Dag Endresen

• Bari, Abdallah; Khazaei, Hamid; Stoddard, Frederick L.; Street, Kenneth; Sillanpää, Mikko J.; Chaubey, Yogen P.; Dayanandan, Selvadurai; Endresen, Dag Terje Filip; De Pauw, Eddy & Damania, Ardeshir B. (2015). In silico evaluation of plant genetic resources to search for traits for adaptation to climate change. Climatic Change.  ISSN 0165-0009.  134(4), s 667- 680 . doi: 10.1007/s10584-015-1541-9 Vis sammendrag

  Plant genetic resources display patterns resulting from ecological and co-evolutionary processes. Such patterns are instrumental in tracing the origin and diversity of crops and locating adaptive traits. With climate change and the anticipated increase in demand for food, new crop varieties will be needed to perform under unprecedented climatic conditions. In the present study, we explored genetic resources patterns to locate traits of adaptation to drought and to maximize the utilization of plant genetic resources lacking ex ante evaluation for emerging climate conditions. This approach is based on the use of mathematical models to predict traits as response variables driven by stochastic ecological and co-evolutionary processes. The high congruence of metrics between model predictions and empirical trait evaluations confirms in silico evaluation as an effective tool to manage large numbers of crop accessions lacking ex ante evaluation. This outcome will assist in developing cultivars adaptable to various climatic conditions and in the ultimate use of genetic resources to sustain agricultural productivity under conditions of climate change.

• Bryn, Anders; Kristoffersen, Hans P.; Angeloff, Michael; Nystuen, Ingvild; Aune-Lundberg, Linda; Endresen, Dag Terje Filip; Svindseth, Christian & Rekdal, Yngve (2015). Location of plant species in Norway gathered as a part of a survey vegetation mapping programme. Data in Brief.  ISSN 2352-3409.  5, s 589- 594 . doi: 10.1016/j.dib.2015.10.014
• Thormann, Imke; Parra-Quijano, Mauricio; Iriondo, José M.; Rubio-Teso, María Luisa; Endresen, Dag Terje Filip; Maxted, Nigel; Dias, Sónia & Dulloo, Ehsan (2015). Two predictive characterization approaches to search for target traits in crop wild relatives and landraces. Crop Wild Relative.  ISSN 1742-3694.  13(10), s 16- 18
• Walls, Ramona L.; Deck, John; Guralnick, Robert; Baskauf, Steve; Beaman, Reed; Blum, Stanley; Bowers, Shawn; Buttigieg, Pier Luigi; Davis, Neil; Endresen, Dag Terje Filip; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Morrison, Norman; Ó Tuama, Éamonn; Schildhauer, Mark; Smith, Barry; Stucky, Brian J.; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie & Wooley, John (2014). Semantics in Support of Biodiversity Knowledge Discovery: An Introduction to the Biological Collections Ontology and Related Ontologies. PLoS ONE.  ISSN 1932-6203.  9(3), s 1- 13 . doi: 10.1371/journal.pone.0089606 Fulltekst i vitenarkiv. Vis sammendrag

  The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers.

• Wieczorek, John; Bánki, Olaf; Blum, Stan; Deck, John; Döring, Markus; Dröge, Gabriele; Endresen, Dag Terje Filip; Goldstein, Philip; Leary, Patrick; Krishtalka, Leonard; Ó Tuama, Éamonn; Robbins, Robert J.; Robertson, Tim & Yilmaz, Pelin (2013). Meeting Report: GBIF hackathon-workshop on Darwin Core and sample data (22-24 May 2013). Standards in Genomic Sciences.  ISSN 1944-3277.  9(3), s 614- 627 . doi: 10.4056/sigs.4898640 Fulltekst i vitenarkiv. Vis sammendrag

  The workshop-hackathon was convened by the Global Biodiversity Information Facility (GBIF) at its secretariat in Copenhagen over 22-24 May 2013 with additional support from several projects (RCN4GSC, EAGER, VertNet, BiSciCol, GGBN, and Micro B3). It assembled a team of experts to address the challenge of adapting the Darwin Core standard for a wide variety of sample data. Topics addressed in the workshop included 1) a review of outstanding issues in the Darwin Core standard, 2) issues relating to publishing of biodiversity data through Darwin Core Archives, 3) use of Darwin Core Archives for publishing sample and monitoring data, 4) the case for modifying the Darwin Core Text Guide specification to support many-to-many relations, and 5) the generalization of the Darwin Core Archive to a “Biodiversity Data Archive”. A wide variety of use cases were assembled and discussed in order to inform further developments.

• Bari, Abdallah; Street, Kenneth; Mackay, Michael; Endresen, Dag Terje Filip; De Pauw, Eddy & Amri, Ahmed (2012). Focused identification of germplasm strategy (FIGS) detects wheat stem rust resistance linked to environmental variables. Genetic Resources and Crop Evolution.  ISSN 0925-9864.  59(7), s 1465- 1481 . doi: 10.1007/s10722-011-9775-5 Vis sammendrag

  Recent studies have shown that novel genetic variation for resistance to pests and diseases can be detected in plant genetic resources originating from locations with an environmental profile similar to the collection sites of a reference set of accessions with known resistance, based on the Focused Identification of Germplasm Strategy (FIGS) approach. FIGS combines both the development of a priori information based on the quantification of the trait-environment relationship and the use of this information to define a best bet subset of accessions with a higher probability of containing new variation for the sought after trait(s). The present study investigates the development strategy of the a priori information using different modeling techniques including learning-based techniques as a follow up to previous work where parametric approaches were used to quantify the stem rust resistance and climate variables relationship. The results show that the predictive power, derived from the accuracy parameters and cross-validation, varies depending on whether the models are based on linear or non-linear approaches. The prediction based on learning techniques are relatively higher indicating that the non-linear approaches, in particular support vector machine and neural networks, outperform both principal component logistic regression and generalized partial least squares. Overall there are indications that the trait distribution of resistance to stem rust is confined to certain environments or areas, whereas the susceptible types appear to be limited to other areas with some degree of overlapping of the two classes. The results also point to a number of issues to consider for improving the predictive performance of the models.

• Endresen, Dag Terje Filip & Knüpffer, Helmut (2012). The Darwin Core extension for genebanks opens up new opportunities for sharing genebank data sets. Biodiversity Informatics.  ISSN 1546-9735.  8, s 11- 29 Vis sammendrag

  Darwin Core (DwC) defines a standard set of terms to describe the primary biodiversity data. Primary biodiversity data are data records derived from direct observation of species occurrences in nature or describing specimens in biological collections. The Darwin Core terms can be seen as an extension to the standard Dublin Core metadata terms. The new Darwin Core extension for genebanks declares the additional terms required for describing genebank datasets, and is based on established standards from the plant genetic resources community. The Global Biodiversity Information Facility (GBIF) provides an information infrastructure for biodiversity data including a suite of software tools for data publishing, distributed data access, and the capture of biodiversity data. The Darwin Core extension for genebanks is a key component that provides access for the genebanks and the plant genetic resources community to the GBIF informatics infrastructure including the new toolkits for data exchange. This paper provides one of the first examples and guidelines for how to create extensions to the Darwin Core standard.

• Endresen, Dag Terje Filip; Street, Kenneth; Mackay, Michael; Bari, Abdallah; Amri, Ahmed; De Pauw, Eddy; Nazari, Kumarse & Yahyaoui, Amor (2012). Sources of resistance to stem rust (Ug99) in bread wheat and durum wheat identified using focused identification of germplasm strategy. Crop science.  ISSN 0011-183X.  52(2), s 764- 773 . doi: 10.2135/cropsci2011.08.0427 Vis sammendrag

  The focused identification of germplasm strategy (FIGS) has been validated using predictive computer models in simulation studies to predict a priori known trait scores. This study was designed as a “blind” study where the person calculating the computer model did not know the actual trait scores. This study design provides a more realistic test of the predictive capacity of the FIGS approach compared to previous studies. Furthermore this study also explored the suitability of FIGS for the identification of resistance in bread wheat (Triticum aestivum L. subsp. aestivum) and durum wheat [Triticum turgidum L. subsp. durum (Desf.) Husn.] to Ug99—a strain of stem rust (Puccinia graminis Pers. f. sp. tritici Eriks. & Henn.) and typified to race TTKSK. The predictions were validated against a dataset with the screening of wheat accessions conducted in Yemen in 2008. Only a small training set representing 20% of the trait screening results was disclosed to the person conducting the data analysis for the calibration of the prediction model. The hit rate for identification of Ug99-resistant accessions was more than two times higher when using the FIGS approach compared to a random selection of accessions. These results suggested that FIGS was well suited for the identification of samples with resistance to fungal pathogens. It is therefore recommended that FIGS approach be used as a complement to expert knowledge and experience when selecting accessions for plant breeding and crop research activities.

• Endresen, Dag Terje Filip; Street, Kenneth; Mackay, Michael; Bari, Abdallah & De Pauw, Eddy (2011). Predictive association between biotic stress traits and ecogeographic data for wheat and barley landraces. Crop science.  ISSN 0011-183X.  51(5), s 2036- 2055 . doi: 10.2135/cropsci2010.12.0717 Vis sammendrag

  Collections of crop genetic resources are a valuable source of new genetic variation for economically important traits, including resistance to crop diseases. New sources of useful crop traits are often identified through evaluation in field trials. The number of relevant accessions in genebank collections available to be evaluated is often substantially larger than the capacity of the evaluation project. The focused identification of germplasm strategy (FIGS) is an approach used to select subsets of germplasm from genetic resource collections in such a way as to maximize the likelihood of capturing a specific trait. This strategy uses a range of methods to link the expression of a specific trait (of a target crop) with the eco-geographic parameters of the original collection site. This study contributes to the development of the approach by which a FIGS subset could be assembled for biotic traits. We have evaluated trait-specific subset selection methods for two fungal crop diseases, namely stem rust (Puccinia graminis Pers.) in wheat (Triticum aestivum L. and Triticum turgidum L.) and net blotch (Pyrenophora teres Drechs.) in barley (Hordeum vulgare L.). The results indicate that the climate layers from freely available eco-geographic databases are well suited to model and predict the reaction in these crops to biotic stress traits. This result has the potential to improve the efficiency of field screening trials to find novel sources of economically valuable crop traits.

• Endresen, Dag Terje Filip (2010). Predictive association between trait data and eco-geographic data for Nordic barley landraces. Crop science.  ISSN 0011-183X.  50(6), s 2418- 2430 . doi: 10.2135/cropsci2010.03.0174 Vis sammendrag

  Focused Identification of Germplasm (FIGS) is a new method to select plant genetic resources for the improvement of food crops. Traditional cultivars (landraces) and crop wild relatives (CWR) provide a valuable source for novel alleles in crop improvement programs, but conserved landraces and CWR often lack important documentation. Genebank collections worldwide provide ready access to plant genetic resources including online documentation. However, incomplete documentation, and in particular the lack of relevant characterization and evaluation data (traits), often limit the efficient use of plant genetic resources. This current study demonstrates how trait mining with the new FIGS method can be used to predict missing trait information for landraces. Ecogeographic data from the location of origin for 14 Nordic landraces of barley (Hordeum vulgare L.) was successfully correlated to morphological traits using a modern multilinear data modeling method (multilinear partial least squares [N-PLS]). This result suggests that trait mining can efficiently be used as a targeted germplasm selection method and complement or replace the current core selection method in situations when the requirements for the trait mining method are fulfilled.

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• Thormann, Imke; Parra-Quijano, Mauricio; Endresen, Dag Terje Filip; Rubio-Teso, María Luisa; Iriondo, José M. & Maxted, Nigel (2014). Predictive characterization of crop wild relatives and landraces: Technical guidelines version 1. Bioversity International.  ISBN 978-92-9255-004-2.  40 s. Fulltekst i vitenarkiv. Vis sammendrag

  Predictive characterizationPredictive characterization methods use ecogeographical and climatic data derived from the specific location of a collecting or observation site, to predict characteristics of accessions and populations that can inform conservation and use options. The predictive characterization methods presented in these technical guidelines for crop wild relatives (CWR) and landraces (LR) aim to enhance the use of CWR and LR through identification of sets of accessions or occurrences that have a higher likelihood of harbouring genetic diversity for specific adaptive traits than a set selected at random. The methods presented are the ecogeographical filtering and the calibration method. These are two of the various methods that implement the Focused Identification of Germplasm Strategy (FIGS). The guidelines were developed within the framework of the EU funded project PGR Secure ‘Novel characterization of crop wild relative and landrace resources as a basis for improved crop breeding’.

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• Endresen, Dag Terje Filip (2018). Event core and new data types in GBIF. Vis sammendrag

  Integrating event-core and other new and complex data types (data models) in GBIF. Data types inside Darwin Core not yet supported in GBIF. Introduction for starting the discussions at the 10th European GBIF Nodes Meeting in Tallinn Estonia 15th May 2018. See also: http://bit.ly/gbifEu2018_datatypes | http://bit.ly/gbifEu2018_new_datatypes | DOI: 10.13140/RG.2.2.16667.36641

• Endresen, Dag Terje Filip; Finstad, Anders Gravbrøt; Skyttner, Markus & Nilsen, Erlend Birkeland (2018). Scientific reuse of openly published biodiversity information: Programmatic access to and analysis of primary biodiversity information using R. Vis sammendrag

  Scientific use of openly published and aggregated primary biodiversity information is in steady increase. Reuse of open research data and academic data citation is an emerging trend that is prioritized by current research policies, and citation of biodiversity data published through the Global Biodiversity Information Facility (GBIF.org) shows a steady upward trend. On-going improvements in biodiversity informatics to build support for new data types, such as the recent event-core in GBIF, open up for new uses of GBIF-mediated data. However, many researchers still access biodiversity data in GBIF from the web portal and the advanced machine readable programming interfaces (APIs) remain arguably underutilized. This Oikos 2018 workshop will introduce participants to the GBIF API and stimulate Nordic ecologists and systematists to a more programmatic use of GBIF data. Most examples and training exercises will use the R language and software environment for statistical computing. Scientific workflows with tools such as Galaxy will not be covered in this workshop. However, the interested workshop participant will be gently guided towards further reading material. The workshop is organized by the Norwegian participant node in GBIF (GBIF.no) and the ForBio Research School in Biosystematics (forbio.uio.no), both hosted by the UiO Natural History Museum in Oslo and will take place on Sunday 2018-02-18 and Monday 2018-02-19 at the Oikos conference venue Trondheim. Registration is open for both Oikos 2018 participants and ForBio members. We plan to spend some time to work in groups with hands-on exercises, so please consider bringing your own data and research questions to the workshop. We will also prepare some training datasets for you to work with.

• Bari, Abdallah; Chaubey, Yogendra P.; Sillanpää, Mikko J.; Ouabbou, Hassan; Jilal, A.; Khazaei, H.; Stoddard, Frederick L.; Dayanandan, S.; De Pauw, Eddy; Endresen, Dag Terje Filip; Damania, Ardeshir B. & Nachit, Mikael Miloudi (2017). Machine-Learning approaches to accelerate the utilization of plant genetic resources. Vis sammendrag

  Mathematical approaches have played a major role in advancing plant breeding since the 1920s, prior to the emergence of molecular approaches. They have been extensively used in plant breeding to capture the genetic variability and inheritance of quantitative traits, assess the interaction between genotypes and environments and predict the performance gains. While this has helped, a great deal, in plant breeding, mathematical approaches have been less used in pre-breeding and in the mobilization of these yet untapped resources into plant breeding. There is a considerable potential for using mathematical approaches to identify sought after traits in a much reduced number of accessions within a shorter period of time, and mobilize these traits into breeding programs. Our paper focuses on exploring the potential of mathematical approaches to accelerate the mobilization of genetic resources into breeding programs, as tested in the Focused Identification of Germplasm Strategy (FIGS). Several mathematical approaches including Laplace Bayes Inverse problems theorems serve as promising tools for identifying plant accessions harboring genes relevant for adaptation to a variety of environmental conditions expected under changing climate conditions. The use of existing information and knowledge such as the probability distribution of traits in contrasting environments is invaluable for locating relevant genotypes and identifying sought- after traits to achieve highest payoffs in breeding. This will also unravel other barriers that prevent the effective utilization of genetic resources in breeding such as the lack of comprehensive evaluation as well as the bottlenecks in the analyses of massive data associated with these under-utilized genetic resources, which are mostly “non- replicated” and “non-experimental” types including unstructured type of data. We will demonstrate how mathematical approaches have contributed in the past to the mobilization of genetic resources, and how they will advance global collaborative research efforts to address current and future challenges for plant improvements in the light of changing climate conditions.

• Baskauf, Steve; Hyam, Roger; Blum, Stan; Morris, Robert A.; Rees, Jonathan; Sachs, Joel; Whitbread, Greg; Wieczorek, John & Endresen, Dag Terje Filip (ed.) (2017). Standards Documentation Specification. Vis sammendrag

  This document defines how TDWG standards are to be presented. It provides details about the hierarchical structure of standards and versioning of standards components. It specifies how the properties of standards and their components are to be described in human-readable and machine-readable terms.

• Baskauf, Steve; Wieczorek, John; Blum, Stan; Morris, Robert A.; Rees, Jonathan; Sachs, Joel; Whitbread, Greg & Endresen, Dag Terje Filip (ed.) (2017). Vocabulary Maintenance Specification. Vis sammendrag

  This document describes the processes used to modify TDWG vocabularies and their associated documents.

• Endresen, Dag Terje Filip (2017). Chapter 42: Information, knowledge and agricultural biodiversity, In Danny Hunter; Luigi Guarino; Charles Spillane & Peter McKeown (ed.),  Routledge Handbook of Agricultural Biodiversity.  Routledge.  ISBN 9780415746922.  42.  s 646 - 661
• Endresen, Dag Terje Filip (2017). GBIF data portal, ECPGR Cereal and Forage working group meeting. Vis sammendrag

  The ECPGR working groups on forage crops and on barley invited GBIF-Norway to the joint workshop in Malmö to present the GBIF data portal. The European Cooperative Programme for Plant Genetic Resources (ECPGR) organized a joint workshop for the working groups on Forage crops and on Barley crops in Malmö. The workshop addressed publication of genebank accession and collection data in the European Genebank Search Catalog (EURISCO). Topics also included demonstrations on how to publish characterization & evaluation (C&E) trait data in EURISCO.

• Endresen, Dag Terje Filip (2017). If a tree falls in the forest and nobody publish the event in GBIF, did it really happen? Global Biodiversity Information Facility, free and open access to biodiversity data..
• Endresen, Dag Terje Filip (2017). Predictive characterization of wheat and barley landraces - using GBIF-mediated data. Vis sammendrag

  Advancements in plant breeding technologies and in agricultural management practices has caused a steady improvement to the food crops we depend upon for our livelihood. This steady long-term progress has become the norm and an expectation in the larger society. Mathematical approaches and statistical analysis have persisted to provide important tools for plant breeders, in particular since the 1920s. The emergence of molecular methods, during the recent decades, are also largely dependent on mathematical approches to identify new sources of useful genetic diversity. Recent years has seen an explosion in available data, in society as well as in agriculture. This explosion has in popular terms described as an paradigm shift into an era of big data. Novel mathematical approches and machine learning algorithms are under rapid development to ensure capabilities for analysing rapidly increasing volumes of data. International biodiversity information systems have successfully provided access to larger datasets with primary information on agricultural crops. The Genesys information system operated by the Global Crop Diversity Trust and the Global Biodiversity Information Facility (GBIF) provides only two among many examples. The largest increase of information of potential use in crop improvements can, however, be argued to be from sensor data inside the agricultural fields and elsewhere, and other data types that cen be used as explanatory variables in machine learning algorithms for identification of useful genetic diversity. Focused identification of germplasm strategy (FIGS) proposes a new approach to target the evaluation of key germplasm accessions most likely to hold the genetic diversity required by plant breeding programs. This predictive characterization approach is based on the hypotheses that this key germplasm is likely to reflect the selection pressures of the environment from which it was originally sampled. Machine learning models are used to identify genebank accessions and crop wild populations with potentially useful alleles. This provides a computer assisted pre-screening tool to select material for field trials and subsequent molecular approaches to identify novel alleles for plant breeding programs.

• Endresen, Dag Terje Filip (2017). UiO CEES Friday seminar: Open and reusable research data with the Global Biodiversity Information Facility (GBIF). Vis sammendrag

  If a tree falls in the forest and nobody reuses this information in peer review validated research — for what purpose did we then publish the event in GBIF? Easy access to large data volumes is a new paradigm that researchers in many fields are starting to get used with. Production of good quality research data is very expensive and research councils and governments around the world, including Norway, are looking for scientific practices to maximize the reuse of research data for other purposes than what it was originally collected for. The Global Biodiversity Information Facility (GBIF.org) is an open-data research infrastructure funded by the world’s governments and aimed at providing anyone, anywhere access to data about all types of life on Earth. GBIF was established in March 2001, following a recommendation from the OECD Mega-science Forum in 1999. Norway became a voting member in April 2004. Dag Endresen is the national coordinator for the Norwegian participant node in GBIF. The Norwegian GBIF Node (GBIF.no) is hosted by the UiO Natural History Museum in Oslo and provides support (gbif-drift@nhm.uio.no) for publishing and using biodiversity data made available in GBIF to researchers and other users in Norway. In this presentation Dag Endresen will present the GBIF organisation with focus on examples for reuse of biodiversity data in ecological research and provide guidelines for publishing your own research data in GBIF.

• Endresen, Dag Terje Filip; Oswald, Emily; Svindseth, Christian; Bjørn Petter, Løfall & Hetland, Per (2017). Citizen Science dugnadsportal for Telemark Botanisk Forening. Vis sammendrag

  Large number of specimens in the Natural History Museums remain un-digitized and are not yet available in electronic form. The Volunteer Portal is a citizen science project where amateur naturalists are invited to contribute to the electronic registration of herbarium collections. Telemark Botanical Society will help us to test and explore the Volunteer Portal.

• Fitzgerald, Heli; Palmé, Anna; Aronsson, Mora; Endresen, Dag Terje Filip; Weibull, Jens; Asdal, Åsmund; Þorbjörnsson, Hjörtur; Ramussen, Morten; Lund, Birgitte & Kiviharju, Elina (2017). Nordic Crop Wild Relative (CWR) Checklist. [www ]. Vis sammendrag

  The Nordic Crop Wild Relative (CWR) checklist is a result from a joint Nordic project, "Ecosystem services: Genetic resources and crop wild relatives" (2015-2016) funded by the Nordic Council of Ministers and the Nordic Genetic Resources Center (NordGen). A Crop Wild Relative (CWR) is a wild species that is closely related to a cultivated crop. This close relationship means that properties in a CWR can be transferred to the crop by traditional crossings. As modern cultivars may lack the desired variation, diversity found in CWRs can be central for adaptation to new demands on the crops.

• Oswald, Emily; Svindseth, Christian; Løfall, Bjørn Petter; Endresen, Dag Terje Filip & Hetland, Per (2017). Citizen science dugnadsportal for Telemark Botanisk Forening.
• Palmé, Anna; Fitzgerald, Heli; Weibull, Jens; Asdal, Åsmund; Lund, Birgitte; Endresen, Dag Terje Filip; Kiviharju, Elina; Þorbjörnsson, Hjörtur; Rasmussen, Morten & Carlson-Nilsson, Ulrika (2017). A Nordic regional approach for crop wild relative (CWR) conservation. Vis sammendrag

  The Nordic project “Ecosystem services: Genetic resources and crop wild relatives” was initiated with the long-term aim to assure conservation and sustainable use of the wild genetic resources associated with future food security. There is an increasing threat to crop wild relatives (CWRs) in nature and actions are therefore needed to safeguard these important resources. The Nordic project has resulted in two stakeholder workshops (Stockholm 2015, Vilnius 2016), a common homepage dedicated to Nordic CWR (www.nordgen.org/cwr), policy recommendations on CWR conservation and use and the first common Nordic conservation approach for CWRs. During the project, a common CWR checklist was created and prioritized. The most important crop wild relatives of the region, related to food and forage crops, were selected with use and value criteria. The in situ conservation planning identified potential complementary conservation sites for the priority species. These sites would conserve a maximum number of target taxa and their intraspecific variation by using ecogeographic land characteristic map categories of the region as a proxy for the adaptive scenarios of the priority taxa populations. The potential conservation sites are found in all the five countries (Denmark, Iceland, Finland, Norway and Sweden) across the Nordic region. Since the Nordic countries share many species and habitats across the region, the goal is that joint conservation planning on the Nordic level should make national conservation activities more efficient. The project is funded by Nordic Council of Ministers.

• Arnaud, Elizabeth; Castañeda-Álvarez, Nora Patricia; Cossi, Jean Ganglo; Endresen, Dag Terje Filip; Jahanshiri, Ebrahim & Vigouroux, Yves (2016). Final Report of the Task Group on GBIF Data Fitness for Use in Agrobiodiversity. Fulltekst i vitenarkiv. Vis sammendrag

  Human wellbeing and food security in a changing climate depend on productive and sustainable agriculture. For this, policies based on analyses and research results are vital to establish conservation priorities of natural resources that underpin the enhancement of sustainable food production. Therefore, data from agrobiodiversity and wider biodiversity sources are required to be available and accessible. Currently, there is a risk that agrobiodiversity and the wider biodiversity data communities remain separated with inefficient data aggregation, unless data flow pathways are harmonized. GBIF has a role to play in contributing to the convergence of the two communities. Biodiversity data in particular on wild relatives of the cultivated species will flow easier into agrobiodiversity conservation priority assessments and analysis with agrobiodiversity data integrated in GBIF. The Task Group on Data Fitness for Use in Agrobiodiversity was established by the GBIF Secretariat and Bioversity International to help improve the fit of data related to agrobiodiversity to the variety of important uses required and requested by the community of research and policy. The task group has been looking at the key actions for creating interoperability of data on ex situ, in situ and on-farm conservation of agrobiodiversity, with a focus on plants. A survey and interviews of selected experts and ABD data practitioners were conducted to collect feedback on fitness for use and issues with GBIF-mediated data. The 53 recommendations of the task group cover the whole data flow, from publishing to data use with a focus on agrobiodiversity, also considering the role of nodes in data mobilization and in promotion and training. Some key recommendations are to (i) promote GBIF to the agrobiodiversity community, (ii) integrate the terms from the long-standing Multi Crop Passport Data standard (MCPD) already used for several decades by agricultural gene banks into Darwin Core indexed attributes, (iii) by installing proper governance, the Darwin Core germplasm extension can be maintained as a stable international standard, (iv) develop agrobiodiversity user profiles on GBIF data portal to improve the user experience in accessing data of interest, (v) add infraspecific taxonomy levels to ensure adequate publication of agrobiodiversity data, by means of integrating into the GBIF taxonomic backbone the reference taxonomies used by the community with additional attributes related to the crop wild relative species, landraces and cultivars, (vi) publish existing digitized ABD data collections, such as the Bioversity Collecting Mission database1 and the Crop Wild Relative Global Occurrence dataset2, to support capacity building of agrobiodiversity data publishers, (vii) provide quality filtering of the data only using attributes of interest to the agrobiodiversity data users. Additionally, GBIF needs to provide tools and services to discover, mobilize, or link to additional specialized data sources commonly used by the agrobiodiversity community. Integrated access from GBIF to external sources of key agrobiodiversity data would be an added value for the community. (viii) Assign a level of confidence to individual data records, and (ix) channel feedback to data suppliers. The task group identified increasing the knowledge of the nodes about agrobiodiversity data through training as a key step to enable them to play a more prominent role in the mobilization of locally available information resources on ABD. A priority setting of these recommendations, with the feedback of the ABD community, the GBIF country parties and the expert knowledge of the GBIF secretariat and nodes, is needed.

• Endresen, Dag Terje Filip (2016). Downloading species occurrence data using the GBIF web-service API. Vis sammendrag

  The Global Biodiversity Information Facility (GBIF) provides a comprehensive e-infrastructure were data holding institutions can publish biodiversity data, and were researchers and other data analysts can access and download biodiversity data. Norway is one of the absolute largest data publishers in GBIF, but we still remain a more modest user of biodiversity data indexed into the global GBIF portal. This seminar will present some of the web-services and R-packages for accessing and downloading species occurrence data and taxonomic names made available in GBIF.

• Endresen, Dag Terje Filip (2016). #HepaticaWeek April 2016, GBIF data publishing. Vis sammendrag

  Citizen science species observation reporting and data publishing with the Global Biodiversity Information Facility (GBIF). Video feed available at: https://youtu.be/t22QmFPcvOM?t=34m4s

• Endresen, Dag Terje Filip; Svindseth, Christian; Bakken, Vidar; Koch, Wouter; Henriksen, Snorre & Valland, Nils (2016). GBIF data publishing workshop in Tromsø, September 2016. Vis sammendrag

  GBIF Norway (GBIF.no) and the Norwegian Biodiversity Information Centre (Artsdatabanken.no) organize a seminar on data publishing in Tromsø on 7th and 8th of September 2016. The seminar is suitable for all institutions, companies and other stakeholders that are engaged in registration of, or have plans to start registration of species-based biodiversity data. The seminar will cover the importance of collecting and publishing species-based biodiversity data, and describe some of the methods for data registration and data publication. Following the seminar on day 1 we will organize a training workshop where all participants will get basic skills for preparing and standardizing their own datasets. On day 2 we will be available for individual support with data publication. To sign up for day 2, you should already have datasets that are ready for publication. We plan to complete as far as possible the data preparation and data publication during the hands-on workshop.

• Endresen, Dag Terje Filip; Svindseth, Christian; Valland, Nils & Grytnes, John-Arvid (2016). GBIF data publishing seminar at the Department of Biology at the University of Bergen. Vis sammendrag

  The GBIF node and the Norwegian Biodiversity Information Center (NBIC, Artsdatabanken) organized a biodiversity informatics seminar at the University of Bergen about data publication and use.

• Endresen, Dag Terje Filip; Svindseth, Christian; Valland, Nils; Koch, Wouter & Sørensen, Ole Jakob (2016). GBIF seminar om datapublisering for Nord Universitet, campus Steinkjer. Vis sammendrag

  GBIF Norge, Artsdatabanken og Nord Universitet organiserte et åpent seminar om datapublisering hos Nord Universitet i Steinkjer.

• Endresen, Dag Terje Filip; Wang, Yu-Huang; Chiang, Po-Jen & Mai, Guan-Shuo (2016). GBIF BIFA mentoring: Orientation Workshop on Mobilizing Biodiversity Data from ASEAN Protected Areas. Vis sammendrag

  GBIF BIFA mentoring in Los Banos, Philippines for the South-East Asian ASEAN Heritage Parks (AHP). * Camera trap setup, monitoring and data collection * Data publishing using the IPT. With Dr. Yu-Huang Wang, Dr. Po-Jen Chiang, and Guan-Shuo (Jason) Mai from TaiBIF the GBIF node of Taiwan (Chinese Taipei); and the Biodiversity Informatics team at ASEAN Centre For Biodiversity, Carmel Eje, Carlos Aurelio Callangan, Ecay Villavelez, Jerome Alano, Kit Elloran (ACB Node manager), Lilibeth Cabebe, and Dr. Sheila G Vergara (BIM Director). Participants included some of the ASEAN Heritage Park managers and staff from Brunei Darussalam (BR), Indonesia (ID), Laos PDR (LA), Malaysia (MY), Myanmar (MM), Philippines (PH), Singapore (SG), and Thailand (TH). Only Cambodia and Vietnam were absent at the workshop. The camera trap field work training was in the Mount Makiling Forest Reserve (MMFR) is an ASEAN Heritage Park located 14°8′ north and 121°12′ east and lies within the 65 km of Metro Manila. MMFR spans a total of 4,244 hectares.

• Thormann, Imke; Parra-Quijano, Mauricio; Rubio Teso, María Luisa; Endresen, Dag Terje Filip; Dias, Sonia; Iriondo, José M. & Maxted, Nigel (2016). Predictive characterization methods for accessing and using CWR diversity, In Nigel Maxted; Mohammad Ehsan Dulloo & Brian V. Ford-Lloyd (ed.),  Enhancing crop genepool use: capturing wild relative and landrace diversity for crop improvement.  CABI Publishing.  ISBN 9781780646138.  Chapter 8.  s 64 - 77 Vis sammendrag

  This chapter reports and discusses the results of the application of the ecogeographical filtering and calibration methods to crop wild relatives of the genera Avena, Beta, Brassica and Medicago, which were the target genera of the PGR Secure project. The ecogeographical filtering method filters occurrence records, combining the spatial distribution of the target taxon on an ecogeographical land characterization map (ELC) with the ecogeographical characterization of those environments that are likely to impose selection pressure for the adaptive trait investigated. In the predictive characterization context, a taxon-specific ELC map is used, aiming at representing the adaptive scenarios that are present over the territory studied. The calibration method uses a training set with existing characterization and evaluation data for the trait of interest, together with ecogeographical data specific to the environment at the sites from where these accessions were collected, to identify existing relationships between the trait and the environment.

• Austrheim, Gunnar; Endresen, Dag Terje Filip; Finstad, Anders Gravbrøt; Grytnes, John-Arvid; Koch, Wouter; Lindgaard, Arild; Mathisen, Ingrid Ertshus; Speed, James David Mervyn & Øien, Dag-Inge (2015). Deling av vegetasjonsdata: Forslag til infrastruktur for å sikre faglige og tekniske standarder som kan lette datautveksling. NTNU Vitenskapsmuseet naturhistorisk rapport. 4. Vis sammendrag

  Vegetasjonsdata utgjør et viktig kunnskapsgrunnlag både for forskning og forvaltning, men deling av disse dataene har vært vanskelig å realisere av ulike årsaker. Denne rapporten gjennomgår viktige juridiske prinsipper for datadeling og samarbeid, samt mulige faglige og tekniske standarder og løsninger som kan lette datautvekslingen. For å vise hvilke konkrete utfordringer som er knyttet til deling av vegetasjonsdata har vi brukt tre ulike vegetasjonsdatasett som gjennomgående eksempler. Avslutningsvis presenterer vi et forslag til en nasjonal infrastruktur for deling av vegetasjonsdata der både juridiske prinsipper, standarder for dataflyt, organisering og ansvarsforhold, virkemidler og ressursbehov er vurdert.

• Endresen, Dag Terje Filip (2015). Data publication to GBIF and Artskart, presentation at the Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences (NMBU). Vis sammendrag

  Data publication meeting at the Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences (NMBU), GBIF Norway and the Norwegian Biodiversity Information Centre (Artsdatabanken).

• Endresen, Dag Terje Filip (2015). GBIF og crowdsourcing ved Naturhistorisk museum. Vis sammendrag

  UiO Naturhistorisk museum er vertskap for den norske noden i et globalt samarbeide som heter Global Biodiversity Information Facility (GBIF). Dag Endresen fra Naturhistorisk museum forteller om hensikten med nettverket med fokus på hvordan disse artsdata brukes for forskning i Norge. Samlingene ved de naturhistoriske museene omfatter biologiske innsamlinger datert fra 250 år tilbake i tid og frem til i dag. En stor utfordring med å bygge en virtuell digital database med informasjon om alle samlingsobjektene er at mange av de eldre samlingene ikke er registrert digitalt ennå. Mye informasjon er fortsatt kun tilgjengelig fra etikettene som er festet til de fysiske samlingsobjektene. En innsats har startet i mange land, inkludert Norge, for å fotografere samlingsobjektene slik at etiketten er synlig i bildet. Vi etablerer nå web-løsninger der vi ber om hjelp fra publikum til å bli med på å database-registrere samlingene.

• Endresen, Dag Terje Filip (2015). GBIF portal API. Vis sammendrag

  A brief presentation of examples using the GBIF API for the GBIF nodes training hackaton for checklist cross-mapping and precursor national checklist generation from GBIF data. Organized by Species 2000 and GBIF at Naturalis in Leiden, March 2015.

• Endresen, Dag Terje Filip; Brosens, Dimitri & Svindseth, Christian (2015). Data paper workshop, March 2015, Trondheim. Vis sammendrag

  Introduction to writing good data set metadata and to the procedure for writing and submitting data paper manuscripts to the PENSOFT Biodiversity Data Journal. Participants bring their own data set(s) and we aim at least a good start on the writing for a complete data paper manuscript by the end of day 2.

• Endresen, Dag Terje Filip; Svindseth, Christian; Finstad, Anders Gravbrøt & Vang, Roald (2015). Biodiversity data publishing workshop October 2015, Trondheim. Vis sammendrag

  NINA, NTNU University Museum, GBIF Norway and the NBIC (Artsdatabanken) organized a workshop on publication of biodiversity occurrence data to GBIF and the Norwegian Map Service (Artskart) at NINA in Trondheim in October 2015. The workshop provides an introduction to publishing biodiversity data through the GBIF network - with a focus on the recent support for publishing sample-based and monotoring data using the GBIF online data infrastructure.

• Endresen, Dag Terje Filip (2014). Data exchange: the Darwin core and other approaches. Vis sammendrag

  Presentation on the Darwin Core standard for data exchange and the germplasm extension for genebanks during the 2014 workshop of the ECPGR Documentation and Information Working Group "Tailoring the Documentation of Plant Genetic Resources in Europe to the Needs of the User" (http://www.ecpgr.cgiar.org/working_groups/documentation_information/docinfo2014.html) in Prague-Ruzyně, Czech Republic, 20th May 2014.

• Endresen, Dag Terje Filip (2014). Lansering av crowdsourcing ved NHM. Vis sammendrag

  Som første museum i Norge inviterer Naturhistorisk museum i Oslo publikum til å delta i arbeidet med å registrere data fra gamle herbarieark. Samlingene ved NHM har en historie som strekker seg tilbake til 1700-talet. I mer enn to hundre år har forskere herfra samlet inn plantar, sopp og lav til herbariesamlingene her. Mye av materialet er altså samlet inn lenge før datamaskiner og internett så dagens lys. Derfor har vi et enormt etterslep i elektronisk registrering av materialet. Du kan bidra til museet sitt samlingsarbeid ved å gå inn på http://gbif.no/dugnad. Der vil du få opp foto av et herbarieark, og en boks der du kan fylle inn manglende data.

• Endresen, Dag Terje Filip (2014). Persistent identifiers: Connecting data. Vis sammendrag

  Implementation of persistent and globally unique identifiers for specimens held in natural history collections worldwide will open up new opportunities for referring to these physical resources in an interlinked digital context such as the Internet. Here, we will describe the approach for persistent identification of collection specimens developed and implemented at the Natural History Museum in Oslo (NHM-UiO) by the the Norwegian participant node to the Global Biodiversity Information Facility (GBIF-Norway). The Norwegian university museums are invited to use our resolver service at "http://purl.org/gbifnorway/id/<UUID>" when publishing biodiversity data to GBIF. All occurrence records published through GBIF-Norway with appropriate PURL-UUID identifiers mapped to the Darwin Core occurrenceID will be automatically added to our resolver service and kept updated.

• Endresen, Dag Terje Filip (2014). Searching for traits of resistance to crop diseases and pests in plant genetic resources. Vis sammendrag

  The agricultural food crops we depend upon for our livelihood are exposed to evolving plant diseases, pests and environmental climate change. Plant breeding programs require access to novel genetic diversity to maintain and improve the food crops to keep pace with these changes. The genetic diversity available in the breeders material has already been intensively explored and we need to start looking into traditional landraces (farmers varieties) and crop wild relatives as new sources of genetic materials. However, field experiments to gather trait evaluation data are expensive, and many of these less explored plant genetic resources lack availability to such information. The Global Biodiversity Information Facility (GBIF) has contributed to mobilize primary biodiversity information, including georeferenced plant genetic resources of landraces and crop wild relatives. Focused identification of germplasm strategy (FIGS) proposes a new approach to target the evaluation of key germplasm accessions most likely to hold the genetic diversity required by plant breeding programs. This predictive characterization approach is based on the hypotheses that this key germplasm is likely to reflect the selection pressures of the environment from which it was originally sampled. Statistical techniques are applied to build predictive models between responses to biotic stresses such as fungal crop diseases and the environmental conditions of the collecting sites where the sampled germplasm of traditional agricultural landraces and crop wild relatives originally evolved. The prediction models are then used to identify genebank accessions and crop wild populations with potentially useful alleles. This provides a computer assisted pre-screening tool to select material for field trials and subsequent molecular allele mining to identify novel alleles for plant breeding programs.

• Endresen, Dag Terje Filip; Bari, Abdallah; Street, Kenneth; Amri, Ahmed & Mackay, Michael (2014). Searching for traits of resistance to crop diseases and pests in plant genetic resources. Vis sammendrag

  The agricultural food crops we depend upon for our livelihood are exposed to evolving plant diseases, pests and environmental climate change. Plant breeding programmes require access to novel genetic diversity to maintain and improve the food crops to keep pace with these changes. Focused identification of germplasm strategy (FIGS) proposes a new approach to target the evaluation of key germplasm accessions most likely to hold the genetic diversity required by plant breeding programmes. The FIGS approach is based on the hypotheses that this key germplasm is likely to reflect the selection pressures of the environment from which it was originally sampled. Statistical techniques were applied to build predictive models between responses to biotic stresses such as fungal crop diseases and the environmental conditions of the collecting sites where the sampled germplasm of traditional agricultural landraces originally evolved.

• Endresen, Dag Terje Filip & Svindseth, Christian (2014). Persistent identifiers for museum specimens in Norway. Vis sammendrag

  One of the key challenges in maturing biodiversity informatics infrastructures is the integration of data across disparate databases. Implementation of persistent and globally unique identifiers (PIDs) for specimens held in natural history collections will open up new opportunities for referring to these physical resources in an interlinked digital context such as the Internet. Different approaches for declaring and resolving such persistent identifiers are now being implemented for the first natural history collections. The catalog numbers assigned to almost all of the specimens in the Natural History Museum at the University of Oslo (NHM-UiO) are unique and will identify the specimens unambiguously given the context of the museum. However, in a larger context, such as the information network established by GBIF, the catalog numbers are often no longer sufficiently unique. Alternative solutions such as the Darwin Core triplet, composed of an institution code, collection code, and catalog number separated by a colon, have been explored with various success. The Darwin Core triplet aim to combine the catalog number with additional identifiers or strings that encode for the local context where the catalog numbers are locally unique. This approach has proven challenging partly because of the lack of persistent codes/identifiers for the institutions and collections. NHM-UiO has implemented an approach for persistent identifiers (PIDs) using universally unique identifiers (UUIDs) prefixed by a persistent uniform resource locator (PURL) “http://purl.org/nhmuio/id/[UUID]”. The identifiers are optimized for machine readability by encoding the http-PURL-UUID-string as QR codes or data matrix barcodes before they are attached to the labels of the physical specimens. The UUID provides the globally unique identity for the physical specimen. The http-PURL prefix is part of the identifier and provides the redirection (HTTP 303 "see other") to the resolver service located at “http://gbif.no/resolver/[UUID]”. Using content negotiation the user or machine can access descriptive information as html, comma-separated-values (csv), tab-delimited text-files, n3/turtle RDF data, and json. These formats can also be accessed directly (without calling content negotiation) using the file extension "http://gbif.no/resolver/[UUID].[html|csv|txt|n3|json]". All Norwegian institutions are invited to use this resolver service at "http://purl.org/gbifnorway/id/[UUID]" when publishing biodiversity data to GBIF. All occurrence records published through GBIF-Norway, with appropriate identifiers (mapped to occurrenceID), will be added to the resolver service. After the first year of operation new persistent identifiers have been assigned and physically attached to more than 250 000 (255 046) specimens held by NHM-UiO.

• Endresen, Dag Terje Filip; Svindseth, Christian; Timdal, Einar & Rindal, Eirik (2014). Crowdsourcing portal for transcription of label information for Norwegian natural history collections. Vis sammendrag

  The number of specimens in natural history museums and university-collections worldwide count approximately 1.2 to 3 billion specimens. These collections provide a unique resource for understanding biological and ecological processes across time and place. Norwegian natural history collections have been estimated to include a total of 8.5 million specimens. An estimated 65% of the specimens have been digitized (in some form) and 30% published to the GBIF portal. Recent large-scale digitization efforts in Norway have focused on the imaging of a large number of specimens accompanied by initial minimal database registration, limited to scientific name, year and the country where the specimen was collected. The registration of more complete label information is recognized to require laborious efforts and it was decided to explore a citizen science approach with a volunteer transcription portal. After exploring similar volunteer transcription portals (such as the portals from the Botanical Society of Britain & Ireland, Atlas of Living Australia, National Museum of Natural History in Paris and Smithsonian), the Natural History Museum in Oslo initiated contact and collaboration with the Notes from Nature team. A simplified software implementation, based on Notes from Nature, was developed at the Natural History Museum in Oslo during the first months of 2014 and launched on June 1st (http://gbif.no/transcribe/). The first collection of images to be made available for volunteer transcription included 2850 non-digitized specimens from the Lichen herbarium collected in Africa. Each image is registered three times by individual volunteers. Already during the first two weeks, more than 1000 of the specimens (40%) were completed. By early August, most of the (easy) labels were completed (70%). A new batch with images of non-digitized African Lichens, and also other collections such as the non-digitized specimens from the vascular plant herbarium, will soon be included to the portal.

• Hanssen, Frank Ole; Heggberget, Tor Gravråk; Bladt, Jesper; Endresen, Dag Terje Filip; Forsius, Martin; Gudmundsson, Gudmundur A.; Gärdenfors, Ulf; Heiðmarsson, Starri; Kindvall, Oscar; Koch, Wouter; Koivula, Hanna; Laiho, Eija-Leena; Obst, Matthias; Skov, Flemming; Telenius, Anders; Valland, Nils; Wasowicz, Pawel & Wremp, Anna Maria (2014). Nordic LifeWatch cooperation, final report: A joint initiative from Denmark, Iceland, Finland, Norway and Sweden. Fulltekst i vitenarkiv. Vis sammendrag

  The main goal of the present report is to outline the possibilities for an enhanced cooperation between the Nordic countries within eScience and biodiversity. LifeWatch is one of several ESFRI projects which aim to establish eInfrastructures and databases in the field of biodiversity and ecosystem research. Similarities between Nordic countries are extensive in relation to a number of biodiversity related issues. Most species in Nordic countries are common, and frequently the same challenges concerning biodiversity and ecosystem services are addressed in the different countries. The present report has been developed by establishing a Nordic LifeWatch network with delegates from each of the Nordic countries. The report has been written jointly by the delegates, and the work was organized by establishing working groups with the following themes: strategic issues, technical development, legal framework and communication. Written during two workshops, Skype meetings and emailing, the following main issues are discussed in the present report: * Scientific needs for improved access to biodiversity data and advanced eScience research infrastructure in the Nordic countries. * Future challenges and priorities facing the international biodiversity research community. * Scientific potential of openly accessible biodiversity and environmental data for individual researchers and institutions. * Spin-off effects of open access for the general public. * Internationally standardized Nordic metadata inventory. * Legal framework and challenges associated with environmental-, climate-, and biodiversity data sharing, communication, training and scientific needs. * Finally, some strategic steps towards realizing a Nordic LifeWatch construction and operational phase are discussed. Easy access to open data on biodiversity and the environment is crucial for many researchers and research institutions, as well as environmental administration. Easy access to data from different fields of science creates an environment for new scientific ideas to emerge. This potential of generating new, interdisciplinary approaches to pre-existing problems is one of the key features of open-access data platforms that unify diverse data sources. Interdisciplinary elements, access to data over larger gradients, compatible eSystems and eTools to handle large amounts of data are extremely important and, if further developed, represent significant steps towards analysis of biological effects of climate change, human impact and development of operational ecosystem service assessment techniques. It is concluded that significant benefits regarding both scientific potential, technical developments and financial investments can be obtained by constructing a common Nordic LifeWatch eInfrastructure. Several steps concerning organizing and funding of a future Nordic LifeWatch are discussed, and an action plan towards 2020 is suggested. To analyze the potential for future Nordic LifeWatch in detail, our main conclusion is to arrange a Nordic LifeWatch conference as soon as possible. This conference should involve Nordic research councils, scientists and relevant stakeholders. The national delegates from the participating countries in the Nordic LifeWatch project are prepared to present details from the report and developments so far as a basis for further development of Nordic LifeWatch. The present work is financed by NordForsk and in-kind contributions from participating institutions.

• Hilde, Zahl & Endresen, Dag Terje Filip (2014, 04. august). NRK P1 Kveldsåpent 04.08.2014 Besøk fra Naturhistorisk museum. [Radio].  NRK P1 radio.
• Thormann, Imke; Parra-Quijano, Mauricio; Iriondo, José M.; Rubio-Teso, María Luisa; Endresen, Dag Terje Filip; Dias, Sónia; van Etten, Jacob & Maxted, Nigel (2014). New predictive characterization methods for accessing and using CWR diversity. Vis sammendrag

  Novel approaches to enhance characterization of plant genetic resources are being developed, as traditional phenotypic characterization techniques have shown to be insufficient to fully harness crop wild relative (CWR) and landrace diversity. These are genomics, transcriptomics, metabolomics, high-throughput phenotyping, as well as less resource intensive predictive characterization techniques. The latter build on the hypothesis that the environment influences gene flow and natural selection, and thus spatial genetic differentiation of organisms. CWR populations growing in a specific environment will possess a suite of adaptive traits shaped by selection pressures unique to these environments. Thus information about a CWR occurrence site can be used to approach the utilization of genetic resources in a more rational way. Two predictive characterization methods for CWR were developed within the PGR Secure project, using an agro-ecological approach for optimizing the search for populations and accessions with targeted adaptive traits: The ecogeographical filtering method combines spatial distribution of the target species with the ecogeographical identification of those environments that are likely to impose selection pressure for the selected trait. Edaphic, geophysic and bioclimatic variables most relevant for adaptation are identified and used together with ecogeographic land characterization maps to identify promising occurrences. The calibration method bases the criteria to filter accessions on existing evaluation data for the trait of interest. Ecogeographical data specific to the environment at collecting sites evaluated for the trait are used as input to identify existing relationships between trait and environment. This relationship is then used to calibrate a model through which other non-evaluated accessions can be assessed. The methods were applied to the four project genera, Avena, Beta, Brassica and Medicago to identify subsets of potentially interesting accessions or occurrences, investigating the following abiotic stress factors: aluminium toxicity for Avena, drought for Beta, drought and salinity for Brassica, and frost for Medicago. Keywords: predictive characterization, crop wild relatives, Avena, Beta, Brassica, Medicago, Conservation and use

• Baskauf, Steve; Ó Tuama, Éamonn; Endresen, Dag Terje Filip & Hagedorn, Gregor (2013). Report of the TDWG Vocabulary Management Task Group (VoMaG). Vis sammendrag

  This report constitutes the outcome of the TDWG Vocabulary Management Task Group (VoMaG). It consists of an introduction and four sections. The introduction describes the remit of VoMaG and the three task areas that emerged based on its charter, each of which is dealt with in separate sections. The first area (Section 2) relates to the status of the TDWG Ontology and its relationship to existing TDWG standards. It also examines the Darwin Core Namespace Policy as a means to maintain technical specification standards that define vocabularies, and provides recommendations for actions that would resolve several long-standing issues. The second area (Section 3 and Section 4) deals with the use of Semantic MediaWiki as a community platform for developing and maintaining vocabularies and with the NCBO BioPortal as a tool for sharing ontologies. It looks at the core features provided by MediaWiki, the enhancements provided by the Semantic MediaWiki extension, the implementation of the ViBRANT/GBIF terms wiki on Biowikifarm, and the advantages of BioPortal for ontologies (as opposed to vocabularies). The third area (Section 5) addresses the requirements for a framework for managing vocabularies, identifying the main components and a suggested workflow. Sections include recommendations for consideration by TDWG.

• Endresen, Dag Terje Filip (2013). A framework for managing vocabularies. Vis sammendrag

  Vocabularies are identified as one of three core components of the TDWG technical architecture - or to use the TDWG Technical Architecture Group (TAG) analogy, one of the legs of a “three-legged-stool”. The VoMaG report proposes best practices for governance and management of such vocabularies. The report adopts the general principle of distinguishing between “concept vocabularies” for declaring fundamental terminology and “application vocabularies” that combine and reuse terminology declared by the concept vocabularies for a specific application. This distinction is modelled after the practices established by the Darwin Core and Dublin Core and is motivated by the goal of supporting maximal reuse of terms declared by concept vocabularies which can be viewed as providing a pool of re-usable terms with clear and unambiguous definitions. TDWG should ensure that all concept vocabularies that are accepted into the TDWG terminology architecture are managed and developed by a group of experts in response to community feedback. New terms can be proposed for inclusion in one of the concept vocabularies or form the start of new concept vocabularies when a group of domain experts is ready to take responsibility for the task. These task groups should avoid declaring new terms for concepts that are already under stable maintenance by other groups outside of TDWG. Instead, such terms, if useful, should be imported into a TDWG concept vocabulary. We strongly recommend that all terms included in a concept vocabulary should have a dereferenceable identifier (URI) compatible with Semantic Web principles. When a term is reused in another vocabulary, this URI shall always be used to identify it. Terminology declared by concept vocabularies can be reused as property terms as well as class entities and controlled value elements.

• Endresen, Dag Terje Filip (2013). Darwin Core extension for germplasm data. Vis sammendrag

  Publishing germplasm information on plant genetic resources and their traits using the Darwin Core standard and the germplasm extension for genebanks. Presented during Session 2 of the 1st International e-Conference on Germplasm Data Interoperability (https://sites.google.com/site/germplasminteroperability/).

• Hagedorn, Gregor; Endresen, Dag Terje Filip & Ó Tuama, Éamonn (2013). Use of Semantic MediaWiki for vocabulary management (Hackathon). Vis sammendrag

  A vocabulary management system must support many tasks, among them, the definition, annotation, discussion, translation and export of terms or concepts in standard formats. In particular, it should be capable of importing externally defined vocabularies to enable their re-use. At the implementation level, a web-based platform is highly desirable to support remote collaboration. In meeting these requirements, the TDWG Vocabulary Management Task Group has proposed the use of MediaWiki[1], the wiki engine that underpins Wikipedia, in conjunction with the Semantic MediaWiki (SMW)[2] extension which allows data items to be tagged and queried within the wiki pages. In this hands-on, practical session we will explore the use and advantages of Semantic MediaWiki for vocabulary management. Participants are encouraged to test how SMW can support a use case of their own, e.g., for translating an existing vocabulary or developing a new one. While the main features of SMW will be briefly introduced in the preceding session (Vocabulary Management I), we encourage prospective participants to begin their own exploration of the system beforehand at http://terms.gbif.org. In this session, we will begin with a short (5-10 min) live demonstration of the main features of the SMW interface and then act as tutors, answering questions, etc., as participants try out the system on their own laptops. As places are limited, prospective participants should indicate their interest in participating in the session by emailing Gregor Hagedorn (gregor.hagedorn at mfn-berlin.de) before Tuesday 29th October. [1] http://www.mediawiki.org/ [2] http://semantic-mediawiki.org/

• Hanssen, Frank Ole; Heggberget, Tor Gravråk; Valland, Nils; Koch, Wouter; Moe, S. Jannicke; Karud, Jan; Sagen, Helge; Lid, Sjur Ringheim & Endresen, Dag Terje Filip (2013). LifeWatch Norge. Sluttrapport fra forprosjektet - NINA Rapport 928. NINA rapport. 928. Fulltekst i vitenarkiv. Vis sammendrag

  LifeWatch er et europeisk initiativ med langsiktig fokus på utvikling av vitenskapelig baserte e-løsninger for biodiversitets- og økosystemforskning. LifeWatch er en del av det europeiske veikartet for infrastrukturutvikling (ESFRI- European Strategy for Research Infrastructure), og kom inn på det norske veikartet for e-infrastrukturutvikling i 2010. NINA ble i 2008 invitert av Forskningsrådet til å følge utviklingen av det europeiske LifeWatch prosjektet (finansiert gjennom EU sitt 7. Rammeprogram for forskning og infrastrukturutbygging) og til å initiere et norsk LifeWatch forprosjekt. Forprosjektet ble formelt oppstartet i januar 2011 med finansiell støtte fra Forskningsrådet. Konsortiet har vært koordinert av NINA i tett samarbeid med Havforskningsinstituttet (HI), Artsdatabanken, Naturhistorisk Museum ved Universitetet i Oslo (norsk node i Global Biodiversity Information Facility) og Norsk institutt for vannforskning (NIVA). Forprosjektets hovedformål har vært å utrede muligheter og utfordringer knyttet til realisering av en norsk e-infrastruktur for fri deling av biodiversitets- og miljødata på tvers av institusjons- og landegrenser. Forprosjektet LifeWatch Norge er tett integrert med LifeWatch Europa gjennom NINA sin deltagelse i LifeWatch Preparatory Phase (2008-2010) og observatørstatus i styringsgruppen for LifeWatch Europa. Med finansiering fra NordForsk har LifeWatch konsortiene i Norge, Sverige, Danmark og Finland, i samarbeid med Islands Naturhistoriske Museum nylig startet opp et nordisk LifeWatch forprosjekt for å utrede muligheten for å realisere en nordisk e-forskningsinfrastruktur. På sikt vil et nordisk tyngdepunkt innen LifeWatch være strategisk viktig for de nordiske forskningsmiljøene. En nordisk overbygning vil kunne danne en felles grenseflate mellom nasjonale prosjekter og det europeiske nivå. Forprosjektet har kartlagt brukerbehov og metadata, samt foretatt en gjennomgang av de mest sentrale prinsipper, lover og retningslinjer knyttet til deling av offentlig finansierte miljø- og biodiversitetsdata. Videre er sentrale utfordringer, barrierer og rammevilkår for deling og tilgjengeliggjøring av offentlig finansierte forskningsdata drøftet. Utgangspunktet er at det i dag eksisterer store mengder relevante miljø- og biodiversitetsdata som av ulike årsaker er lite, eller overhodet ikke tilgjengelig for samfunnet. Konsortiet kommer på bakgrunn av dette med relevante anbefalinger og tiltak for realisering av en nasjonal e-infrastruktur for deling av offentlig finansierte miljø- og biodiversitetsdata. Dette omfatter utvikling av kontraktmaler, strategier og handlingsplaner for bedre dataforvaltning, kapasitetsbygging, utvikling av datamobiliseringsverktøy, samt evaluering av gjeldende rammevilkår og virkemiddelbruk rettet mot instituttsektoren. For å kunne realisere en operativ norsk LifeWatch e-infrastruktur må en tverrsektoriell forankring og organisering sikres. Vi anbefaler at nåværende LifeWatch-konsortium i samarbeid med Norges Forskningsråd arrangerer en interdepartemental LifeWatch konferanse innen Juni 2013 med relevante fagdepartement. Dette bør være første fase i utvidelsen av det nasjonale LifeWatch konsortiet, hvor hovedformålet bør være å klarlegge potensialet for merverdi og effektivisering for forskning og forvaltning. Forskningsrådet ønsker å styrke sin innsats for innovasjon i offentlig sektor og har derfor nylig startet arbeidet med strategiutvikling hvor grunntanken er å styrke kunnskapsflyten mellom forskning, næringsliv/industri og utdanningssektoren. Vi mener at en nasjonal LifeWatch e-forskningsinfrastruktur for miljø- og biodiversitetsdata generelt kan bidra til økt kvalitet, innovasjon og effektivitet innen forskningsmiljøene, samt økt anvendelse og politikkutforming innen næringsliv og offentlig forvaltning.

• Endresen, Dag Terje Filip & Ó Tuama, Éamonn (2012). Knowledge Organization System (KOS) for biodiversity information resources, GBIF KOS work programme. Vis sammendrag

  The Biodiversity Information Standards (TDWG) maintains standards for biodiversity data. Many of these standards have in the past been expressed using the XML schema language (XSD). With the advance of the semantic web there is a growing interest in TDWG for expressing vocabularies as RDF resources. The Global Biodiversity Information Facility (GBIF) has proposed a Vocabulary Management Task Group (VoMaG) [1] to develop best practices and guidelines for maintaining RDF vocabularies of terms and concepts from biodiversity informatics. One of the first tasks for the vocabulary management task group would be to evaluate software tools including the ISOcat [2] and the Semantic MediaWiki [3] for collaborative development and maintenance of vocabularies of fundamental concepts (declared here to be re-used by other resources). The simple knowledge organization system (SKOS) has been proposed for the declaration of the “concept vocabularies”. SKOS vocabularies can be expressed using the resource description framework (RDF). One of the uses for the concept vocabularies is as a repository of terms for the data sharing profiles in use by the GBIF network. These data sharing profiles include the Darwin Core "extensions" and the "vocabularies" of controlled values that are declared for some of the terms included in "extensions". The overall outline is that terms to be included in the "extensions" and in the "vocabularies" would be drawn from the fundamental concepts declared by the concept vocabularies. We have proposed as a best practice to separate the declaration of standalone concepts from the declaration of semantic relationships between these concepts. The rationale is partly that the user-friendly declaration of standalone concepts will maximize their reuse, and in part that we believe the ontologies declaring semantic relationships between concepts will always depend on the purpose and context of the ontology. We believe that declaring fundamental concepts as part of rich ontologies will cause an undesired limitation for the reuse of these concepts. The web ontology language (OWL) has been proposed for the declaration of relationships between concepts. OWL can be expressed using RDF. GBIF has published a resources repository [4] for biodiversity vocabularies. The NCBO BioPortal has been proposed as a more appropriate portal for the publication of biodiversity ontologies and vocabulary resources. The BioPortal provides tools for cross-mapping between vocabulary and ontology concepts. BioPortal will therefore provide an efficient platform to build interoperability between biodiversity information standards and the standards of the biomedical community. The Darwin Core standard of the biodiversity community was loaded to the BioPortal as a first test [5]. [1] http://community.gbif.org/pg/groups/21382/vocabulary-management/ [2] http://kos.gbif.org/isocat/interface/ [3] http://terms.gbif.org/wiki/ [4] http://rs.gbif.org/terms/ [5] http://bioportal.bioontology.org/projects/168

• Endresen, Dag Terje Filip; Ó Tuama, Éamonn & Remsen, David (2012). Knowledge Organization Systems in the GBIF work programme – recent developments.
• Gaiji, Samy; Dias, Sonia; Endresen, Dag Terje Filip & Franco, Tito (2008). Desarrollo de un sistema global de información a nivel de accesiones en apoyo al Tratado Internacional sobre los Recursos Fitogenéticos para la Alimentación y la Agricultura. Recursos Naturales y Ambiente.  ISSN 1659-1216.  53, s 126- 135 Vis sammendrag

  El desarrollo de un sistema de información global sobre recursos fitogenéticos en consonancia con el Artículo 17 del Tratado Internacional sobre los Recursos Fitogenéticos para la Alimentación y la Agricultura, podría avanzar con más rapidez, sobre todo para la comunidad de bancos de germoplas- ma, debido a la rápida evolución de las tecnolo- gías de la información. Los sistemas de informa- ción y portales de los bancos de germoplasma, como la Red de Información sobre Recursos Genéticos (SINGER) del Grupo Consultivo para la Investigación Agrícola Internacional (CGIAR) y el Catálogo Europeo de Investigación (EURISCO), podrían usarse como componentes básicos y esenciales de un sistema global. Sin embargo, para construir una infraestructura de información a gran escala que sirva de plataforma global para el acceso e intercambio de información a nivel de accesiones se requiere un diseño cuidadoso de la estrategia, la metodología y la tecnología. El objeti- vo de este artículo es demostrar la viabilidad de tal plataforma tomando como modelo la Infraestructura Mundial de Información sobre Biodiversidad (GBIF). Además, se proponen opciones prácticas para que los bancos de germoplasma en América Latina y el Caribe puedan unirse a esta iniciativa.

• Skovmand, Bent; Christensen, Lene Krøl; Endresen, Dag Terje Filip & Rasmussen, Morten C. (2006). Обеспечение и Документирование Рационализация генетических ресурсов растений сохранения и использования для улучшения. Agromeridian - Theoretical and Applied Agricultural Research Journal.  ISSN 1814-8417.  3(4), s 80- 85 Vis sammendrag

  Securing, Documenting and Rationalizing Plant Genetic Resources to Improve Conservation and Utilization

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