Tag: natural history

One Biodiversity Knowledge Hub to link them all: BiCIKL 2nd General Assembly

The FAIR Data Place – the key and final product of the partnership – is meant to provide scientists with all types of biodiversity data “at their fingertips”

The Horizon 2020 – funded project BiCIKL has reached its halfway stage and the partners gathered in Plovdiv (Bulgaria) from the 22nd to the 25th of October for the Second General Assembly, organised by Pensoft. 

The BiCIKL project will launch a new European community of key research infrastructures, researchers, citizen scientists and other stakeholders in the biodiversity and life sciences based on open science practices through access to data, tools and services.

BiCIKL’s goal is to create a centralised place to connect all key biodiversity data by interlinking 15 research infrastructures and their databases. The 3-year European Commission-supported initiative kicked off in 2021 and involves 14 key natural history institutions from 10 European countries.

BiCIKL is keeping pace as expected with 16 out of the 48 final deliverables already submitted, another 9 currently in progress/under review and due in a few days. Meanwhile, 21 out of the 48 milestones have been successfully achieved.

Prof. Lyubomir Penev (BiCIKL’s project coordinator Prof. Lyubomir Penev and CEO and founder of Pensoft) opens the 2nd General Assembly of BiCIKL in Plovdiv, Bulgaria.

The hybrid format of the meeting enabled a wider range of participants, which resulted in robust discussions on the next steps of the project, such as the implementation of additional technical features of the FAIR Data Place (FAIR being an abbreviation for Findable, Accessible, Interoperable and Reusable).

This FAIR Data Place online platform – the key and final product of the partnership and the BiCIKL initiative – is meant to provide scientists with all types of biodiversity data “at their fingertips”.

This data includes biodiversity information, such as detailed images, DNA, physiology and past studies concerning a specific species and its ‘relatives’, to name a few. Currently, the issue is that all those types of biodiversity data have so far been scattered across various databases, which in turn have been missing meaningful and efficient interconnectedness.

Additionally, the FAIR Data Place, developed within the BiCIKL project, is to give researchers access to plenty of training modules to guide them through the different services.

Halfway through the duration of BiCIKL, the project is at a turning point, where crucial discussions between the partners are playing a central role in the refinement of the FAIR Data Place design. Most importantly, they are tasked with ensuring that their technologies work efficiently with each other, in order to seamlessly exchange, update and share the biodiversity data every one of them is collecting and taking care of.

By Year 3 of the BiCIKL project, the partners agree, when those infrastructures and databases become efficiently interconnected to each other, scientists studying the Earth’s biodiversity across the world will be in a much better position to build on existing research and improve the way and the pace at which nature is being explored and understood. At the end of the day, knowledge is the stepping stone for the preservation of biodiversity and humankind itself.

“Needless to say, it’s an honour and a pleasure to be the coordinator of such an amazing team spanning as many as 14 partnering natural history and biodiversity research institutions from across Europe, but also involving many global long-year collaborators and their infrastructures, such as Wikidata, GBIF, TDWG, Catalogue of Life to name a few,”

said BiCIKL’s project coordinator Prof. Lyubomir Penev, CEO and founder of Pensoft.

“I see our meeting in Plovdiv as a practical demonstration of our eagerness and commitment to tackle the long-standing and technically complex challenge of breaking down the silos in the biodiversity data domain. It is time to start building freeways between all biodiversity data, across (digital) space, time and data types. After the last three days that we spent together in inspirational and productive discussions, I am as confident as ever that we are close to providing scientists with much more straightforward routes to not only generate more biodiversity data, but also build on the already existing knowledge to form new hypotheses and information ready to use by decision- and policy-makers. One cannot stress enough how important the role of biodiversity data is in preserving life on Earth. These data are indeed the groundwork for all that we know about the natural world”  

Prof. Lyubomir Penev added.
Christos Arvanitidis (CEO of LifeWatch ERIC) at the 2nd General Assembly of the BiCIKL project.

Christos Arvanitidis, CEO of LifeWatch ERIC, added:

“The point is: do we want an integrated structure or do we prefer federated structures? What are the pros and cons of the two options? It’s essential to keep the community united and allied because we can’t afford any information loss and the stakeholders should feel at home with the Project and the Biodiversity Knowledge Hub.”

Joe Miller, Executive Secretary and Director at GBIF, commented:

“We are a brand new community, and we are in the middle of the growth process. We would like to already have answers, but it’s good to have this kind of robust discussion to build on a good basis. We must find the best solution to have linkages between infrastructures and be able to maintain them in the future because the Biodiversity Knowledge Hub is the location to gather the community around best practices, data and guidelines on how to use the BiCIKL services… In order to engage even more partners to fill the eventual gaps in our knowledge.”

Joana Pauperio (biodiversity curator at EMBL-EBI) at the 2nd General Assembly of the BiCIKL project.

“BiCIKL is leading data infrastructure communities through some exciting and important developments”  

said Dr Guy Cochrane, Team Leader for Data Coordination and Archiving and Head of the European Nucleotide Archive at EMBL’s European Bioinformatics Institute (EMBL-EBI).

“In an era of biodiversity change and loss, leveraging scientific data fully will allow the world to catalogue what we have now, to track and understand how things are changing and to build the tools that we will use to conserve or remediate. The challenge is that the data come from many streams – molecular biology, taxonomy, natural history collections, biodiversity observation – that need to be connected and intersected to allow scientists and others to ask real questions about the data. In its first year, BiCIKL has made some key advances to rise to this challenge,”

he added.

Deborah Paul, Chair of the Biodiversity Information Standards – TDWG said:

“As a partner, we, at the Biodiversity Information Standards – TDWG, are very enthusiastic that our standards are implemented in BiCIKL and serve to link biodiversity data. We know that joining forces and working together is crucial to building efficient infrastructures and sharing knowledge.”

The project will go on with the first Round Table of experts in December and the publications of the projects who participated in the Open Call and will be founded at the beginning of the next year.

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Learn more about BiCIKL on the project’s website at: bicikl-project.eu

Follow BiCIKL Project on Twitter and Facebook. Join the conversation on Twitter at #BiCIKL_H2020.

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All BiCIKL project partners:

‘Who is in your database and why does it matter?’

The uncertainty about a person’s identity hampers research, hinders the discovery of expertise, and obstructs the ability to give attribution or credit for work performed. 

Collection discovery through disambiguation

Guest blog post by Sabine von Mering, Heather Rogers, Siobhan Leachman, David P. Shorthouse, Deborah Paul & Quentin Groom

Worldwide, natural history institutions house billions of physical objects in their collections, they create and maintain data about these items, and they share their data with aggregators such as the Global Biodiversity Information Facility (GBIF), the Integrated Digitized Biocollections (iDigBio), the Atlas of Living Australia (ALA), Genbank and the European Nucleotide Archive (ENA). 

Even though these data often include the names of the people who collected or identified each object, such statements may be ambiguous, as the names frequently lack any globally unique, machine-readable concept of their shared identity.

Despite the data being available online, barriers exist to effectively use the information about who collects or provides the expertise to identify the collection objects. People have similar names, change their name over the course of their lifetime (e.g. through marriage), or there may be variability introduced through the label transcription process itself (e.g. local look-up lists). 

As a result, researchers and collections staff often spend a lot of time deducing who is the person or people behind unknown collector strings while collating or tidying natural history data. The uncertainty about a person’s identity hampers research, hinders the discovery of expertise, and obstructs the ability to give attribution or credit for work performed. 

Disambiguation activities: the act of churning strings into verifiable things using all available evidence – need not be done in isolation. In addition to presenting a workflow on how to disambiguate people in collections, we also make the case that working in collaboration with colleagues and the general public presents new opportunities and introduces new efficiencies. There is tacit knowledge everywhere.

More often than not, data about people involved in biodiversity research are scattered across different digital platforms. However, with linking information sources to each other by using person identifiers, we can better trace the connections in these networks, so that we can weave a more interoperable narrative about every actor.

That said, inconsistent naming conventions or lack of adequate accreditation often frustrate the realization of this vision. This sliver of natural history could be churned to gold with modest improvements in long-term funding for human resources, adjustments to digital infrastructure, space for the physical objects themselves alongside their associated documents, and sufficient training on how to disambiguate people’s names.

“He aha te mea nui o te ao. He tāngata, he tāngata, he tāngata.”

“What is the most important thing in the world? It is people, it is people, it is people.”

(Māori proverb)

The process of properly disambiguating those who have contributed to natural history collections takes time. 

The disambiguation process involves the extra challenge of trying to deduce “who is who” for legacy data, compared to undertaking this activity for people alive today. Retrospective disambiguation can require considerable detective work, especially for scarcely known people or if the community has a different naming convention. Provided the results of this effort are well-communicated and openly shared, mercifully, it need only be done once.

At the core of our research is the question of how to solve the issue of assigning proper credit. 

In our recent Methods paper, we discuss several methods for this, as well as available routes for making records available online that include not only the names of people expressed as text, but additionally twinned with their unique, resolvable identifiers. 

Disambiguation is a cycle. Enrichment of the data feeds off itself leading to further disambiguation. As more names are disambiguated and more biographical data are accumulated, it becomes easier to disambiguate more names. 

First and foremost, we should maintain our own public biographical data by making full use of ORCID. In addition to preserving our own scientific legacy and that of the institutions that employ us, we have a responsibility to avoid generating unnecessary disambiguation work for others. 

For legacy data, where the people connected to the collections are deceased, Wikidata can be used to openly document rich bibliographic and demographic data, each statement with one or more verifiable references. Wikidata can also act as a bridge to link other sources of authority such as VIAF or ORCID identifiers. It has many tools and services to bulk import, export, and to query information, making it well-suited as a universal democratiser of information about people often walled-off in collection management systems (CMS). 

A network of the top twenty most used identifiers for biologists on Wikidata.

Once unique identifiers for people are integrated in collection management systems, these may be shared with the global collections and research community using the new Darwin Core terms, recordedByID or identifiedByID along with the well-known, yet text-based terms, recordedBy or identifiedBy. 

Approximately 120 datasets published through GBIF now make use of these identifier-based terms, which are additionally resolved in Bionomia every few weeks alongside co-curated attributions newly made there. This roundtrip of data – emerging as ambiguous strings of text from the source, affixed with resolvable identifiers elsewhere, absorbed into the source as new digital annotations, and then re-emerging with these fresh, identifier-based enhancements – is an exciting approach to co-manage collections data.

Round tripping. In Bionomia, people identifiers from Wikidata and ORCID are used to enrich data published via GBIF, thus linking natural history specimens to the world’s collectors.

Disambiguation work is particularly important in recognising contributors who have been historically marginalized. For example, gender bias in specimen data can be seen in the case of Wilmatte Porter Cockerell, a prolific collector of botanical, entomological and fossil specimens. Cockerell’s collections are often attributed to her husband as he was also a prolific collector and the two frequently collected together. 

On some labels, her identity is further obscured as she is simply recorded as “& wife” (see example on GBIF). Since Wilmatte Cockerell was her husband’s second wife, it can take some effort to confirm if a specimen can be attributed to her and not her husband’s first wife, who was also involved in collecting specimens. By ensuring that Cockerell is disambiguated and her contributions are appropriately attributed, the impact of her work becomes more visible enabling her work to be properly and fairly credited.

Thus, disambiguation work helps to not only give credit where credit is due, thereby making data about people and their biodiversity collections more findable, but it also creates an inclusive and representative narrative of the landscape of people involved with scientific knowledge creation, identification, and preservation. 

A future – once thought to be a dream – where the complete scientific output of a person is connected as Linked Open Data (LOD) is now. 

Both the tools and infrastructure are at our disposal and the demand is palpable. All institutions can contribute to this movement by sharing data that include unique identifiers for the people in their collections. We recommend that institutions develop a strategy, perhaps starting with employees and curatorial staff, people of local significance, or those who have been marginalized, and to additionally capitalize on existing disambiguation activities elsewhere. This will have local utility and will make a significant, long-term impact. 

The more we participate in these activities, the greater chance we will uncover positive feedback loops, which will act to lighten the workload for all involved, including our future selves!

The disambiguation of people in collections is an ongoing process, but it becomes easier with practice. We also encourage collections staff to consider modifying their existing workflows and policies to include identifiers for people at the outset, when new data are generated or when new specimens are acquired. 

There is more work required at the global level to define, update, and ratify standards and best practices to help accelerate data exchange or roundtrips of this information; there is room for all contributions. Thankfully, there is a diverse, welcoming, energetic, and international community involved in these activities. 

We see a bright future for you, our collections, and our research products – well within reach – when the identities of people play a pivotal role in the construction of a knowledge graph of life.

You would like to participate and need support getting disambiguation of your collection started? Please contact our TDWG People in Biodiversity Data Task Group.

A good start is also to check Bionomia to find out what metrics exist now for your institution or collection and affiliated people.

The next steps for collections: 7 objectives that can help to disambiguate your institutions’ collection:

1. Promote the use of person identifiers in local, national or international outreach, publishing and research activities

2. Increase the number of collection management systems that use person identifiers

3. Increase the number of living collectors registered and using an ORCID identifier when contributing to collections

4. Undertake disambiguation in the national languages of many countries

5. Increase the number of identified people on Wikidata linked to collections

6. Increase the number of people in collections with expertise in person disambiguation

7. Collaborate towards an exchange standard for attribution data

A real example of how a name string is disambiguated and the steps taken in documenting it. Wikidata item of Jean-André Soulié

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Methods publication:

Groom Q, Bräuchler C, Cubey RWN, Dillen M, Huybrechts P, Kearney N, Klazenga N, Leachman S, Paul DL, Rogers H, Santos J, Shorthouse DP, Vaughan A, von Mering S, Haston EM (2022) The disambiguation of people names in biological collections. Biodiversity Data Journal 10: e86089. https://doi.org/10.3897/BDJ.10.e86089

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Volunteer “community scientists” do a pretty darn good job generating usable data

When museum-goers did a community science activity in an exhibit at the Field Museum (USA), the data they produced were largely accurate.

Left: Cuong Pham, Jimmy Crigler, and Joshua Torres working on a community science platform in an exhibit at the Field Museum (photo by Melanie Pivarski, Roosevelt University).
Right: The microscopic leaves of a liverwort, a primitive plant that helps scientists track climate change (photo by Lauren Johnson, Field Museum).
Original publication by the Field Museum

Ask any scientist — for every “Eureka!” moment, there’s a lot of less-than-glamorous work behind the scenes. Making discoveries about everything from a new species of dinosaur to insights about climate change entails some slogging through seemingly endless data and measurements that can be mind-numbing in large doses.

Community science shares the burden with volunteers who help out, for even just a few minutes, on collecting data and putting it into a format that scientists can use. But the question remains how useful these data actually are for scientists. 

A new study, authored by a combination of high school students, undergrads and grad students, and professional scientists showed that when museum-goers did a community science activity in an exhibit, the data they produced were largely accurate, supporting the argument that community science is a viable way to tackle big research projects.

“It was surprising how all age groups from young children, families, youth, and adults were able to generate high-quality taxonomic data sets, making observations and preparing measurements, and at the same time empowering community scientists through authentic contributions to science,”

says Matt von Konrat (Field Museum, USA), an author of the paper in the journal Research Ideas and Outcomes (RIO Journal) and the head of plant collections at Chicago’s Field Museum.

“This study demonstrates the wonderful scientific outcomes that occur when an entire community comes together,”

says Melanie Pivarski, an associate professor of mathematics at Roosevelt University (USA) and the study’s lead author.

“We were able to combine a small piece of the Field Museum’s vast collections, their scientific knowledge and exhibit creation expertise, the observational skills of biology interns at Northeastern Illinois University (USA), led by our collaborator Tom Campbell, and our Roosevelt University student’s data science expertise. The creation of this set of high-quality data was a true community effort!” 

The study focuses on an activity in an exhibition at the Field Museum, in which visitors could partake in a community science project. In the community science activity, museumgoers used a large digital touchscreen to measure the microscopic leaves photographs of plants called liverworts. 

These tiny plants, the size of an eyelash, are sensitive to climate change, and they can act like a canary in a coal mine to let scientists know about how climate change is affecting a region. It’s helpful for scientists to know what kinds of liverworts are present in an area, but since the plants are so tiny, it’s hard to tell them apart. The sizes of their leaves (or rather, lobes — these are some of the most ancient land plants on Earth, and they evolved before true leaves had formed) can hint at their species. But it would take ages for any one scientist to measure all the leaves of the specimens in the Field’s collection. Enter the community scientists.

“Drawing a fine line to measure the lobe of a liverwort for a few hours can be mentally strenuous, so it’s great to have community scientists take a few minutes out of their day using fresh eyes to help measure a plant leaf. A few community scientists who’ve helped with classifying acknowledged how exciting it is knowing they are playing a helping hand in scientific discovery,”  

says Heaven Wade, a research assistant at the Field Museum who began working on the MicroPlants project as an undergraduate intern.

Community scientists using the digital platform measured thousands of microscopic liverwort leaves over the course of two years.

“At the beginning, we needed to find a way to sort the high quality measurements out from the rest. We didn’t know if there would be kids drawing pictures on the touchscreen instead of measuring leaves or if they’d be able to follow the tutorial as well as the adults did. We also needed to be able to automate a method to determine the accuracy of these higher quality measurements,”

says Pivarski.

To answer these questions, Pivarski worked with her students at Roosevelt University to analyze the data. They compared measurements taken by the community scientists with measurements done by experts on a couple “test” lobes; based on that proof of concept, they went on to analyze the thousands of other leaf measurements. The results were surprising.

“We were amazed at how wonderfully children did at this task; it was counter to our initial expectations. The majority of measurements were high quality. This allowed my students to create an automated process that produced an accurate set of MicroPlant measurements from the larger dataset,”

says Pivarski.

The researchers say that the study supports the argument that community science is valuable not just as a teaching tool to get people interested in science, but as a valid means of data collection.

“Biological collections are uniquely poised to inform the stewardship of life on Earth in a time of cataclysmic biodiversity loss, yet efforts to fully leverage collections are impeded by a lack of trained taxonomists. Crowd-sourced data collection projects like these have the potential to greatly accelerate biodiversity discovery and documentation from digital images of scientific specimens,”

says von Konrat.
Research article:

Pivarski M, von Konrat M, Campbell T, Qazi-Lampert AT, Trouille L, Wade H, Davis A, Aburahmeh S, Aguilar J, Alb C, Alferes K, Barker E, Bitikofer K, Boulware KJ, Bruton C, Cao S, Corona Jr. A, Christian C, Demiri K, Evans D, Evans NM, Flavin C, Gillis J, Gogol V, Heublein E, Huang E, Hutchinson J, Jackson C, Jackson OR, Johnson L, Kirihara M, Kivarkis H, Kowalczyk A, Labontu A, Levi B, Lyu I, Martin-Eberhardt S, Mata G, Martinec JL, McDonald B, Mira M, Nguyen M, Nguyen P, Nolimal S, Reese V, Ritchie W, Rodriguez J, Rodriguez Y, Shuler J, Silvestre J, Simpson G, Somarriba G, Ssozi R, Suwa T, Syring C, Thirthamattur N, Thompson K, Vaughn C, Viramontes MR, Wong CS, Wszolek L (2022) People-Powered Research and Experiential Learning: Unravelling Hidden Biodiversity. Research Ideas and Outcomes 8: e83853. https://doi.org/10.3897/rio.8.e83853

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Scientists conceptualize a species ‘stock market’ to put a price tag on actions posing risks to biodiversity

“…the most realistic and tangible way out of the looming biodiversity crisis is to put a price tag on species and thereby a cost to actions that compromise them.”

So far, science has described more than 2 million species, and millions more await discovery. While species have value in themselves, many also deliver important ecosystem services to humanity, such as insects that pollinate our crops. 

Meanwhile, as we lack a standardized system to quantify the value of different species, it is too easy to jump to the conclusion that they are practically worthless. As a result, humanity has been quick to justify actions that diminish populations and even imperil biodiversity at large.

In a study, published in the scholarly open-science journal Research Ideas and Outcomes, a team of Estonian and Swedish scientists propose to formalize the value of all species through a conceptual species ‘stock market’ (SSM). Much like the regular stock market, the SSM is to act as a unified basis for instantaneous valuation of all items in its holdings.

However, other aspects of the SSM would be starkly different from the regular stock market. Ownership, transactions, and trading will take new forms. Indeed, species have no owners, and ‘trade’ would not be about transfer of ownership rights among shareholders. Instead, the concept of ‘selling’ would comprise processes that erase species from some specific area – such as war, deforestation, or pollution.

“The SSM would be able to put a price tag on such transactions, and the price could be thought of as an invoice that the seller needs to settle in some way that benefits global biodiversity,”

explains the study’s lead author Prof. Urmas Kõljalg (University of Tartu, Estonia).

Conversely, taking some action that benefits biodiversity – as estimated through individuals of species – would be akin to buying on the species stock market. Buying, too, has a price tag on it, but this price should probably be thought of in goodwill terms. Here, ‘money’ represents an investment towards increased biodiversity. 

“By rooting such actions in a unified valuation system it is hoped that goodwill actions will become increasingly difficult to dodge and dismiss,”

adds Kõljalg.

Interestingly, the SSM revolves around the notion of digital species. These are representations of described and undescribed species concluded to exist based on DNA sequences and elaborated by including all we know about their habitat, ecology, distribution, interactions with other species, and functional traits. 

For the SSM to function as described, those DNA sequences and metadata need to be sourced from global scientific and societal resources, including natural history collections, sequence databases, and life science data portals. Digital species might be managed further by incorporating data records of non-sequenced individuals, notably observations, older material in collections, and data from publications.

The study proposes that the SSM is orchestrated by the international associations of taxonomists and economists. 

“Non-trivial complications are foreseen when implementing the SSM in practice, but we argue that the most realistic and tangible way out of the looming biodiversity crisis is to put a price tag on species and thereby a cost to actions that compromise them,”

says Kõljalg.

“No human being will make direct monetary profit out of the SSM, and yet it’s all Earth’s inhabitants – including humans – that could benefit from its pointers.”

Original source

Kõljalg U, Nilsson RH, Jansson AT, Zirk A, Abarenkov K (2022) A price tag on species. Research Ideas and Outcomes 8: e86741. https://doi.org/10.3897/rio.8.e86741

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Call for Expression of Interest for biodiversity data-related scientific projects from BiCIKL

The purpose of this call is to solicit, select and implement four to six biodiversity data-related scientific projects that will make use of the added value services developed by the leading Research Infrastructures that make the BiCIKL project.

The BiCIKL project invites submissions of Expression of Interest (EoI) to the First BiCIKL Open Call for projects. The purpose of this call is to solicit, select and implement four to six biodiversity data-related scientific projects that will make use of the added value services developed by the leading Research Infrastructures that make the BiCIKL project.

By opening this call, BiCIKL aims to better understand how it could support scientific questions that arise from across the biodiversity world in the future, while addressing specific scientific or technical biodiversity data challenges presented by the applicants.

We need and want to assess real-world problems and make the best possible use of our data and technical capabilities. This will greatly assist in defining the long-term development goals of the participating Research Infrastructures and improve the way they can technically and operationally work together to deliver greater scientific value.

explain the project partners.

The BiCIKL project – a Horizon 2020-funded project involving 14 European institutions, representing major global players in biodiversity research and natural history, and coordinated by Pensoft – establishes a European starting community of key research infrastructures, researchers, citizen scientists and other biodiversity and life sciences stakeholders based on open science practices through access to data, tools and services.

Find more about the Call and submit your Expression of Interest

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Image recognition to the rescue of natural history museums by enabling curators to identify specimens on the fly

New Research Idea, published in RIO Journal presents a promising machine-learning ecosystem to unite experts around the world and make up for lacking taxonomic expertise.

In their Research Idea, published in Research Ideas and Outcomes (RIO Journal), Swiss-Dutch research team present a promising machine-learning ecosystem to unite experts around the world and make up for lacking expert staff

Guest blog post by Luc Willemse, Senior collection manager at Naturalis Biodiversity Centre (Leiden, Netherlands)

Imagine the workday of a curator in a national natural history museum. Having spent several decades learning about a specific subgroup of grasshoppers, that person is now busy working on the identification and organisation of the holdings of the institution. To do this, the curator needs to study in detail a huge number of undescribed grasshoppers collected from all sorts of habitats around the world. 

The problem here, however, is that a curator at a smaller natural history institution – is usually responsible for all insects kept at the museum, ranging from butterflies to beetles, flies and so on. In total, we know of around 1 million described insect species worldwide. Meanwhile, another 3,000 are being added each year, while many more are redescribed, as a result of further study and new discoveries. Becoming a specialist for grasshoppers was already a laborious activity that took decades, how about knowing all insects of the world? That’s simply impossible. 

Then, how could we expect from one person to sort and update all collections at a museum: an activity that is the cornerstone of biodiversity research? A part of the solution, hiring and training additional staff, is costly and time-consuming, especially when we know that experts on certain species groups are already scarce on a global scale. 

We believe that automated image recognition holds the key to reliable and sustainable practises at natural history institutions. 

Today, image recognition tools integrated in mobile apps are already being used even by citizen scientists to identify plants and animals in the field. Based on an image taken by a smartphone, those tools identify specimens on the fly and estimate the accuracy of their results. What’s more is the fact that those identifications have proven to be almost as accurate as those done by humans. This gives us hope that we could help curators at museums worldwide take better and more timely care of the collections they are responsible for. 

However, specimen identification for the use of natural history institutions is still much more complex than the tools used in the field. After all, the information they store and should be able to provide is meant to serve as a knowledge hub for educational and reference purposes for present and future generations of researchers around the globe.

This is why we propose a sustainable system where images, knowledge, trained recognition models and tools are exchanged between institutes, and where an international collaboration between museums from all sizes is crucial. The aim is to have a system that will benefit the entire community of natural history collections in providing further access to their invaluable collections. 

We propose four elements to this system: 

  1. A central library of already trained image recognition models (algorithms) needs to be created. It will be openly accessible, so any other institute can profit from models trained by others.
Mock-up of a Central Library of Algorithms.
  1. A central library of datasets accessing images of collection specimens that have recently been identified by experts. This will provide an indispensable source of images for training new algorithms.
Mock-up of a Central Library of Datasets.
  1. A digital workbench that provides an easy-to-use interface for inexperienced users to customise the algorithms and datasets to the particular needs in their own collections. 
  2. As the entire system depends on international collaboration as well as sharing of algorithms and datasets, a user forum is essential to discuss issues, coordinate, evaluate, test or implement novel technologies.

How would this work on a daily basis for curators? We provide two examples of use cases.

First, let’s zoom in to a case where a curator needs to identify a box of insects, for example bush crickets, to a lower taxonomic level. Here, he/she would take an image of the box and split it into segments of individual specimens. Then, image recognition will identify the bush crickets to a lower taxonomic level. The result, which we present in the table below – will be used to update object-level registration or to physically rearrange specimens into more accurate boxes. This entire step can also be done by non-specialist staff. 

Mock-up of box with grasshoppers mentioned in the above table

Results of automated image recognition identify specimens to a lower taxonomic level.

Another example is to incorporate image recognition tools into digitisation processes that include imaging specimens. In this case, image recognition tools can be used on the fly to check or confirm the identifications and thus improve data quality.

Mock-up of an interface for automated taxon identification. 

Using image recognition tools to identify specimens in museum collections is likely to become common practice in the future. It is a technical tool that will enable the community to share available taxonomic expertise. 

Using image recognition tools creates the possibility to identify species groups for which there is very limited to none in-house expertise. Such practises would substantially reduce costs and time spent per treated item. 

Image recognition applications carry metadata like version numbers and/or datasets used for training. Additionally, such an approach would make identification more transparent than the one carried out by humans whose expertise is, by design, in no way standardised or transparent.

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Research publication:

Greeff M, Caspers M, Kalkman V, Willemse L, Sunderland BD, Bánki O, Hogeweg L (2022) Sharing taxonomic expertise between natural history collections using image recognition. Research Ideas and Outcomes 8: e79187. https://doi.org/10.3897/rio.8.e79187

Natural History Museum of Berlin’s journal Fossil Record started publishing on ARPHA Platform

Fossil Record – the paleontological scholarly journal of the Natural History Museum of Berlin (Museum für Naturkunde Berlin) published its first articles after moving to the academic publisher Pensoft and its publishing platform ARPHA Platform in late 2021. The renowned scientific outlet – launched in 1998 – joined two other historical journals owned by the Museum: Deutsche Entomologische Zeitschrift and Zoosystematics and Evolution, which moved to Pensoft back in 2014.

Fossil Record – the paleontological scholarly journal of the Natural History Museum of Berlin (Museum für Naturkunde Berlin) published its first articles after moving to the academic publisher Pensoft and its publishing platform ARPHA in late 2021. The renowned scientific outlet – launched in 1998 – joined two other historical journals owned by the Museum: Deutsche Entomologische Zeitschrift and Zoosystematics and Evolution, which moved to Pensoft back in 2014.

Published in two issues a year, the open-access scientific outlet covers research from all areas of palaeontology, including the taxonomy and systematics of fossil organisms, biostratigraphy, palaeoecology, and evolution. It deals with all taxonomic groups, including invertebrates, microfossils, plants, and vertebrates.

As a result of the move to ARPHA, Fossil Record utilises the whole package of ARPHA Platform’s services, including its fast-track, end-to-end publishing module, designed to appeal to readers, authors, reviewers and editors alike. A major advantage is that the whole editorial process, starting from the submission of a manuscript and continuing into peer review, editing, publication, dissemination, archiving and hosting, happens within the online ecosystem of ARPHA. 

As soon as they are published, the articles in Fossil Record are available in three formats: PDF, machine-readable JATS XML and semantically enriched HTML for better and mobile-friendly reader experience. 

The publications are equipped with real-time metrics on both article and sub-article level that allow easy access to the number of visitors, views and downloads for every article and each of it’s figures, tables or supplementary materials. In their turn, the semantic enhancements do not only allow for easy navigation throughout the text and quick access to cited literature and the article’s own citations, but also tag each taxon that appears in the paper to provide links to further information concerning its occurrences, genomics, nomenclature, treatments and more as available from various databases.      

The first five papers – now available on the brand new journal website powered by ARPHA – already demonstrate the breadth of topics covered by Fossil Record, including systematics, paleobiogeography, palaeodiversity and morphology, as well as the international appeal of the scholarly outlet. The articles are co-authored by collaborative research teams representing ten countries and spanning three continents: Europe, Asia and Africa.

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About the Natural History Museum of Berlin:

The “Museum für Naturkunde – Leibniz Institute for Evolution and Biodiversity Science” is an integrated research museum within the Leibniz Association. It is one of the most important research institutions worldwide in the areas of biological and geological evolution and biodiversity.

The Museum’s mission is to discover and describe life and earth – with people, through dialogue. As an excellent research museum and innovative communication platform, it wants to engage with and influence the scientific and societal discourse about the future of our planet, worldwide. Its vision, strategy and structure make the museum an excellent research museum. The Natural History Museum of Berlin has research partners in Berlin, Germany and approximately 60 other countries. Over 700,000 visitors per year as well as steadily increasing participation in educational and other events show that the Museum has become an innovative communication centre that helps shape the scientific and social dialogue about the future of our earth. 

Digitising the Natural History Museum London’s entire collection could contribute over £2 billion to the global economy

In a world first, the Natural History Museum, London, has collaborated with economic consultants, Frontier Economics Ltd, to explore the economic and societal value of digitising natural history collections and concluded that digitisation has the potential to see a seven to tenfold return on investment. Whilst significant progress is already being made at the Museum, additional investment is needed in order to unlock the full potential of the Museum’s vast collections – more than 80 million objects. The project’s report is published in the open science scientific journal Research Ideas and Outcomes (RIO Journal).

One of the Museum’s digitisers imaging a butterfly to join the 4.93 million specimens already available online. 
© The Trustees of the Natural History Museum, London

The societal benefits of digitising natural history collections extends to global advancements in food security, biodiversity conservation, medicine discovery, minerals exploration, and beyond. Brand new, rigorous economic report predicts investing in digitising natural history museum collections could also result in a tenfold return. The Natural History Museum, London, has so far made over 4.9 million digitised specimens available freely online – over 28 billion records have been downloaded over 429,000 download events over the past six years. 

Digitisation at the Natural History Museum, London 

Digitisation is the process of creating and sharing the data associated with Museum specimens. To digitise a specimen, all its related information is added to an online database. This typically includes where and when it was collected and who found it, and can include photographs, scans and other molecular data if available. Natural history collections are a unique record of biodiversity dating back hundreds of years, and geodiversity dating back millennia. Creating and sharing data this way enables science that would have otherwise been impossible, and we accelerate the rate at which important discoveries are made from our collections.  

The Natural History Museum’s collection of 80 million items is one of the largest and most historically and geographically diverse in the world. By unlocking the collection online, the Museum provides free and open access for global researchers, scientists, artists and more. Since 2015, the Museum has made 4.9 million specimens available on the Museum’s Data Portal, which have seen more than 28 billion downloads over 427,000 download events. 

This means the Museum has digitised  about 6% of its collections to date. Because digitisation is expensive, costing tens of millions of pounds, it is difficult to make a case for further investment without better understanding the value of this digitisation and its benefits. 

In 2021, the Museum decided to explore the economic impacts of collections data in more depth, and commissioned Frontier Economics to undertake modelling, resulting in this project report, now made publicly available in the open-science journal Research Ideas and Outcomes (RIO Journal), and confirming benefits in excess of £2 billion over 30 years. While the methods in this report are relevant to collections globally, this modelling focuses on benefits to the UK, and is intended to support the Museum’s own digitisation work, as well as a current scoping study funded by the Arts & Humanities Research Council about the case for digitising all UK natural science collections as a research infrastructure.

“Sharing data from our collections can transform scientific research and help find solutions for nature and from nature. Our digitised collections have helped establish the baseline plant biodiversity in the Amazon, find wheat crops that are more resilient to climate change and support research into potential zoonotic origins of Covid-19. The research that comes from sharing our specimens has immense potential to transform our world and help both people and the planet thrive,“

says Helen Hardy, Science Digital Programme Manager at the Natural History Museum.

How digitisation impacts scientific research?

The data from museum collections accelerates scientific research, which in turn creates benefits for society and the economy across a wide range of sectors. Frontier Economics Ltd have looked at the impact of collections data in five of these sectors: biodiversity conservation, invasive species, medicines discovery, agricultural research and development and mineral exploration. 

“The Natural History Museum’s collection is a real treasure trove which, if made easily accessible to scientists all over the world through digitisation, has the potential to unlock ground-breaking research in any number of areas. Predicting exactly how the data will be used in future is clearly very uncertain. We have looked at the potential value that new research could create in just five areas focussing on a relatively narrow set of outcomes. We find that the value at stake is extremely large, running into billions,”

says Dan Popov, Economist at Frontier Economics Ltd.

The new analyses attempt to estimate the economic value of these benefits using a range of approaches, with the results in broad agreement that the benefits of digitisation are at least ten times greater than the costs. This represents a compelling case for investment in museum digital infrastructure without which the many benefits will not be realised.

“This new analysis shows that the data locked up in our collections has significant societal and economic value, but we need investment to help us release it,“

adds Professor Ken Norris, Head of the Life Sciences Department at the Natural History Museum.

Other benefits could include improvements to the resilience of agricultural crops by better understanding their wild relatives, research into invasive species which can cause significant damage to ecosystems and crops, and improving the accuracy of mining.  

Finally, there are other impacts that such work could have on how science is conducted itself. The very act of digitising specimens means that researchers anywhere on the planet can access these collections, saving time and money that may have been spent as scientists travelled to see specific objects.

The value of research enabled by digitisation of natural history collections can be estimated by looking at specific areas where the Museum’s collections contribute towards scientific research and subsequently impact the wider economy. 
© Frontier Economics Ltd.

Original source: 

Popov D, Roychoudhury P, Hardy H, Livermore L, Norris K (2021) The Value of Digitising Natural History Collections. Research Ideas and Outcomes 7: e78844. https://doi.org/10.3897/rio.7.e78844

New BiCIKL project to build a freeway between pieces of biodiversity knowledge

Within Biodiversity Community Integrated Knowledge Library (BiCIKL), 14 key research and natural history institutions commit to link infrastructures and technologies to provide flawless access to biodiversity data.

In a recently started Horizon 2020-funded project, 14 European institutions from 10 countries, representing both the continent’s and global key players in biodiversity research and natural history, deploy and improve their own and partnering infrastructures to bridge gaps between each other’s biodiversity data types and classes. By linking their technologies, they are set to provide flawless access to data across all stages of the research cycle.

Three years in, BiCIKL (abbreviation for Biodiversity Community Integrated Knowledge Library) will have created the first-of-its-kind Biodiversity Knowledge Hub, where a researcher will be able to retrieve a full set of linked and open biodiversity data, thereby accessing the complete story behind an organism of interest: its name, genetics, occurrences, natural history, as well as authors and publications mentioning any of those.

Ultimately, the project’s products will solidify Open Science and FAIR (Findable, Accessible, Interoperable and Reusable) data practices by empowering and streamlining biodiversity research.

Together, the project partners will redesign the way biodiversity data is found, linked, integrated and re-used across the research cycle. By the end of the project, BiCIKL will provide the community with a more transparent, trustworthy and efficient highly automated research ecosystem, allowing for scientists to access, explore and put into further use a wide range of data with only a few clicks.

“In recent years, we’ve made huge progress on how biodiversity data is located, accessed, shared, extracted and preserved, thanks to a vast array of digital platforms, tools and projects looking after the different types of data, such as natural history specimens, species descriptions, images, occurrence records and genomics data, to name a few. However, we’re still missing an interconnected and user-friendly environment to pull all those pieces of knowledge together. Within BiCIKL, we all agree that it’s only after we puzzle out how to best bridge our existing infrastructures and the information they are continuously sourcing that future researchers will be able to realise their full potential,” 

explains BiCIKL’s project coordinator Prof. Lyubomir Penev, CEO and founder of Pensoft, a scholarly publisher and technology provider company.

Continuously fed with data sourced by the partnering institutions and their infrastructures, BiCIKL’s key final output: the Biodiversity Knowledge Hub, is set to persist with time long after the project has concluded. On the contrary, by accelerating biodiversity research that builds on – rather than duplicates – existing knowledge, it will in fact be providing access to exponentially growing contextualised biodiversity data.

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Learn more about BiCIKL on the project’s website at: bicikl-project.eu

Follow BiCIKL Project on Twitter and Facebook. Join the conversation on Twitter at #BiCIKL_H2020.

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The project partners:

48 years of Australian collecting trips in one data package

From 1973 to 2020, Australian zoologist Dr Robert Mesibov kept careful records of the “where” and “when” of his plant and invertebrate collecting trips. Now, he has made those valuable biodiversity data freely and easily accessible via the Zenodo open-data repository, so that future researchers can rely on this “authority file” when using museum specimens collected from those events in their own studies. The new dataset is described in the open-access, peer-reviewed Biodiversity Data Journal.

While checking museum records, Dr Robert Mesibov found there were occasional errors in the dates and places for specimens he had collected many years before. He was not surprised.

“It’s easy to make mistakes when entering data on a computer from paper specimen labels”, said Mesibov. “I also found specimen records that said I was the collector, but I know I wasn’t!”

One solution to this problem was what librarians and others have long called an “authority file”.

“It’s an authoritative reference, in this case with the correct details of where I collected and when”, he explained.

“I kept records of almost all my collecting trips from 1973 until I retired from field work in 2020. The earliest records were on paper, but I began storing the key details in digital form in the 1990s.”

The 48-year record has now been made publicly available via the Zenodo open-data repository after conversion to the Darwin Core data format, which is widely used for sharing biodiversity information. With this “authority file”, described in detail in the open-access, peer-reviewed Biodiversity Data Journal, future researchers will be able to rely on sound, interoperable and easy to access data, when using those museum specimens in their own studies, instead of repeating and further spreading unintentional errors.

“There are 3829 collecting events in the authority file”, said Mesibov, “from six Australian states and territories. For each collecting event there are geospatial and date details, plus notes on the collection.”

Mesibov hopes the authority file will be used by museums to correct errors in their catalogues.

“It should also save museums a fair bit of work in future”, he explained. “No need to transcribe details on specimen labels into digital form in a database, because the details are already in digital form in the authority file.”

Mesibov points out that in the 19th and 20th centuries, lists of collecting events were often included in the reports of major scientific expeditions.

“Those lists were authority files, but in the pre-digital days it was probably just as easy to copy collection data from specimen labels.”

“In the 21st century there’s a big push to digitise museum specimen collections”, he said. “Museum databases often have lookup tables with scientific names and the names of collectors. These lookup tables save data entry time and help to avoid errors in digitising.”

“Authority files for collecting events are the next logical step,” said Mesibov. “They can be used as lookup tables for all the important details of individual collections: where, when, by whom and how.”

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Research paper:

Mesibov RE (2021) An Australian collector’s authority file, 1973–2020. Biodiversity Data Journal 9: e70463. https://doi.org/10.3897/BDJ.9.e70463

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Robert Mesibov’s webpage: https://www.datafix.com.au/mesibov.html

Robert Mesibov’s ORCID page: https://orcid.org/0000-0003-3466-5038