The NOAFAULTs database of active faults of Greece was first published in 2013 at BGSG (versions 1.0 & 1.1; http://dx.doi.org/10.12681/bgsg.11079). Version 2.1 (see map below) was published in 2018 http://doi.org/10.5281/zenodo.3483136); Version 3.0 was published in 2020 http://doi.org/10.5281/zenodo.4304613; Version 4.0 was published in 2022 https://zenodo.org/record/6326260 ; Version 5.0 was published in 2023 https://doi.org/10.5281/zenodo.8075517 ; Version 6.0 was published in 2024 https://zenodo.org/records/13168947 . NOAFAULTs was created towards compiling a digital database of fault traces, geometry and additional attributes (kinematics, slip rate, associated seismicity etc.) primarily to support seismicity monitoring at the National Observatory of Athens (NOA). It has been constructed from published fault maps in peer-reviewed journals since 1972 while the number of the scientific papers that have contributed with fault data in version 7.0 is 158. The standard commercial software ARCGIS has been used to design and populate the database. The fault layer was produced at NOA by on-screen digitization of fault traces at the original map-scale (as drawn by the reference paper it was taken from) and is available through our web portal application https://arcg.is/04Haer supported by ESRI.

In this version, in order to streamline the process, avoid inconsistencies during data input, and ensure a homogeneous database, we decided to automatically calculate certain fields from the attribute table. Specifically, the Strike and Dip-Direction fields were derived programmatically. First, the digitization of the faults was carried out to align with the dip-direction of each. With this method of digitization, the user also could apply a symbol to each fault that correctly corresponds to its dip-direction, enhancing the accuracy and interpretability of the fault representation. Then, by calculating the line bearing of the fault and applying a ±180° function to the result, the Strike was determined. Subsequently, using the calculated strike and appropriate functions, the Dip-Direction of each fault was generated. If the dip angle was not provided by the scientific source, we assigned standard values: 60° for Normal faults, 30° for Reverse faults, and 90° for Strike-Slip faults. Consequently, the Rake field was assigned values of -90° for Normal, 90° for Reverse, and 0° or 180° for Strike-Slip faults, depending on relative sense of motion.

Four new thematic layers were added to V7.0: the Sampling Sites layer, which includes locations from paleoseismological trenches and ³⁶CL sampling sites; the NOA Surface Rupture Database layer, which contains documented surface ruptures from field mapping ; and the Cyprus Faults layer, provided by the Cyprus Geological Survey Department (GSD[1]) , incorporated after initial evaluation and selection of specific features. Furthermore, the Focal Mechanisms layer from the NOA Gisola Catalogue (2012–2025) was updated to include data up to 3 June 2025, while the Strong Earthquakes in Greece since 1964 layer was updated with events up to 2 June 2025. In addition, one more station was added to the RING GNSS Network (INGV) layer, enhancing the coverage and detail of the database Moreover, the Rupture Plane of the 2020 Samos Earthquake (M7.0) was added.

Since 2022 NOAFAULTs has contributed to the EFSM20 database (https://www.seismofaults.eu/efsm20).

Analysis of ‘List of Greek Gods and Goddesses’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/katrinaalaimo/list-of-greek-gods-and-goddesses on 14 February 2022.

--- Dataset description provided by original source is as follows ---

General info

Gods, titans, nymphs, and other divine figures were extracted from Wikipedia's List of Greek mythological figures in December 2020. Most sections contained their own unique formatting style. Basic features were created and entry descriptions, many of which were quite lengthy, were condensed.

A large handful of entries also needed to be corrected since they contained uncomfortably incomplete information and duplicates were removed. It was often obvious which duplicate entry to remove (e.g. 'Nyx: Νύξ: god: primordial: goddess of night' was kept and 'Nyx: Νύξ: god: chthonic: primeval goddess of night' was removed ). However, knowledge of the subject area was sometimes needed to make the correct decision (e.g. 'Thanatos: Θάνατος: god: primordial: god of death' was kept and 'Thanatos: Θάνατος: god: chthonic: god of death' was removed.)

This list and the Wikipedia list are not exhaustive. For example, it does not contain all entries for Oceanids and Potamoi, both which have their own long lists on separate pages. It also does not include heros, kings, and other mortals. In total, the resulting list contains a total of 445 divine figures.

Each entry was separated into the following:

• name-english: name in English; if multiple, the most well-known was chosen

• name-greek: name in Greek corresponding to the English name

• main-type: entry type: god, titan, or personification

• sub-type: type within main-type; often the type of god: e.g. olympian, primordial, chthonic, sea, sky, etc.

• description: brief lower-cased description of the entry

Technologies

Python 3.7.6 (PyCharm and Jupyter Notebook); the following modules were heavily utilised: BeautifulSoup, re, pandas.

Please see my GitHub for the code: https://github.com/katrinaalaimo/greek-gods

Inspiration

My academic studies have always had a focus on religion in antiquity (albeit often Roman). This project no doubt was influenced by my profound interest in the subject.

--- Original source retains full ownership of the source dataset ---

The data are derived from interpretation of seismic reflection profiles within the offshore Corinth Rift, Greece (the Gulf of Corinth) integrated with IODP scientific ocean drilling borehole data from IODP Expedition 381 (McNeill et al., 2019a, 2019b). The data include rift fault coordinate (location, geometry) information and slip rate and extension rate information for the major faults. Seismic reflection data were published in Taylor et al. (2011) and in Nixon et al. (2016). Preliminary fault interpretations and rate data, prior to IODP drilling, were published in Nixon et al. (2016). Details of datasets: The data can be viewed in GIS software (ArcGIS, QGIS) or the Excel and .dbf files can be used for viewing of rate data and import of fault coordinates into other software. The 4 folders are for different time periods with shape files for the N-Dipping and S-Dipping Faults in the offshore Corinth Rift and respective slip and extension (horizontal) rates. The shapefiles are digitised fault traces for the basement offsetting faults, picked from the Multichannel Seismic Data collected by the R/V Maurice Ewing. Fault traces are segmented and each segment has an average throw (vertical) rate (Tavg) in mm/yr. The rates for the segments are averages based on measurements at the ends of each segment. The major fault trace segments also have slip-rates (slip_rate) and extension-rates (ext_rate or extension_) in mm/yr. All rates as well as the names for major faults can be located in the attribute table of the shape files along with X- and Y-coordinates. The coordinate system is WGS84 UTM Zone 34N. The shape files can be loaded into a GIS (ArcGIS, QGIS etc.) allowing mapping and visualization of the fault traces and their activity rates. In addition, the attribute tables are .dbf files found within each folder. These have also been provided as .xlsx (Excel) files which include the fault coordinate information, and slip rates and extension rates along the major faults. References McNeill, L.C., Shillington, D.J., Carter, G.D.O., and the Expedition 381 Participants, 2019a. Corinth Active Rift Development. Proceedings of the International Ocean Discovery Program, 381: College Station, TX (International Ocean Discovery Program). McNeill, L.C., Shillington, D.J., et al., 2019b, High-resolution record reveals climate-driven environmental and sedimentary changes in an active rift, Scientific Reports, 9, 3116. Nixon, C.W., McNeill, L.C., Bull, J.M., Bell, R.E., Gawthorpe, R.L., Henstock, T.J., Christodoulou, D., Ford, M., Taylor, B., Sakellariou, S. et al., 2016. Rapid spatiotemporal variations in rift structure during development of the Corinth Rift, central Greece. Tectonics, 35, 1225–1248. Taylor, B., J. R. Weiss, A. M. Goodliffe, M. Sachpazi, M. Laigle, and A. Hirn (2011), The structures, stratigraphy and evolution of the Gulf of Corinth Rift, Greece, Geophys. J. Int., 185(3), 1189–1219.

This statistic shows the number of The Greek Gods yogurt used within a month in the United States in 2020. The data has been calculated by Statista based on the U.S. Census data and Simmons National Consumer Survey (NHCS). According to this statistic, **** million Americans used * servings or more of The Greek Gods yogurt.

An Open Context "media" dataset item. Open Context publishes structured data as granular, URL identified Web resources. This "Vector geospatial (GIS) media" record is part of the "The Eastern Korinthia Archaeological Survey" data publication.

Spatial coverage index compiled by East View Geospatial of set "Greece 1:50,000 Scale Geological Maps". Source data from IGME (publisher). Type: Geoscientific - Geology. Scale: 1:50,000. Region: Europe.

An attempt to collect, format, analyse and disseminate surveyed marine biological data deriving from the Eastern Mediterranean and Black Sea region is currently under development at the Hellenic Center for Marine Research (HCMR, Greece). The effort has been supported by the MedOBIS project (Mediterranean Ocean Biogeographic Information System) and has been carried out in cooperation with the Aristotelian University of Thessaloniki (Greece), the National Institute of Oceanography (Israel) and the Institute of Biology of the Southern Seas (Ukraine).

    The aim is to develop a taxon-based biogeography database and online data server with a link to survey and provide satellite environmental data. Currently, the primary features of the MedOBIS application are its offline GIS data formatting capabilities and its online Java and JavaScript enabling data server with taxon-based search, mapping and data downloading capabilities. In its completion, the MedOBIS online marine biological data system (http://www.iobis.org/OBISWEB/ObisDynPage1.jsp?content=meta/42.html) will be a single source of biological and environmental data (raw and analysed) as well as an online GIS tool for access of historical and current data by marine researchers. It will function as the Eastern Mediterranean and Black Sea node of EurOBIS (the European node of the International OBIS initiative, part of the Census of Marine Life).

    INTRODUCTION

    The international and interdisciplinary nature of the biological degradation issue as well as the technological advances of the Internet capabilities allowed the development of a considerable number of interrelated online databases. The free dissemination of valuable historical and current biological, environmental and genetic information has contributed to the establishment of an interdisciplinary platform targeted towards information integration at regional and also at global scales and to the development of information-based management schemes about our common interest.

    The spatial component of these data has led to the integration of the information by means of the Geographic Information System (GIS) technology. The latter is widely used as the natural framework for spatial data handling (Wright & Bartlett 1999, Valavanis 2002). GIS serves as the basic technological infrastructure for several online marine biodiversity databases available on the Internet today. Developments like OBIS (Ocean Biogeographic Information System, "http://www.iobis.org/"), OBIS-SEAMAP (Spatial Ecological Analysis of Megavertebrate Populations, "http://seamap.env.duke.edu/") and FIGIS (FAO Fisheries Global Information System, http://www.fao.org/fishery/figis) facilitate the study of anthropogenic impacts on threatened species, enhance our ability to test biogeographic and biodiversity models, support modelling efforts to predict distribution changes in response to environmental change and develop a strong potential for the public outreach component. In addition, such online database systems provide a broader view of marine biodiversity problems and allow the development of management practices that are based on synthetic analysis of interdisciplinary data (Schalk 1998, Decker & O'Dor 2002, Tsontos & Kiefer 2002).

    Towards this end, a development of a new online marine biological information system is presented here in its initial phase. MedOBIS (Mediterranean Ocean Biogeographic Information System) intends to assemble, formulate and disseminate marine biological data for the Eastern Mediterranean and Black Sea regions focusing on the assurance and longevity of historical surveyed data, the assembly of current and new information and the dissemination of raw and integrated biological and environmental data and future products through the Internet.

    MedOBIS DESCRIPTION

    MedOBIS current development consists of four main phases (Fig. 1). The data assembly phase is based on the free contribution of biological data from various national and international scientific surveys in the region. The data formatting phase is based on a GIS (ESRI, 1994), under which the geographic location of data stations is used to convert station data and their attributes to GIS shapefiles. The data analysis phase is based on data integration through GIS and spatial analyses (e.g. species distribution maps, species-environment relations, etc). Finally, the dissemination phase is based on ALOV Map, a free portable Java application for publication of vector and raster maps to the Internet and interactive viewing on web browsers. It supports navigation and search capabilities and allows working with multiple layers, thematic maps, hyperlinked features and attributed data.

    During the on-going data assembly phase, a total number of 776 stations with surveyed benthic biological data was employed. These data include mainly benthic species abundance (for nearly 3000 benthic organisms), benthic substrate types and several environmental parameters. Currently, 100 stations have been assembled for the Ionian Sea, 570 stations for the Aegean Sea and 106 stations for the Black Sea. The temporal resolution of these data extends for the period 1937-2000 while most data cover the period 1986-1996. Additionally, monthly satellite images of sea surface temperature (SST) and chlorophyll (Chl-a) were assembled for the period 1998-2003. Satellite data were obtained from the Advanced Very High Resolution Radiometer (AVHRR SST) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS Chl-a). 

    During the data formatting phase, all assembled surveyed stations were converted to a GIS shapefile (Fig. 2). This GIS information layer includes the geographic coordinates of the stations as well as stations' identification number. Station data attributes were organised in an MS Access Database while satellite data were embedded in a GIS database as GIS regular grids. The MedOBIS data analysis phase is still at the initial stage. Several off line analytical published efforts (e.g. Arvanitidis et al. 2002, Valavanis et al. 2004a,b,c) will be included in the MedOBIS development, which mainly focus on species distribution maps, mapping of productive oceanic processes and species-environment interactions. 

    The MedOBIS dissemination phase ("http://www.medobis.org/") is based on ALOV Map ("http://www.alov.org/"), a joint project of ALOV Software and the Archaeological Computing Laboratory, University of Sydney, Australia. ALOV Map is a Java-based application for publication of GIS data on the Internet and interactive viewing on web browsers. ALOV Map is designed to display geographical information stored in shapefiles or in any SQL database or even in an XML (Extensible Markup Language) document serving as a database. MedOBIS uses ALOV Map's full capabilities and runs in a client-server mode (Fig. 3). ALOV Map is connected to an MS Access database via a servlet container. This architecture was needed to connect the biological data with the spatial data and facilitate search options, such as, which species are found at which stations. Additionally, a JavaScript code is invoked, which searches the data, pops up a window with the results and then shows the relevant stations on the map.

    To provide a taxon-based search capability to the MedOBIS development, the sampling data as well as the relevant spatial data are stored in the database, so taxonomic data can be linked with the geographical data by SQL (Structured Query Language) queries. To reference each species to its location on the map, the database queries are stored and added to the applet as individual layers. A search function written in JavaScript searches the attribute data of that layer, displays the results in a separate window and marks the matching stations on the map (Fig. 4). Finally, selecting several stations by drawing a zooming rectangle on the map provides a list with predefined themes from which the user may select more information (Fig. 5). 

    CURRENT LIMITATIONS AND FUTURE PLANS

    A disadvantage of embedding information from the database as a layer is the relatively long download time due to the current MedOBIS-ALOV Map client-server architecture. An appropriate solution would be a direct search on the server side, which will allow partial data downloading to the client side. This work will be embedded in the MedOBIS application in the future (client-side architecture), when the size of assembled data becomes relatively 'heavy' for the current client-server architecture. This is an on-going process, since the MedOBIS initiative has been endorsed by the "Excellence of the Institute of Marine Biology of Crete (IMBC) in Marine Biodiversity", a Hellenic National Project that has been evaluated and approved by European experts. As more data will be assembled in time-series databases, an additional future work will include the development of MedOBIS data analysis phase, which is planned to include GIS modelling/mapping of species-environment interactions.

    Size reference: 2953 species; 776 stations

    [Source: The information provided in the summary was extracted from the MarBEF Data System at "http://www.marbef.org/data/eurobisproviders.php"]

The aim of the project was to map the Jewish presence in the Byzantine empire using GIS (Geographical Information Systems). All references (published and unpublished) to Jewish communities in the Byzantine Empire were gathered and collated. The data were incorporated in a GIS which will be made freely available to the general public using web maps at www.byzantinejewry.net.

Slides from lightning-round presentation on February 5, 2018, during NYCDH Week.

The NOAFAULTs database of active faults was published in 2013 (versions 1.0 & 1.1). In this datase we present the upgrades comprising the newer version of the database (version 2.1). NOAFAULTs was created towards compiling a digital database of fault geometry and additional attributes (character of faulting, past seismicity etc) primarily to support seismicity monitoring at the National Observatory of Athens (NOA). It has been constructed from published fault maps in peer-reviewed journals since 1972 while the number of the scientific papers that were included is 110. The standard commercial software ARC GIS has been used to design and populate the database. In the new version, details on fault geometry, such as the strike, the dip-angle and the dip direction, and kinematics for each individual fault are included. For well-studied faults, information about the slip rate or the creep or the co-seismic slip is reported. The fault layer was produced by on-screen digitization and is available to the scientific community in ESRI shapefile (SHP), KML/KMZ and TXT formats in WGS84 projection. In this version of the database, we continue to focus on the active faults of the upper (Aegean + Eurasian) plate and the back-arc region of the Hellenic Arc, in general. A number of 2437 faults are now included.

In the course of the extensive survey of Sikyonia (1996-2002) by Yannis Lolos, more than 250 archaeological sites were recorded and mapped, including settlements, forts and watch/signal towers, roads, sanctuaries, quarries, aqueducts and cisterns, terracing walls, and other types of remains.

Out of the 250 archaeological sites that we have mapped and examined in Sikyonia, we identified 148 as representing areas of habitation, with the earliest going back to the Neolithic period and the latest to the 19th century. We observed a certain concentration of prehistoric sites in proximity to the coastal plain (10 out of the 18 sites of this period), where also lies the most important prehistoric settlement site of Sikyonia that we have recorded, namely Litharakia of Krines, with a ceramic surface scatter of ca. 3 ha and an occupation from the Neolithic to the Geometric period. Habitation in Sikyonia followed a rising course from the 6th millennium to the Late Helladic period, and from the Geometric to the Classical period, where it reached its peak.

The Classical period saw the appearance of the largest settlements outside the city (in 12 of those we observed a surface material scatter of over 2 ha), but also a multitude of smaller settlements (scattered over an area between 0.1 and 0.8 ha) which probably represent isolated farmsteads. For the satisfaction of the vital needs of the population, people have now started cultivating even marginal areas, semi-mountainous and usually lying on a slope, and attempted to improve their fertility by constructing retaining walls and other infrastructure works. In later Hellenistic, and less so in Roman times, we witness a shrinkage of settlement sites in the chora of Sikyonia. Recovery will come in Late Roman times, a phenomenon witnessed also in other areas of the Greek world. During this period we observed a tendency for medium and large sites with a corresponding reduction in the number of smaller sites, which suggests a growing preference for communal living. In addition, churches and monasteries now appear in the countryside, a tendency continuing during the Byzantine and post-Byzantine period, with the best example being that of the monastery of Lechova on mount Vesiza.

The reduction of the rural settlement sites in Hellenistic and Roman times may be due to a general demographic crisis or (and) to the concentration of the population in the refounded city – the plateau of Vasiliko. The location and mapping of the visible segments of the ancient walls of Sikyon showed that the entire plateau, ca. 230 ha of surface, was intramuros.

Data

The data in this collection is spatial data collected and created from the project. It is all in GML format which can be used in most GIS applications.

Subject: This is a history lesson. Abstract: This lesson is part of a series within the ‘Ancient Greece’ topic in science. Students will learn about the beliefs of the Ancient Greeks. Lesson Plan Method: The lesson employs face-to-face learning. Age of Students: 10 years old Preparation Time: 60 minutes Teaching Time: 80 minutes Learning Objectives: By completing this learning plan, students will achieve learning outcomes and develop skills such as: Understanding the religious beliefs of the Ancient Greek people. Learning about some of the gods they worshipped. Traditional Scenario 2 - Greek gods.docx Metaverse Scenario 2 - Greek gods - - with Metaverse Activities.docxv

Συντεταγμένες διεύθυνσης

DESCRIPTION - DATA SOURCES Cartographical Data: Contours, Altitude points - Topographic maps (H.M.G.S.) Isobaths, Depth points - Topographic maps (H.M.G.S.), Hydrographic maps, Field measurements Road Network (primary, secondary) - Topographic maps (H.M.G.S.), Local authorities Drainage system, Drainage basins - Topographic maps (H.M.G.S.)Geological formations - Geological maps (I.G.M.E.) Tectonic structure - Geological maps (I.G.M.E.)Lithology - Geological formations Land Use - Corine maps, Field work, Satellite / Aerial photo interpretation Geomorphological Data (planation surfaces, karstic formations, buttes, tobolos, valleys, gorges, knick points, etc) - Field work (GPS), Satelite / Aerial photo interpretation Measurements: Coastal slopes - Field work (GPS)Bathymetry - Field work (sonar/GPS) Coastal material - Field work (GPS), Aerial photo interpretation Archaeological sites (GPS) - Field work (GPS)Gridded Data: Relief (DEM) - GIS contour vector layer Slope - GIS contour vector layer Aspect - GIS contour vector layer. The amount of data, depends on the region. The quality of the data varies. Generally we try to keep accuracy over 90%.

In the Odyssey's Apologoi, Odysseus’ understanding of the gods changes both in a metaphysical dimension as the gods reveal themselves to him, and in an ethical dimension as his own behavior changes.

Lithuania Imports from Greece of Women's or girls' slips, not knitted or crocheted was US$5.99 Thousand during 2023, according to the United Nations COMTRADE database on international trade. Lithuania Imports from Greece of Women's or girls' slips, not knitted or crocheted - data, historical chart and statistics - was last updated on July of 2025.

This dataset is about books. It has 4 rows and is filtered where the book subjects is God (Greek religion). It features 9 columns including author, publication date, language, and book publisher.

An Open Context "media" dataset item. Open Context publishes structured data as granular, URL identified Web resources. This "Vector geospatial (GIS) media" record is part of the "The Eastern Korinthia Archaeological Survey" data publication.

this dataset inscludes shapefiles interpreted from photomosaics over the milos shallow water hydrothermal system, and instrument locaitons, from fieldwork in july and september 2019. the shapefiles are organized by study areas (agia kyria, paleochori, and spathi bays). details are provided in the associated paper (puzenat et al., 2021) in addition to information in the readme file associated.a) shapefiles of seafloor textures interpreted from drone imagery. b) shapefiles of seafloor texttures interpreted from auv imagery. c) shapefiles of instruments deployed in the study area in september 2019.

Greece Exports of women's or girls' overcoats, carcoats, not knitted or crocheted to Russia was US$3.01 Thousand during 2022, according to the United Nations COMTRADE database on international trade. Greece Exports of women's or girls' overcoats, carcoats, not knitted or crocheted to Russia - data, historical chart and statistics - was last updated on July of 2025.