Amoebae of the genus Leptomyxa have variable morphologies and can only be reliably identified using molecular data. However, species distinction based on the 18S rRNA gene sequence is difficult due to the very low level of sequence divergence among morphologically different species. The database for other genes is much smaller, and genomic data on Leptomyxa is almost absent. In this study, we describe two new terrestrial species of the genus Leptomyxa isolated from Northwestern Russia, Leptomyxa botanica n. sp. and Leptomyxa monrepos n. sp. Both species easily adopt an expanded fan-shaped form and have a complex structure of the nucleolar material. Phylogenetic analyses show a derived status of these two species. They form a clade with Leptomyxa valladaresi. Our tree confirms that the 18S rRNA gene sequences of Leptomyxa species are split into two large clades. The morphological synapomorphies of these clades are not obvious. This analysis is complicated by the lack of reliable morphological data on many sequenced strains and probable misidentification of some isolates.

The extension of biology with a more data-centric component offers new opportunities for discovery. To enable investigations that rely on third-party data, the infrastructure that retains data and allows their re-use should, arguably, enable transactions that relate to any and all biological processes. The assembly of such a service-oriented and enabling infrastructure is challenging. Part of the challenge is to factor in the scope and scale of biological processes. From this foundation can emerge an estimate of the number of discipline-specific centres which will gather data in their given area of interest and prepare them for a path that will lead to trusted, persistent data repositories which will make fit-for-purpose data available for re-use. A simple model is presented for the scope and scale of life sciences. It can accommodate all known processes conducted by or caused by any and all organisms. It is depicted on a grid, the axes of which are (x) the durations of the processes and (y) the sizes of participants involved. Both axes are presented in log10 scales, and the grid is divided into decadal blocks with ten fold increments of time and size. Processes range in duration from 10-17 seconds to 3.5 billion years or more, and the sizes of participants range from 10-15 to 1.3 107 metres. Examples are given to illustrate the diversity of biological processes and their often inexact character. About half of the blocks within the grid do not contain known processes. The blocks that include biological processes amount to ‘Nature’s envelope’, a valuable rhetorical device onto which subdisciplines and existing initiatives may be mapped, and from which can be derived some key requirements for a comprehensive data infrastructure.

The majority of biodiversity data is not findable, accessible, integratable, or reusable, partially because of a lack of metadata. Taxonomic names as metadata are useful, but not sufficient because these names may be updated as knowledge progresses. There is a great need for tools and services that can scale up to create and maintain metadata for the vast and varied long tail of dark data. Here we examine the use of GNFinder as a tool for creating and maintaining metadata using mentions of taxa in text from publications corresponding to data sets deposited in Dryad. Most studied taxa were mentioned in the publication using a properly formed scientific name, with a few exceptions for studies that only used vernacular names and only mentioned taxa in the corresponding files. GNFinder had a high F1 Score (0.86) representing a balance between precision (0.91) and recall (0.82). GNFinder had lower performance when a name string was an irregular abbreviation, had unexpected capitalization or punctuation, or contained a qualifier (like aff. or cf. ). Approximately 14% of the name strings identified in text published from 1996 to 2012 were outdated and updated to a current, valid name. Automated metadata creation and maintenance at scale using GNFinder can make it easier to find biodiversity publications as demonstrated by the Biodiversity Heritage Library and HathiTrust.

The vampyrellids (Vampyrellida, Rhizaria) are a major group of predatory amoebae that have attracted significant attention because of their diversity of feeding strategies. The crucial roles they play in important processes such as suppressing soil disease and controlling aquatic algae, and as microbial contaminants in outdoor large-scale algal cultures, have also received increasing attention.

Decades of reductionist approaches in biology have achieved spectacular progress, but the proliferation of subdisciplines, each with its own technical and social practices regarding data, impedes the growth of the multidisciplinary and interdisciplinary approaches now needed to address pressing societal challenges. Data integration is key to a reintegrated biology able to address global issues such as climate change, biodiversity loss, and sustainable ecosystem management. We identify major challenges to data integration and present a vision for a "Data as a Service"-oriented architecture to promote reuse of data for discovery. The proposed architecture includes standards development, new tools and services, and strategies for career-development and sustainability.

Decades of reductionist scientific approaches have led to spectacular progress and the proliferation of biological sub-disciplines, each spawning its own technical and social practices regarding data. This fragmented landscape poses substantial hurdles to the multi-disciplinary approaches needed to address pressing societal challenges. Data integration is key to the reintegration of biology and the pursuit of global questions such as climate change, biodiversity loss, and sustainable ecosystem management. Here, we define the primary challenges in data integration and present a vision for a Data as a Service (DaaS) oriented architecture that enables frictionless data reuse, hypothesis testing, and discovery. The proposed data integration infrastructure includes standards development, a suite of tools and services, and strategies for education and sustainability.

The Biodiversity Heritage Library contains 57 million pages of biological information. The majority of this information is a scanned and digitized non-structured text. This "raw" text is hard to access by computers or humans, without the addition of rich metadata. Recent improvements in natural language processing (NLP) and machine learning (ML) promise to facilitate the creation of such metadata. One obvious approach to improve BHL usability is to extract and provide an index of scientific names thereby enabling biologists to find useful information easier and faster. The Global Names Architecture (GNA) detects, verifies, collects, and indexes scientific names from many sources. Six years ago GNA developers created an index of the scientific names in the BHL by parsing every page one by one. This took 45 days to accomplish. Almost immediately BHL users began to find problems in the index and suggest improvements. However, the cost of repeating such a gigantic job was insurmountable and as a result the index remained nearly unchanged for 6 years. Two problems were at the heart of dealing with the “Big Data” of the BHL, the time it took to transfer the raw data prior to processing, and the computational time it took to detect the names themselves.To solve these problems we could either throw more hardware resources into the problem (expensive), or find ways to dramatically improve performance of the tasks (cheaper). We decided to achieve our goal by utilizing hardware more effectively, and by using fast, scalable programming languages. We wrote several Open Source applications in Go and Scala to detect candidate scientific names then verify them as names by comparing them to 27 million scientific name-strings aggregated by GNA. We were able to speed up data mobilization from 24 hours to 11 minutes, and decrease the time for name detection from 35 days to 5 hours. Name-verification time decreased from 10 days to 9 hours. Overall our computing requirements shrank from 4 high-end servers to one modern laptop. As a result we achieved our goal and indexed BHL in only 14 hours and unlocked the reality of iterative improvements to the scientific name index. We also wanted to make it possible to study BHL data in its entirety remotely, in real-time. We created an HTTP2 service that is able to stream gigantic amounts of BHL textual data together with scientific names to a researcher. Sending the text of 50 million pages with an associated 250 million name occurrences takes ~5 hours. For comparison, simply copying BHL text data from Smithsonian Institute to University of Illinois using more traditional methods took us 10 days. What do we hope to achieve with these tools as next steps? To make it possible for everyone to make new discoveries by computing in real-time across the complete BHL text. For example 20% of all names in BHL are abbreviated, and, as a result, very poorly searchable given their existing full-text indexing. We plan to develop algorithms to expand abbreviated genera reliably. Digitized texts contain huge amounts of character recognition mistakes. The tools might help to detect badly digitized pages and mark them for re-digitization. Tools can help to extract scientific names that are identical to "normal" words, such as "Atlanta", or "America", to find common names in texts, and to localize information on locations, adding new search contexts. Finally, we are exploring tools that allow researchers to stream such results back to source thereby growing the “Big Data” and ultimately improving the BHL’s end-user experience.

Taxonomy is a scientific discipline that has provided the universal naming and classification system of biodiversity for centuries and continues effectively to accommodate new knowledge. A recent publication by Garnett and Christidis [1] expressed concerns regarding the difficulty that taxonomic changes represent for conservation efforts and proposed the establishment of a system to govern taxonomic changes. Their proposal to “restrict the freedom of taxonomic action” through governing subcommittees that would “review taxonomic papers for compliance” and their assertion that “the scientific community’s failure to govern taxonomy threatens the effectiveness of global efforts to halt biodiversity loss, damages the credibility of science, and is expensive to society” are flawed in many respects. They also assert that the lack of governance of taxonomy damages conservation efforts, harms the credibility of science, and is costly to society. Despite its fairly recent release, Garnett and Christidis' proposition has already been rejected by a number of colleagues [2,3,4,5,6,7,8]. Herein, we contribute to the conversation between taxonomists and conservation biologists aiming to clarify some misunderstandings and issues in the proposition by Garnett and Christidis.

Recent advances in molecular technology have revolutionized research on all aspects of the biology of organisms, including ciliates, and created unprecedented opportunities for pursuing a more integrative approach to investigations of biodiversity. However, this goal is complicated by large gaps and inconsistencies that still exist in the foundation of basic information about biodiversity of ciliates. The present paper reviews issues relating to the taxonomy of ciliates and presents specific recommendations for best practice in the observation and documentation of their biodiversity. This effort stems from a workshop that explored ways to implement six Grand Challenges proposed by the International Research Coordination Network for Biodiversity of Ciliates (IRCN-BC). As part of its commitment to strengthening the knowledge base that supports research on biodiversity of ciliates, the IRCN-BC proposes to populate The Ciliate Guide, an online database, with biodiversity-related data and metadata to create a resource that will facilitate accurate taxonomic identifications and promote sharing of data.