Tuesday, October 29, 2013
Outreach activities have been the main focal point so far in Autumn 2013.
ENVIRONMENTS, ENVIRONMENTS-EOL, and the sister project SPECIES have been presented at an invited talk at the BioCreative IV workshop (7 - 9 October, Washington DC, US) as part of a DOE-funded Discussion Panel on Metagenomics.
Bridging the metagenomics and text mining communities e.g. by employing text mining techniques to support standards-compliant sequence metadata annotation was one of the main discussion points.
The Biocreative IV workshop proceedings including opinions on the previous point are available here (see Volume 1, pages 279-291).
On behalf of the ENVIRONMENTS-EOL team a big thank you to the BioCreative organizers.
At the time of writing, the Biodiversity Information Standards Conference (TDWG 2013, 28 Oct - 1 Nov, Firenze), is on-going.
ENVIRONMENTS-EOL will be be presented this Friday (1st Nov, 11:20) in the "Interoperability with genomic and ecological semantics" session of the Semantics for Biodiversity Symposium of TDWG2013 (Travel made possible thanks to EOL Rubenstein Fellows Program's funding).
In parallel and while the benchmarking algorithms are being prepared, the ENVIRONMENTS-600 (E600) corpus returned by the curators (see August's post) underwent housekeeping processing e.g. by removing any errors that had been introduced during the manual curation such as missing tabs in the annotation items, flag misspellings and others.
A mountain range (ENVO:00000080) as seen on board a flight from Münich, Germany to Florence, Italy to attend TDWG2013. Could it be the Dolomite mountain range?
Saturday, September 14, 2013
Amid July – August high temperatures for some of the team members, visits in associate labs for some others, and as a side-activity to normal lab/office work for the rest, the most tedious and time-consuming part of this project has now been completed.
Environments-600 (E600), a corpus comprising 600 EOL Taxa pages was evenly and randomly distributed among the 6 curators (4 graduate students, 2 postdocs, see June’s post).
To maximize environment type coverage the 600 EOL documents were species pages randomly picked from the following eight taxonomic taxa: Actinopterygii, Annelida, Arthropoda, Aves, Chlorophyta, Mammalia, Mollusca, Streptophyta. These are taxa either associated with different environments to each other, or known to exist in a diverse range of environments.
Each curator had 45 days to annotate 120 documents (ie. their part of the corpus: 600/6 = 100 documents each, plus 20 documents (ie. 20% of 100) that are common with other curators. The ‘20% overlap’ is an important part of the curation process. It supports the calculation of the Inter-annotator agreement (IAA, based on pairwise calculations of the Cohen's kappa coefficient.
Each curator had access to his/her own documents only. No information on the shared documents had been disclosed.
All curators were instructed to evaluate all document substrings and map the recognized environment descriptors to the corresponding EnvO terms.
Reflecting on the EnvO, envo-basic.obo, version-date: 14th June 2013, such environment descriptors included: habitats, biomes, enviromental features, conditions and materials (EnvO high level terms: 00002036, 00000428, 00002297, 01000203, 00010483 respectively)
All recognized mentions should be listed (including repetitions) in the order of appearance in text. To facilitate EnvO term search and ontology browsing OBO-Edit has been employed.
When an environment descriptor could refer to more than one EnvO terms multiple mappings were allowed (e.g. mapping “forest” to ENVO:00000111, “forest” (environmental feature), and 01000174, “forest biome”).
In the case of “nested” environment descriptors, a “left-longest most”-like matching approach applied. If for example “sandy sediment” is met in text, it will be mapped to ENVO: 01000118, “sandy sediment” (and not to the nested terms: sand, sediment).
During the curation a range of special cases were encountered. Cases like misspellings, EnvO term missing synonyms and enumerations were indicated as such. Environment descriptors that did not correspond to an existing EnvO term were also marked as such.
Finally, when environment descriptive terms where part of geographical locations and/or common taxon names (e.g. Steppe Eagle, Aquila nipalensis, shown in the Figure) were flagged as such to allow for downstream analysis.
Calculating the IAA, merging the annotated document in a single corpus are now ongoing, paving the ground for the ENVIRONMENT’s accuracy benchmark. Stay tuned!
Friday, August 9, 2013
July 2013 has been a highly active month.
A visit of Dr. Lars Juhl Jensen in HCMR (Hellenic Center for Marine Research), Crete followed up on last April’s ENVIRONMENTS software developments (see post).
The main focus was on updating the dictionary and the stopword-list according to the information contained in a recent Environmental Ontology version (envo-basic.obo, date: 14 June 2013)
The Environmental Ontology updates including an improved coverage of terrestrial biomes (see EnvO News post) were the main reason for such an update.
As a result, the v1.0 ENVIRONMENTS tagger is now ready and has been delivered to EOL (including the latest dictionary of environment descriptive terms and the relevant stopword-list). All these software components are open source and will be made available at due time.
An annotation of all EOL-Taxon pages using the v1.0 tagger, along with a precision analysis of the different EOL page section annotation have been completed.
The gold standard corpus curation and the analysis of ENVIRONMENTS’ accuracy based on that corpus are now the main focus. 600 EOL species pages (from eight taxonomic taxa: Actinopterygii, Annelida, Arthropoda, Aves, Chlorophyta, Mammalia, Mollusca, Streptophyta – to maximize environment diversity) have now been shared among the curators and the manual annotation is ongoing.
Thursday, July 4, 2013
A gold standard corpus generation comprises steps such as: document collection/selection, manual document annotation, annotation result collection and statistical analysis.
The first and last steps can be computationally assisted and partially automated. However, this is not the case for the manual document annotation. Also called “curation”, the manual document annotation comprises the manual scanning of the document text to identify environment descriptive terms and map them to unique identifiers according to a community resource (the Environment Ontology (EnvO) in this case).
The tediousness and time-demands of such process call for collaborative effort. Aa international group of six researchers: Lucia Fanini, Sarah Faulwetter, Evangelos Pafilis, Christina Pavloudi, Julia Schnetzer, Katerina Vasileiadou (in alphabetical order) have undertaken this task.
Coming from a diverse range of scientific background (such as ecology, computational biology, molecular biology, and systematic) they represent different mindsets upon scanning pieces of text, in a way representing different EOL readers.
Such pluralism is a desired feature for the corpus curation, however a common understanding among team members has to be established.
This was one of the main aims of the test curation (“dry run”) that took place during June 2013. A small set of documents (Text sections from EOL species pages, see post) were delivered to all curators. Upon manually annotating these documents curators collected as many questions as possible around unclear and/or problematic annotation cases. Some examples of the latter are: terms and/or synonyms missing from EnvO, words that could be mapped to multiple EnvO terms, location names, nested environment descriptive terms.
A strategy employing a set of flags to indicate such cases is now in place. The previously generated the curation guideline document (see post) has been updated accordingly and the production-level curation may now start.
The SPECIES and ORGANISMS Resources for Fast and Accurate Identification of Taxonomic Names in Text @ PLOS ONE
The sister projects of SPECIES and ORGANISMS now published at PLOS ONE, part of the PLOS Text Mining Collection.
The SPECIES and ORGANISMS Resources for Fast and Accurate Identification of Taxonomic Names in Text. Pafilis E, Frankild SP, Fanini L, Faulwetter S, Pavloudi C, et al. (2013) PLoS ONE 8(6): e65390. doi:10.1371/journal.pone.0065390
The knowledge, skills and know-how gained through this work paved the ground for ENVIRONMENTS.
A big thank you to the team, Evangelos
Monday, June 3, 2013
May 2013: gearing up the corpus curation, mining names and synonyms from EOL content, following closing EnvO developments
Chrisi, a Natura 2000 site south-east of Crete, Greece. “Coarse beach sand” (ENVO:00002148) can be observed along with shells forming a “biogenous sediment” (ENVO:01000082); a unique feature of this island. Besides the “Coarse beach sand” are all types of sand included in the Environment Ontology? Can the Environments-EOL project assist in proposing terms, names and synonyms? (Image: CC BY-NC-SA)
The Environments-EOL project is nearing its main stages (corpus creation, tagger bench-marking, EOL annotation and taxa characterization, to take place in Summer 2013). To this end a range of preparatory tasks are being/have been conducted.
May 2013 has seen a “dry-run” curation being setup. A small set of document is being used for a trial curation (ongoing). The manual and lengthy nature of a corpus generation dictates tests take place before the main body of work commences. Via such a “dry-run” curators are getting familiarized with the Environment Ontology as well as with relevant browsing and searching tools. Additionally, questions are being raised and discussions invoked on the exact context of terms to be annotated by the Environments-EOL project.
In parallel: early tests showed that the manual addition of synonyms in the dictionary (see “Dictionary Generation in previous post”) could improve the tagger performance. To facilitate such task specialized EOL sections (e.g. Habitat) have been analyzed (counting word frequency in non-tagged text segments). A priority list of terms to be considered was derived. After manual inspection environment related words have been mapped to EnvO terms and can now be added in the dictionary. The EOL records involved in this training step have been excluded from the corpus generation (and subsequently the software evaluation).
Last but not least: Environments-EOL is a project tightly bound to the Environment Ontology community resource. Highlighting this connection as well the projects’ dynamic nature: a thank you for the EnvO team’s prompt and timely response in updating the "terrestrial biome" hierarchy, comprising now more compact and fine grained terms (see EnvO News Post)
Friday, May 3, 2013
Nice days during the visit in Copenhagen (1-13 April 2013); while working on ENVIRONMENTS balloons showed up in the "air"(ENVO:00002005) (image taken at Frederiksberg, Copenhagen; CC BY-NC-SA)
April 2013 has been mainly a travelling month. Besides the presentation of ENVIRONMENTS at GSC 15 (see previous post) a 2-week visit (made possible via the EOL-RubensteinFellowship support) at Dr. Lars Juhl Jensen and Dr. Sune Frankild premises (NNF-CPR, Denmark) has resulted in the implementation of series of critical tasks.
ENVIRONMENTS Software Development: Dictionary generation
The name and synonym information in the Environment Ontology (EnvO) resource has been assessed. Based on them a dictionary has been generated mapping environment descriptive terms to EnvO identifiers.
Where necessary, extra synonyms were generated capturing the variable ways EnvO terms may be written in text. As an extension to previous work (see post) the generation of adjectives (e.g. coast – coastal) or plural forms (e.g. brackish water – brackish waters) has been included.
Species names and anatomy terms present in EnvO, also described in other taxonomies/ontologies, were not included in the dictionary. Moreover food names were excluded as they may give rise to out-of-context text mining results.
Encyclopedia of Life textual component retrieval and processing
The EOL API has been used to retrieve sections (“subjects” in the EOL terminology) for every taxon such as: TaxonBiology, Description, Biology, Distribution, Habitat and more)
The EOL Taxa text components have been downloaded in the JSON format. A parser has been development that collected the selected sections only and converts the text in a ENVIRONMENTS compatible format (e.g. removes HTML tags and convers UTF8 characters to ASCII)
ENVIRONMENTS Software Development: Stopword curation
Local text repositories of PubMed and EOL were processed with ENVIRONMENTS (using an early-version dictionary). The most frequently tagged terms were inspected manually in-text. Those that were found, most of the times, in a context other than describing an environment were added in a “stopword” list. “well”, “sping”, “range” are a few such examples. Such terms would have caused a high number of false positive matches. This “stopword” list is a mechanism against such phenomenon; its terms will be excluded from the analysis.
ENVIRONMENTS corpus preparation
A major component of this project is the creation of a manually annotated corpus (gold standard).
Such a corpus comprises a set of documents in which environment descriptors have been manually identified and mapped to unique identifiers in community resources (e.g. the Environment Ontology terms). By comparing the manual annotations with software predicted tags the accuracy of environment descriptive term identification software can be evaluated.
Two basic requirements that such a corpus must meet is:
a. to be comprehensive i.e. to contain text that refer to diverse types of environments
b. to contain a minimum number of terms per document that would make the manual annotation feasible in a pragmatic time frame