Catalonia and the Blanquerna Foundation of Ramon Llull University, at the initiative of the Catalan Department for Digital Policy and Public Administration, Government of Catalonia. Using a mixed method, the study is divided into 3 phases and presents the definitions of the 5 competence areas, 19 competences, 3 achievement levels and a total of 233 indicators. The definitions were validated by a group of experts. As a result of the study, three key dimensions have emerged that improve digital awareness among citizens while empowering them and providing them with a way of having their skills accredited and acknowledged in the workplace: (i) identity, centred around participatory, social, ethical and civic issues; (ii) skills learning among citizens; and (iii) technological development and digital autonomy of citizens.

opencc-by-4.0May 2022View details →

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Extract from the PEAPL framework : Modelling "Writing sentences" competency (French as the schooling language)

Competences, skills and knowledges that make up "writing sentences" competency, based on the linguistic praxeological organization of French as the schooling language (https://doi.org/10.5281/zenodo.4001381). This is an extract of the general framework, some of the visible objects are linked to other objects in other main competences. Orange links show how pedagogic ressources (game levels) are linked to framework objects. This framework is used for the PEAPL (peapl.eu) project to link activities in the GamesHub platform (for example activities using "L'Orthodyssée des Gram" grammar online game, available at https://www.lafamillegram.ch/#)

opencc-by-4.0May 2022View details →

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Figure 1 in HighRes for journal article "Critical digital literacy as a key for (post)digital citizenship: an international review of teacher competence frameworks"

Detail for the figure: Figure 1. Location and scope of the sample of TCFs analysed in this study. Created with mapchart.net In the following article: Villar-Onrubia, D., Morini, L., Marín, V. I., & Nascimbeni, F. (2022). Critical digital literacy as a key for (post)digital citizenship: an international review of teacher competence frameworks. Journal of e-Learning and Knowledge Society, 18(3), 128-139. https://doi.org/10.20368/1971-8829/1135697

opencc-by-4.0Dec 2022View details →

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Fig. 1 in German CULex pipienS biotype MoLeStUS and CULex torrentiUM are vector-competent for Usutu virus

Fig. 1 Comparison of the feeding and survival rates (from 0 to 14/16 dpi) of the four tested mosquito populations. Data values above the bars indicate the number of fully engorged or survived females per species, respectively. Numbers in brackets specify the ratio of engorged and survived females to the total number of females exposed to a blood meal or subjected to the experiment (minus day-0 samples), respectively. Error bars represent 95% confidence intervals. *P <0.05, **P <0.01, and ***P <0.001 by generalized binomial regression models or Fisher's exact test with Bonferroni correction. †Cx. pipiens biotype molestus laboratory colony from "Wendland," Lower Saxony, Germany. ‡Cx. pipiens biotype molestus laboratory colony from Novi Sad, the Republic of Serbia. §Cx. torrentium field-collected colony near Berlin and Bonn, North Rhine-Westphalia, Germany. ¶Ae. aegypti laboratory colony from Malaysia (Bayer CropScience, Langenfeld, Germany)

opencc-by-4.0Dec 2020View details →

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Fig. 1 in Competing invaders: Performance of two Anguillicola species in Lake Bracciano

Fig. 1. Life cycle of Anguillicola crassus. The basic life cycle (blue arrow) includes eels as final hosts and copepods as intermediate hosts. By integrating additional paratenic hosts (e.g. fish), the life cycle can be extended (white arrow).Source: (Moravec, 2006).

opencc-by-4.0Apr 2015View details →

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Fig. 2 in Competing invaders: Performance of two Anguillicola species in Lake Bracciano

Fig. 2. Population growth rate. The relationship between the number of adult individuals per host and the days post infection is shown. The lines represent model predictions and the dots represent experimental data.

opencc-by-4.0Apr 2015View details →

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Fig. 3 in Competing invaders: Performance of two Anguillicola species in Lake Bracciano

Fig. 3. Development to L3 in intermediate host. Days post infection (dpi) until Anguillicola spp. larvae develop into the infective L3 at 20 ̊C. Most A. crassus larvae develop within 17 dpi while the majority of A. novaezelandiae larvae need 23 dpi to complete the development in the intermediate host.

opencc-by-4.0Apr 2015View details →

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Fig. 2 in Relative competence of native and exotic fish hosts for two generalist native trematodes

Fig. 2. Mean worm size of the trematodes Telogaster opisthorchis (a) and Stegodexamene anguillae (b) in experimentally infected exotic brown trout and rainbow trout, and native longfin eel. Error bars indicate standard error.

opencc-by-4.0Dec 2013View details →

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Fig. 3 in Relative competence of native and exotic fish hosts for two generalist native trematodes

Fig. 3. Flowchart summarising the circulation and transmission dynamics of trematodes, (a) Telogaster opisthorchis and (b) Stegodexamene anguillae, in native and exotic hosts in Lake Pearson. (Native fish images; McDowall, 2000; exotic fish; Rauque et al., 2003.)

opencc-by-4.0Dec 2013View details →

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Fig. 1 in Relative competence of native and exotic fish hosts for two generalist native trematodes

Fig. 1. Mean worm size, number of eggs and egg volume of the trematodes Telogaster opisthorchis (a, c, e) and Stegodexamene anguillae (b, d, f) naturally infecting exotic salmonids (Lake Pearson) and native longfin eel (Lake Sumner). Error bars indicate standard error, ‡‡‡ Significant differences (P <0.0001).

opencc-by-4.0Dec 2013View details →

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Fig. 1 in Host competence of African rodents Arvicanthis neumanni, A. niloticus and Mastomys natalensis for Leishmania major

Fig. 1. Xenodiagnosis and external manifestation of L. major in rodents. Direct xenodiagnosis with P. duboscqi in plastic tubes covered with fine mesh held on the ear of the anaesthetized A. niloticus (A) and external manifestation of L. major LV109 in ear pinnae (site of inoculation) of A. neumanni by week 10 p.i., (B); A. niloticus by week 30 p.i. (C, D) and M. natalensis by week 19 p.i. (E).

opencc-by-4.0Apr 2019View details →

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Views of the students and prospective teachers of the National and Kapodistrian University of Athens and School of Pedagogical and Technological Education, regarding the necessity of certified pedagogical competence.

views of the students and prospective teachers of the National and Kapodistrian University of Athens and School of Pedagogical and Technological Education, regarding the necessity of certified pedagogical competence.

opencc-by-4.0Jul 2019View details →

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Fig. 3 in Host competence of Algerian Gerbillus amoenus for Leishmania major

Fig. 3. The external manifestation of L. major infection in Gerbillus amoenus. A) non-infected ear, B) 8th-week post-infection, C) 11th-week post-infection, D) 6 months post-infection.

opencc-by-4.0Aug 2023View details →

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Fig. 2 in Host competence of Algerian Gerbillus amoenus for Leishmania major

Fig. 2. Lesion growth in Gerbillus amoenus and Balb/c mice. Data are presented as the means ± standard errors of the means.

opencc-by-4.0Aug 2023View details →

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record