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208 Research products, page 1 of 21

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  • Open Access English
    Authors: 
    Strupler, Néhémie;
    Publisher: Zenodo

    This forms part of the preliminary open data release for the Project Panormos archaeological survey. This "panormos/survey-analysis" repository contains the R code used for preliminary mapping and statistical representation of the survey data. The code is arranged as a multi-part R Markdown document, drawing on the various relevant archaeological and spatial data to create representations of the results. The code is provided separately here for reference, citation and re-use, but in order to produce the visualisations, three other repositories are also required: 'survey-data', 'survey-spatial' (currently closed access) and 'gis-copernicus'. Note that 'survey-spatial' is only available to bona fide researchers on request.

  • Research software . 2022
    Open Access English
    Authors: 
    Sherratt, Tim;
    Publisher: Zenodo

    Current version: v1.0.0 Tools and examples for working with GLAM information in Wikidata. For more information see the Wikidata section of the GLAM Workbench. Notebook topics Create a Gannt chart of Australian government departments – visualises life dates of government departments Create a network graph visualisation of Australian government departments – visualises changes in Australian government departments over time Visualise the connections of a single Australian government agency See the GLAM Workbench for more details.

  • Restricted English
    Authors: 
    Mangiacrapa F.;
    Country: Italy
    Project: EC | ARIADNEplus (823914)

    Il sistema "geoportal-data-entry-app", nasce nell'ambito del progetto europeo "ARIADNEPlus", in cui in collaborazione e per i referenti dell'Istituto centrale per l'Archeologia (ICA) e per il Ministero dei Beni Culturali, si è realizzato un ambiente di prototipazione per il Geoportale Nazionale per l'Archeologia (GNA). In particolare, il sistema permette agli attori che lo utilizzano, il Project management (data entry e gestione del ciclo di vita) di prodotti spazio-temporali basati su Use Case Descriptor (UCD) document che ne specificano il modello del documento, gestione, lifecycle, handler, etc. Pertanto il sistema permette di: (i) accedere e ricercare i prodotti pubblicati nel sistema, (ii) accedere al report di pubblicazione dei prodotti, visionare lo stato di pubblicazione (SUCCESS, WARNING, ERROR), etc., (iii) accedere alla loro visualizzazione su mappa, (iv) gestire il loro contenuto mediante il flusso (Workflow) di pubblicazione, (v) gestire le relazioni (collegamenti temporali e/o qualitativi) tra i prodotti. Il sistema in generale consente il data-entry di qualsivoglia prodotto avente caratteristiche spazio-temporali e non, i cui metadati sono specificati da un indice che specifica uno o più Metadata Profile e la struttura del JSON risultante. Un Metadata Profile è un documento XML-based di specifica di un "prodotto generico" (es. un dataset spazio-temporale) e dei suoi attributi, che indica la lista dei metadati che lo compongono e che possono essere di tipo descrittivo, spaziale, temporale, risorsa (es. file immagine), ecc..

  • English
    Authors: 
    Thrun, Michael C.;
    Publisher: Code Ocean

    Package that will be attached to Projection-based Classification of Chemical Groups for Provenance Analysis of Archaeological Materials. The swarm system called Databionic swarm (DBS) was published in Thrun, M.C., Ultsch A.: "Swarm Intelligence for Self-Organized Clustering" (2020), Artificial Intelligence, . DBS is able to adapt itself to structures of high-dimensional data such as natural clusters characterized by distance and/or density based structures in the data space. The first module is the parameter-free projection method called Pswarm (Pswarm()), which exploits the concepts of self-organization and emergence, game theory, swarm intelligence and symmetry considerations. The second module is the parameter-free high-dimensional data visualization technique, which generates projected points on the topographic map with hypsometric tints defined by the generalized U-matrix (GeneratePswarmVisualization()). The third module is the clustering method itself with non-critical parameters (DBSclustering()). Clustering can be verified by the visualization and vice versa. The term DBS refers to the method as a whole. It enables even a non-professional in the field of data mining to apply its algorithms for visualization and/or clustering to data sets with completely different structures drawn from diverse research fields. The comparison to common projection methods can be found in the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) . For details, please see the vignette in https://cran.r-project.org/web/packages/DatabionicSwarm/vignettes/DatabionicSwarm.html

  • Research software . 2019
    Open Access English
    Authors: 
    Sherratt, Tim;
    Publisher: Zenodo

    Trove lists are user created collections of items. The details of public lists are available through the Trove API. The notebooks in this repository harvest and visualise list metadata.

  • Open Access English
    Authors: 
    Laurence Horton;
    Publisher: Zenodo

    Code for checking the status of URL links in the dataset: Horton, Laurence (2018). UK Higher Education Institution Research Data Management Policies, 2009-2016. [Data Collection]. Colchester, Essex: UK Data Archive. https://doi.org/10.5255/UKDA-SN-851566 {"references": ["Horton, Laurence (2018). UK Higher Education Institution Research Data Management Policies, 2009-2016. [Data Collection]. Colchester, Essex: UK Data Archive. 10.5255/UKDA-SN-851566"]}

  • English
    Authors: 
    Kanakaris, Nikos; Giarelis, Nikolaos; Siachos, Ilias; Karacapilidis, Nikos;
    Publisher: Code Ocean

    This paper employs techniques and algorithms from the fields of natural lan-guage processing, graph representation learning and word embeddings to assistproject managers in the task of personnel selection. To do so, our approachinitially represents multiple textual documents as a single graph. Then, it com-putes word embeddings through representation learning on graphs and performsfeature selection. Finally, it builds a classification model that is able to estimatehow qualified a candidate employee is to work on a given task, taking as inputonly the descriptions of the tasks and a list of word embeddings. Our approachdiffers from the existing ones in that it does not require the calculation of keyperformance indicators or any other form of structured data in order to operateproperly. For our experiments, we retrieved data from the Jira issue trackingsystem of the Apache Software Foundation. The evaluation results show, inmost cases, an increase of 0.43% in the accuracy of the proposed classificationmodels when compared against a widely-adopted baseline method, while theirvalidation loss is significantly decreased by 65.54%

  • Open Access English
    Authors: 
    Harrop, Mitchell;
    Publisher: Zenodo

    Current version: v1.0.1 A collection of examples using the Victorian Heritage Database API. For more information see the Heritage Council of Victoria section of the GLAM Workbench. Notebook topics Introduction to the Victorian Heritage Database API This repository is part of the GLAM Workbench.

  • Research software . 2018
    Open Access English
    Authors: 
    Knitter, Daniel; Hamer, Wolfgang; Günther, Gerrit; Vorspel-Rüter, Camille;
    Publisher: Zenodo

    This package is an (adapted) R implementation of the land use quantification approach from Hughes et al. 2018; The package calculates the required area of land for a given number of people, mainly based on their diet. Further information how to use the packge are found in the vignettes. Various nutritional information are collected as data objects within the package (see additional notes). New in version 1.1: added protein requirments. Reference: Hughes RE, Weiberg E, Bonnier A, Finné M and Kaplan JO (2018) Quantifying Land Use in Past Societies from Cultural Practice and Archaeological Data. Land 7(1): 9: doi:10.3390/land7010009. Empirical Data used in the package The package builds upon empirical data on caloric density as well as plant productivity. Below is the list of references for these data (the list of full references is also supplied in the references.txt and references.bib respectively, that is shipped with the package) Abdel-Aal E-SM, Hucl P and Sosulski FW (1995) Compositional and Nutritional Characteristics of Spring Einkorn and Spelt Wheats. Cereal Chemistry 72(6): 621–624. Aggelopoulou KD, Wulfsohn D, Fountas S, Gemtos TA, Nanos GD and Blackmore S (2009) Spatial variation in yield and quality in a small apple orchard. Precision Agriculture 11(5): 538–556. AIM Statistics Report 2016 ( (n.d.)). . Arnon I (1972) Crop production in dry regions. Volume 2. Systematic treatment of the principal crops. Crop production in dry regions. Systematic treatment of the principal crops 2. Available at: https://www.cabdirect.org/cabdirect/abstract/19720701641. Barker G and Barker DP of A and D of the MI for ARG (1985) Prehistoric Farming in Europe. New Yok: CUP Archive. Barzegar AR, Asoodar MA, Khadish A, Hashemi AM and Herbert SJ (2003) Soil physical characteristics and chickpea yield responses to tillage treatments. Soil and Tillage Research 71(1): 49–57: doi:10.1016/S0167-1987(03)00019-9. Battisti A, Benvegnù I, Colombari F and Haack RA (2014) Invasion by the chestnut gall wasp in Italy causes significant yield loss in Castanea sativa nut production. Agricultural and Forest Entomology 16(1): 75–79: doi:10.1111/afe.12036. Böhm E (1997) Jagdpraxis im Schwarzwaldrevier: Vom Abfährten bis zum Zerwirken. Graz: Stocker, L. Buchner RP (2012) Prune Production Manual. Oakland: University of California: UCANR Publications. Cohen DM, Inada T, Iwamoto T and Scialabba N (1990) FAO species catalogue. Vol. 10. Gadiform fishes of the world. An annotated and illustrated catalogue of cods, hakes, grenadiers and other gadiform fishes known to date. Rome: Food and Agricultural Organization of the United Nations. Dahl G and Hjort A (1976) Having herds: pastoral herd growth and household economy. Stockholm: Dept. of Social Anthropology, University of Stockholm. Datenbank BiolFlor - Helmholtz-Zentrum für Umweltforschung UFZ ( (n.d.)). . Available at: http://www.ufz.de/index.php?de=38567. Ferguson L, Polito V and Kallsen C (2005) The pistachio tree; botany and physiology and factors that affect yield. Pistachio Production Manual, 10. Foxhall L (2007) Olive Cultivation in Ancient Greece: Seeking the Ancient Economy. Oxford. Freyhof J and Kottelat M (2007) Handbook of European freshwater fishes. Berlin: Kottelat, Cornol and Freyhof. Available at: https://portals.iucn.org/library/node/9068. Ganopoulos I, Merkouropoulos G, Pantazis S, Tsipouridis C and Tsaftaris A (2011) Assessing molecular and morpho-agronomical diversity and identification of ISSR markers associated with fruit traits in quince (Cydonia oblonga). Genetics and Molecular Research 10(4): 2729–2746: doi:10.4238/2011.November.4.7. Garnsey P (1992) Yield of the Land. Agriculture in Ancient Greece: Proceedings of the Seventh International Symposium at the Swedish Institute at Athens 42. Glutz von Blotzheim UN (1966) Handbuch der Vögel Mitteleuropas. Wiesbaden: Akademische Verlagsgesellschaft. Halstead P (1996) Pastoralism or Household Herding? Problems of Scale and Specialization in Early Greek Animal Husbandry. World Archaeology 28(1): 20–42. Hampson CR, Azarenko AN and Potter JR (1996) Photosynthetic Rate, Flowering, and Yield Component Alteration in Hazelnut in Response to Different Light Environments. Journal of the American Society for Horticultural Science 121(6): 1103–1111. Hughes RE, Weiberg E, Bonnier A, Finné M and Kaplan JO (2018) Quantifying Land Use in Past Societies from Cultural Practice and Archaeological Data. Land 7(1): 9: doi:10.3390/land7010009. James P and Measham PF (2011) Australian Cherry Production Guide. Lenswood: Government of Southern Australia. Klimenko S (2004) The Cornelian Cherry (Cornus mas L.): Collection, preservation, and utilization of genetic resources. Journal of Fruit and Ornamental Plant Research 12: 94–98. Lüning J and Meurers-Balke J (1980) Experimenteller Getreideanbau im Hambacher Forst, Gemeinde Elsdorf, Kreis Bergheim, Rheinland. Bonner Jahrbücher 180: 305–344. Miarnau X, Alegre S and Vargas F (2010) Productive potential of six almond cultivars under regulated deficit irrigation. XIV GREMPA Meeting on Pistachios and almonds. Options Méditerranéennes, Series A (94): 267–271. Muus BJ and Dahlström P (1968) Süßwasserfische. München: BLV Verlagsgesellschaft. Osten-Sacken E von der (2015) Untersuchungen zur Geflügelwirtschaft im Alten Orient. Fribourg: Academic Press Fribourg. Otte MJ and Chilonda P (2002) Cattle and small ruminant production systems in sub-Saharan Africa : a systematic review. Rome. Poli BM, Focardi S and Tinelli A (1996) Composition and metabolizable energy of feed used by fallow deer (Dama dama) in a coastal Mediterranean ecosystem. Small Ruminant Research 22(2): 103–109: doi:10.1016/S0921-4488(96)00885-1. Pretzsch H (2013) Wood fuels handbook. Pristina: Food and Agriculture Organization of the United Nations. Ramos DE (1998) Walnut Production Manual. Oakland: University of California: UCANR Publications. Referenzwerte für die Nährstoffzufuhr (2017). Bonn: Deutsche Gesellschaft für Ernährung, Österreichische Gesellschaft für Ernährung, Schweizerische Gesellschaft für Ernährung. Revedin A, Aranguren B, Becattini R, Longo L, Marconi E, Lippi MM, et al. (2010) Thirty thousand-year-old evidence of plant food processing. Proceedings of the National Academy of Sciences of the United States of America 107(44): 18815–18819: doi:10.1073/pnas.1006993107. Rinallo C and Modi G (1995) Fruit yield of field-grown pear Pyrus communis (L) exposed to different levels of rain acidity in tuscany. Journal of the Science of Food and Agriculture 68(1): 43–50: doi:10.1002/jsfa.2740680108. Robins CR, Ray GC, Douglass J, Freund R, Society NA and Federation NW (1986) A field guide to Atlantic Coast fishes of North America. Boston: Houghton Mifflin. Robinson J and Harding J (2015) The Oxford Companion to Wine. Oxford: Oxford University Press. Souci SW, Fachmann W and Kraut H (2016) Die Zusammensetzung der Lebensmittel, Nährwert-Tabellen. Stuttgart. Available at: https://www.beck-shop.de/souci-fachmann-kraut-zusammensetzung-lebensmittel-naehrwert-tabellen/productview.aspx?product=16126907. Starr CG (1977) The economic and social growth of early Greece, 800-500 b.c. New York: Oxford University Press. Stubbe C (1979) Rehwild: Biologie - Ökologie - Bewirtschaftung. Stuttgart: Franckh Kosmos Verlag. Svensson L, Grant PJ, Mullarney K and Zetterström D (1999) Der neue Kosmos Vogelführer. Alle Arten Europas, Nordafrikas und Vorderasiens. Stuttgart: Franckh-Kosmos Verlag. USDA Food Composition Databases (2015). . Available at: https://ndb.nal.usda.gov/ndb/. USDA Food Composition Databases (2018). . Available at: https://ndb.nal.usda.gov/ndb/. Wildlebende Gänse und Schwäne in Sachsen (2008). Dresden. Available at: https://publikationen.sachsen.de/bdb/artikel/11438. Wolfe K, Audrey-Luke M, Daniels J, Kane S, Martino K, Heboyan V, et al. (2009) Pomegranate Feasibility Study. Atlanta: University of Georgia.

  • English
    Authors: 
    Amirhosein Bodaghi;
    Publisher: Code Ocean

    This code gets a number of tweets as the input and delivers the semantic graph of relationships between entities of those tweets' text. To this aim first it does a series of text cleanings, and then proceeds with entity extraction and resolutions which come in multiple stages. Finally, the code creates the graph in which nodes represent the entities and the link between them indicates the co-concurrency of those entities in at least one tweet of the input data.

Advanced search in Research products
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
includes
arrow_drop_down
Include:
The following results are related to Digital Humanities and Cultural Heritage. Are you interested to view more results? Visit OpenAIRE - Explore.
208 Research products, page 1 of 21
  • Open Access English
    Authors: 
    Strupler, Néhémie;
    Publisher: Zenodo

    This forms part of the preliminary open data release for the Project Panormos archaeological survey. This "panormos/survey-analysis" repository contains the R code used for preliminary mapping and statistical representation of the survey data. The code is arranged as a multi-part R Markdown document, drawing on the various relevant archaeological and spatial data to create representations of the results. The code is provided separately here for reference, citation and re-use, but in order to produce the visualisations, three other repositories are also required: 'survey-data', 'survey-spatial' (currently closed access) and 'gis-copernicus'. Note that 'survey-spatial' is only available to bona fide researchers on request.

  • Research software . 2022
    Open Access English
    Authors: 
    Sherratt, Tim;
    Publisher: Zenodo

    Current version: v1.0.0 Tools and examples for working with GLAM information in Wikidata. For more information see the Wikidata section of the GLAM Workbench. Notebook topics Create a Gannt chart of Australian government departments – visualises life dates of government departments Create a network graph visualisation of Australian government departments – visualises changes in Australian government departments over time Visualise the connections of a single Australian government agency See the GLAM Workbench for more details.

  • Restricted English
    Authors: 
    Mangiacrapa F.;
    Country: Italy
    Project: EC | ARIADNEplus (823914)

    Il sistema "geoportal-data-entry-app", nasce nell'ambito del progetto europeo "ARIADNEPlus", in cui in collaborazione e per i referenti dell'Istituto centrale per l'Archeologia (ICA) e per il Ministero dei Beni Culturali, si è realizzato un ambiente di prototipazione per il Geoportale Nazionale per l'Archeologia (GNA). In particolare, il sistema permette agli attori che lo utilizzano, il Project management (data entry e gestione del ciclo di vita) di prodotti spazio-temporali basati su Use Case Descriptor (UCD) document che ne specificano il modello del documento, gestione, lifecycle, handler, etc. Pertanto il sistema permette di: (i) accedere e ricercare i prodotti pubblicati nel sistema, (ii) accedere al report di pubblicazione dei prodotti, visionare lo stato di pubblicazione (SUCCESS, WARNING, ERROR), etc., (iii) accedere alla loro visualizzazione su mappa, (iv) gestire il loro contenuto mediante il flusso (Workflow) di pubblicazione, (v) gestire le relazioni (collegamenti temporali e/o qualitativi) tra i prodotti. Il sistema in generale consente il data-entry di qualsivoglia prodotto avente caratteristiche spazio-temporali e non, i cui metadati sono specificati da un indice che specifica uno o più Metadata Profile e la struttura del JSON risultante. Un Metadata Profile è un documento XML-based di specifica di un "prodotto generico" (es. un dataset spazio-temporale) e dei suoi attributi, che indica la lista dei metadati che lo compongono e che possono essere di tipo descrittivo, spaziale, temporale, risorsa (es. file immagine), ecc..

  • English
    Authors: 
    Thrun, Michael C.;
    Publisher: Code Ocean

    Package that will be attached to Projection-based Classification of Chemical Groups for Provenance Analysis of Archaeological Materials. The swarm system called Databionic swarm (DBS) was published in Thrun, M.C., Ultsch A.: "Swarm Intelligence for Self-Organized Clustering" (2020), Artificial Intelligence, . DBS is able to adapt itself to structures of high-dimensional data such as natural clusters characterized by distance and/or density based structures in the data space. The first module is the parameter-free projection method called Pswarm (Pswarm()), which exploits the concepts of self-organization and emergence, game theory, swarm intelligence and symmetry considerations. The second module is the parameter-free high-dimensional data visualization technique, which generates projected points on the topographic map with hypsometric tints defined by the generalized U-matrix (GeneratePswarmVisualization()). The third module is the clustering method itself with non-critical parameters (DBSclustering()). Clustering can be verified by the visualization and vice versa. The term DBS refers to the method as a whole. It enables even a non-professional in the field of data mining to apply its algorithms for visualization and/or clustering to data sets with completely different structures drawn from diverse research fields. The comparison to common projection methods can be found in the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) . For details, please see the vignette in https://cran.r-project.org/web/packages/DatabionicSwarm/vignettes/DatabionicSwarm.html

  • Research software . 2019
    Open Access English
    Authors: 
    Sherratt, Tim;
    Publisher: Zenodo

    Trove lists are user created collections of items. The details of public lists are available through the Trove API. The notebooks in this repository harvest and visualise list metadata.

  • Open Access English
    Authors: 
    Laurence Horton;
    Publisher: Zenodo

    Code for checking the status of URL links in the dataset: Horton, Laurence (2018). UK Higher Education Institution Research Data Management Policies, 2009-2016. [Data Collection]. Colchester, Essex: UK Data Archive. https://doi.org/10.5255/UKDA-SN-851566 {"references": ["Horton, Laurence (2018). UK Higher Education Institution Research Data Management Policies, 2009-2016. [Data Collection]. Colchester, Essex: UK Data Archive. 10.5255/UKDA-SN-851566"]}

  • English
    Authors: 
    Kanakaris, Nikos; Giarelis, Nikolaos; Siachos, Ilias; Karacapilidis, Nikos;
    Publisher: Code Ocean

    This paper employs techniques and algorithms from the fields of natural lan-guage processing, graph representation learning and word embeddings to assistproject managers in the task of personnel selection. To do so, our approachinitially represents multiple textual documents as a single graph. Then, it com-putes word embeddings through representation learning on graphs and performsfeature selection. Finally, it builds a classification model that is able to estimatehow qualified a candidate employee is to work on a given task, taking as inputonly the descriptions of the tasks and a list of word embeddings. Our approachdiffers from the existing ones in that it does not require the calculation of keyperformance indicators or any other form of structured data in order to operateproperly. For our experiments, we retrieved data from the Jira issue trackingsystem of the Apache Software Foundation. The evaluation results show, inmost cases, an increase of 0.43% in the accuracy of the proposed classificationmodels when compared against a widely-adopted baseline method, while theirvalidation loss is significantly decreased by 65.54%

  • Open Access English
    Authors: 
    Harrop, Mitchell;
    Publisher: Zenodo

    Current version: v1.0.1 A collection of examples using the Victorian Heritage Database API. For more information see the Heritage Council of Victoria section of the GLAM Workbench. Notebook topics Introduction to the Victorian Heritage Database API This repository is part of the GLAM Workbench.

  • Research software . 2018
    Open Access English
    Authors: 
    Knitter, Daniel; Hamer, Wolfgang; Günther, Gerrit; Vorspel-Rüter, Camille;
    Publisher: Zenodo

    This package is an (adapted) R implementation of the land use quantification approach from Hughes et al. 2018; The package calculates the required area of land for a given number of people, mainly based on their diet. Further information how to use the packge are found in the vignettes. Various nutritional information are collected as data objects within the package (see additional notes). New in version 1.1: added protein requirments. Reference: Hughes RE, Weiberg E, Bonnier A, Finné M and Kaplan JO (2018) Quantifying Land Use in Past Societies from Cultural Practice and Archaeological Data. Land 7(1): 9: doi:10.3390/land7010009. Empirical Data used in the package The package builds upon empirical data on caloric density as well as plant productivity. Below is the list of references for these data (the list of full references is also supplied in the references.txt and references.bib respectively, that is shipped with the package) Abdel-Aal E-SM, Hucl P and Sosulski FW (1995) Compositional and Nutritional Characteristics of Spring Einkorn and Spelt Wheats. Cereal Chemistry 72(6): 621–624. Aggelopoulou KD, Wulfsohn D, Fountas S, Gemtos TA, Nanos GD and Blackmore S (2009) Spatial variation in yield and quality in a small apple orchard. Precision Agriculture 11(5): 538–556. AIM Statistics Report 2016 ( (n.d.)). . Arnon I (1972) Crop production in dry regions. Volume 2. Systematic treatment of the principal crops. Crop production in dry regions. Systematic treatment of the principal crops 2. Available at: https://www.cabdirect.org/cabdirect/abstract/19720701641. Barker G and Barker DP of A and D of the MI for ARG (1985) Prehistoric Farming in Europe. New Yok: CUP Archive. Barzegar AR, Asoodar MA, Khadish A, Hashemi AM and Herbert SJ (2003) Soil physical characteristics and chickpea yield responses to tillage treatments. Soil and Tillage Research 71(1): 49–57: doi:10.1016/S0167-1987(03)00019-9. Battisti A, Benvegnù I, Colombari F and Haack RA (2014) Invasion by the chestnut gall wasp in Italy causes significant yield loss in Castanea sativa nut production. Agricultural and Forest Entomology 16(1): 75–79: doi:10.1111/afe.12036. Böhm E (1997) Jagdpraxis im Schwarzwaldrevier: Vom Abfährten bis zum Zerwirken. Graz: Stocker, L. Buchner RP (2012) Prune Production Manual. Oakland: University of California: UCANR Publications. Cohen DM, Inada T, Iwamoto T and Scialabba N (1990) FAO species catalogue. Vol. 10. Gadiform fishes of the world. An annotated and illustrated catalogue of cods, hakes, grenadiers and other gadiform fishes known to date. Rome: Food and Agricultural Organization of the United Nations. Dahl G and Hjort A (1976) Having herds: pastoral herd growth and household economy. Stockholm: Dept. of Social Anthropology, University of Stockholm. Datenbank BiolFlor - Helmholtz-Zentrum für Umweltforschung UFZ ( (n.d.)). . Available at: http://www.ufz.de/index.php?de=38567. Ferguson L, Polito V and Kallsen C (2005) The pistachio tree; botany and physiology and factors that affect yield. Pistachio Production Manual, 10. Foxhall L (2007) Olive Cultivation in Ancient Greece: Seeking the Ancient Economy. Oxford. Freyhof J and Kottelat M (2007) Handbook of European freshwater fishes. Berlin: Kottelat, Cornol and Freyhof. Available at: https://portals.iucn.org/library/node/9068. Ganopoulos I, Merkouropoulos G, Pantazis S, Tsipouridis C and Tsaftaris A (2011) Assessing molecular and morpho-agronomical diversity and identification of ISSR markers associated with fruit traits in quince (Cydonia oblonga). Genetics and Molecular Research 10(4): 2729–2746: doi:10.4238/2011.November.4.7. Garnsey P (1992) Yield of the Land. Agriculture in Ancient Greece: Proceedings of the Seventh International Symposium at the Swedish Institute at Athens 42. Glutz von Blotzheim UN (1966) Handbuch der Vögel Mitteleuropas. Wiesbaden: Akademische Verlagsgesellschaft. Halstead P (1996) Pastoralism or Household Herding? Problems of Scale and Specialization in Early Greek Animal Husbandry. World Archaeology 28(1): 20–42. Hampson CR, Azarenko AN and Potter JR (1996) Photosynthetic Rate, Flowering, and Yield Component Alteration in Hazelnut in Response to Different Light Environments. Journal of the American Society for Horticultural Science 121(6): 1103–1111. Hughes RE, Weiberg E, Bonnier A, Finné M and Kaplan JO (2018) Quantifying Land Use in Past Societies from Cultural Practice and Archaeological Data. Land 7(1): 9: doi:10.3390/land7010009. James P and Measham PF (2011) Australian Cherry Production Guide. Lenswood: Government of Southern Australia. Klimenko S (2004) The Cornelian Cherry (Cornus mas L.): Collection, preservation, and utilization of genetic resources. Journal of Fruit and Ornamental Plant Research 12: 94–98. Lüning J and Meurers-Balke J (1980) Experimenteller Getreideanbau im Hambacher Forst, Gemeinde Elsdorf, Kreis Bergheim, Rheinland. Bonner Jahrbücher 180: 305–344. Miarnau X, Alegre S and Vargas F (2010) Productive potential of six almond cultivars under regulated deficit irrigation. XIV GREMPA Meeting on Pistachios and almonds. Options Méditerranéennes, Series A (94): 267–271. Muus BJ and Dahlström P (1968) Süßwasserfische. München: BLV Verlagsgesellschaft. Osten-Sacken E von der (2015) Untersuchungen zur Geflügelwirtschaft im Alten Orient. Fribourg: Academic Press Fribourg. Otte MJ and Chilonda P (2002) Cattle and small ruminant production systems in sub-Saharan Africa : a systematic review. Rome. Poli BM, Focardi S and Tinelli A (1996) Composition and metabolizable energy of feed used by fallow deer (Dama dama) in a coastal Mediterranean ecosystem. Small Ruminant Research 22(2): 103–109: doi:10.1016/S0921-4488(96)00885-1. Pretzsch H (2013) Wood fuels handbook. Pristina: Food and Agriculture Organization of the United Nations. Ramos DE (1998) Walnut Production Manual. Oakland: University of California: UCANR Publications. Referenzwerte für die Nährstoffzufuhr (2017). Bonn: Deutsche Gesellschaft für Ernährung, Österreichische Gesellschaft für Ernährung, Schweizerische Gesellschaft für Ernährung. Revedin A, Aranguren B, Becattini R, Longo L, Marconi E, Lippi MM, et al. (2010) Thirty thousand-year-old evidence of plant food processing. Proceedings of the National Academy of Sciences of the United States of America 107(44): 18815–18819: doi:10.1073/pnas.1006993107. 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  • English
    Authors: 
    Amirhosein Bodaghi;
    Publisher: Code Ocean

    This code gets a number of tweets as the input and delivers the semantic graph of relationships between entities of those tweets' text. To this aim first it does a series of text cleanings, and then proceeds with entity extraction and resolutions which come in multiple stages. Finally, the code creates the graph in which nodes represent the entities and the link between them indicates the co-concurrency of those entities in at least one tweet of the input data.