Cross-collection Linking of Botanical Imagery in Ghent Altarpiece to Learn More about Van Eyck’s Masterpiece and to Explore a Region’s Plant Richness and Diversity over Time

2021 ◽  
Vol 14 (3) ◽  
pp. 1-14
Author(s):  
Krishna Kumar Thirukokaranam Chandrasekar ◽  
Emile Deman ◽  
Steven Verstockt
Keyword(s):  
Cultural Heritage ◽  
Mobile Device ◽  
General Public ◽  
Observation Data ◽  
Global Biodiversity Information Facility ◽  
Plant Richness ◽  
Plant Recognition ◽  
Global Biodiversity ◽  
Biodiversity Information ◽  
Over Time

As people on average only spent 20 seconds(s) observing an artwork, they mostly miss a lot of informative details that are contained within it. As an example, the 75 different plants that can be found in the Ghent Altarpiece is something not a lot of people are aware of. Within this article, we present a methodology, based on cross-collection linking, to create awareness about the botanical imagery in Van Eyck’s masterpiece and to inform people about their region’s plant richness and diversity over time. As such, this article is a nice example of how the interdisciplinary fields of cultural heritage and botany can go hand in hand to facilitate its dissemination to the general public. The plants in the painting can be queried by their name or by a picture taken with a mobile device—a plant recognition app is used to evaluate the pictures taken from the plants. A study has also been performed to evaluate these apps and to select the most appropriate one for the collection of plants in the Ghent Alterpiece. Currently, we link the detected plants to herbaria, observation data, Global Biodiversity Information Facility plantinfo, and recent wikimedia commons pictures, but other links can also be easily integrated with the platform. Finally, we also studied nowadays plant observations (volunteered geographic information) in more detail and reveal which region currently has most of Van Eyck’s plants/flowers.

scholarly journals The InBIO Barcoding Initiative Database: DNA barcodes of Portuguese Diptera 01

2020 ◽  
Vol 8 ◽  
Author(s):  
Sonia Ferreira ◽  
Rui Andrade ◽  
Ana Gonçalves ◽  
Pedro Sousa ◽  
Joana Paupério ◽  
...  
Keyword(s):  
Species Level ◽  
Distribution Data ◽  
Dna Barcodes ◽  
Online Database ◽  
Global Biodiversity Information Facility ◽  
Life Data ◽  
Tagus River ◽  
Global Biodiversity ◽  
Biodiversity Information ◽  
Dipteran Species

The InBIO Barcoding Initiative (IBI) Diptera 01 dataset contains records of 203 specimens of Diptera. All specimens have been morphologically identified to species level, and belong to 154 species in total. The species represented in this dataset correspond to about 10% of continental Portugal dipteran species diversity. All specimens were collected north of the Tagus river in Portugal. Sampling took place from 2014 to 2018, and specimens are deposited in the IBI collection at CIBIO, Research Center in Biodiversity and Genetic Resources. This dataset contributes to the knowledge on the DNA barcodes and distribution of 154 species of Diptera from Portugal and is the first of the planned IBI database public releases, which will make available genetic and distribution data for a series of taxa. All specimens have their DNA barcodes made publicly available in the Barcode of Life Data System (BOLD) online database and the distribution dataset can be freely accessed through the Global Biodiversity Information Facility (GBIF).

scholarly journals Using Global Biodiversity Information Facility Occurrence Data for Automated Invasive Alien Species Risk Mapping 

2020 ◽  
Vol 4 ◽  
Author(s):  
Amy Davis ◽  
Tim Adriaens ◽  
Rozemien De Troch ◽  
Peter Desmet ◽  
Quentin Groom ◽  
...  
Keyword(s):  
Alien Species ◽  
Vascular Plants ◽  
Invasive Alien Species ◽  
Risk Assessments ◽  
Sampling Effort ◽  
Global Biodiversity Information Facility ◽  
Global Biodiversity ◽  
Risk Maps ◽  
Species Occurrences ◽  
Biodiversity Information

To support invasive alien species risk assessments, the Tracking Invasive Alien Species (TrIAS) project has developed an automated, open, workflow incorporating state-of-the-art species distribution modelling practices to create risk maps using the open source language R. It is based on Global Biodiversity Information Facility (GBIF) data and openly published environmental data layers characterizing climate and land cover. Our workflow requires only a species name and generates an ensemble of machine-learning algorithms (Random Forest, Boosted Regression Trees, K-Nearest Neighbors and AdaBoost) stacked together as a meta-model to produce the final risk map at 1 km2 resolution (Fig. 1). Risk maps are generated automatically for standard Intergovernmental Panel on Climate Change (IPCC) greenhouse gas emission scenarios and are accompanied by maps illustrating the confidence of each individual prediction across space, thus enabling the intuitive visualization and understanding of how the confidence of the model varies across space and scenario (Fig. 2). The effects of sampling bias are accounted for by providing options to: use the sampling effort of the higher taxon the modelled species belongs to (e.g., vascular plants), and to thin species occurrences. use the sampling effort of the higher taxon the modelled species belongs to (e.g., vascular plants), and to thin species occurrences. The risk maps generated by our workflow are defensible and repeatable and provide forecasts of alien species distributions under further climate change scenarios. They can be used to support risk assessments and guide surveillance efforts on alien species in Europe. The detailied modeling framework and code are available on GitHub: https://github.com/trias-project.

Development and Deployment of an Ethnobotanical and Phytochemical Knowledge Database of Malaysia

2013 ◽  
Vol 64 (2) ◽  
Author(s):  
Shakina Mohd Talkah ◽  
Iylia Zulkiflee ◽  
Mohd Shahir Shamsir
Keyword(s):  
Scientific Literature ◽  
Pharmaceutical Compounds ◽  
South East Asia ◽  
Online Database ◽  
Global Biodiversity Information Facility ◽  
Knowledge Database ◽  
Global Biodiversity ◽  
Digital Knowledge ◽  
Biodiversity Information ◽  
Scientific Name

Currently, all the information regarding ethnobotanical, phytochemical and pharmaceutical information of South East Asia are scattered over many different publications, depositories and databases using various digital and analogue formats. Although there are taxonomic databases of medicinal plants, they are not linked to phytochemical and pharmaceutical information which are often resides in scientific literature. We present Phyknome; an ethnobotanical and phytochemical database with more than 22,000 species of ethnoflora of Asia. The creation of this database will enable a biotechnology researcher to seek and identify ethnobotanical information based on a species’ scientific name, description and phytochemical information. It is constructed using a digitization pipeline that allow high throughput digitization of archival data, an automated dataminer to mine for pharmaceutical compounds information and an online database to integrated these information. The main functions include an automated taxonomy, bibliography and API interface with primary databases such as Global Biodiversity Information Facility (GBIF). We believe that Phyknome will contribute to the digital knowledge ecosystem to elevate access and provide tools for ethnobotanical research and contributes to the management, assessment and stewardship of biodiversity. The database is available at http://mapping.fbb.utm.my/phyknome/.

scholarly journals Repatriation of knowledge about insects and types through the DORSA virtual museum (Digital Orthoptera Specimen Access).

2005 ◽  
Vol 55 (2) ◽  
pp. 477-484
Author(s):  
Karl Heinz Lampe ◽  
Klaus Riede ◽  
Sigfrid Ingrisch
Keyword(s):  
Virtual Museum ◽  
Global Biodiversity Information Facility ◽  
Access Service ◽  
Global Biodiversity ◽  
Type Information ◽  
Biodiversity Information

DORSA (Digital Orthoptera Specimen Access) ist ein virtuelles Museum, das Informationen über Typus-Exemplare von Orthopteren und andere Belege, welche über die wichtigsten deutschen Museums-Sammlungen verstreut sind, in einer einzigen Datenbank zusammenführt. Etwa 16.000 Individuen-Einträge aus über 4.000 Arten sind über das Internet in der SYSTAX-Datenbank (www.biologie.uni-ulm.de/systax) suchbar. SYSTAX stellt die Daten auch über die GBIF (Global Biodiversity Information Facility)- und BIOCASE (Biological Collection Access Service for Europe)- Portale bereit. Etwa 8.000 Typus-Individuen (davon 2.300 primäre Typen) sind mit über 30.000 Fotos dokumentiert. Die Datenbank enthält ferner 12.000 Tonaufnahmen. Fundortdaten und Verbreitungskarten der gespeicherten Individuen sind ebenfalls abrufbar. Die DORSA-Individuendaten sind reziprok mit dem Orthoptera Species File (OSF) verbunden; dieses bildet zugleich das taxonomische Rückrat für DORSA. Alle DORSA Informationen sind frei über das Internet verfügbar. Auf diese Weise wird das Wissen über die Typus-Individuen, die seit der Kolonialzeit gesammelt worden waren, in die Herkunftsländer repatriiert.StichwörterOrthoptera, DORSA, SYSTAX, OSF, specimen database, type information, virtual museum, repatriation of knowledge.

Sign in / Sign up

Export Citation Format

Share Document