Popler: An r package for extraction and synthesis of population time series from the long‐term ecological research (LTER) network. Issue 2 (20th November 2019)
- Record Type:
- Journal Article
- Title:
- Popler: An r package for extraction and synthesis of population time series from the long‐term ecological research (LTER) network. Issue 2 (20th November 2019)
- Main Title:
- Popler: An r package for extraction and synthesis of population time series from the long‐term ecological research (LTER) network
- Authors:
- Compagnoni, Aldo
Bibian, Andrew J.
Ochocki, Brad M.
Levin, Sam
Zhu, Kai
Miller, Tom E. X. - Editors:
- Ellison, Aaron
- Abstract:
- Abstract: Population dynamics play a central role in the historical and current development of fundamental and applied ecological science. The nascent culture of open data promises to increase the value of population dynamics studies to the field of ecology. However, synthesis of population data is constrained by the difficulty in identifying relevant datasets, by the heterogeneity of available data and by access to raw (as opposed to aggregated or derived) observations. To obviate these issues, we built a relational database, popler, and its R client, the library "popler". popler accommodates the vast majority of population data under a common structure, and without the need for aggregating raw observations. The "popler" R library is designed for users unfamiliar with the structure of the database and with the SQL language. This R library allows users to identify, download, explore and cite datasets salient to their needs. We implemented popler as a PostgreSQL instance, where we stored population data originated by the United States Long Term Ecological Research (LTER) Network. Our focus on the US LTER data aims to leverage the potential of this vast open data resource. The database currently contains 305 datasets from 25 LTER sites. popler is designed to accommodate automatic updates of existing datasets, and to accommodate additional datasets from LTER as well as non‐LTER studies. The combination of the online database and the R library "popler" is a resource for dataAbstract: Population dynamics play a central role in the historical and current development of fundamental and applied ecological science. The nascent culture of open data promises to increase the value of population dynamics studies to the field of ecology. However, synthesis of population data is constrained by the difficulty in identifying relevant datasets, by the heterogeneity of available data and by access to raw (as opposed to aggregated or derived) observations. To obviate these issues, we built a relational database, popler, and its R client, the library "popler". popler accommodates the vast majority of population data under a common structure, and without the need for aggregating raw observations. The "popler" R library is designed for users unfamiliar with the structure of the database and with the SQL language. This R library allows users to identify, download, explore and cite datasets salient to their needs. We implemented popler as a PostgreSQL instance, where we stored population data originated by the United States Long Term Ecological Research (LTER) Network. Our focus on the US LTER data aims to leverage the potential of this vast open data resource. The database currently contains 305 datasets from 25 LTER sites. popler is designed to accommodate automatic updates of existing datasets, and to accommodate additional datasets from LTER as well as non‐LTER studies. The combination of the online database and the R library "popler" is a resource for data synthesis efforts in population ecology. The common structure of popler simplifies comparative analyses, and the availability of raw data confers flexibility in data analysis. The "popler" R library maximizes these opportunities by providing a user‐friendly interface to the online database. Foreign Language Abstract Sommario: Le dinamiche di popolazione hanno un ruolo centrale nella storia e nello sviluppo della scienza ecologica pura ed applicata. La nascente cultura degli open data promette di au‐mentare l'importanza degli studi sulle dinamiche di popolazione nel campo dell'ecologia. Tuttavia, la sintesi dei dati a livello di popolazione e' limitata dalla di_colta' nell'identi_care dataset adeguati, dall'eterogeneita' dei dati disponibili, e dall'accesso ai dati grezzi (invece che a dati aggregati o derivati). Per ovviare a questi problemi, abbiamo creato un database relazionale, popler, e il suo cliente R, il pacchetto "popler". popler e' disegnato per contenere la stragrande maggio‐ranza dei dati a livello di popolazione usando una struttura comune, e senza la necessita' di aggregare dati grezzi. Il pacchetto R "popler" e' disegnato per utilizzatori che non sono a conoscenza della struttura del database e non hanno dimestichezza con il linguaggio SQL. Questo pacchetto R permette al cliente di identi_care, scaricare, esplorare, e citare dataset rilevanti alle sue necessita'. Abbiamo implementato popler creando una istanza PostgreSQL, dove abbiamo riposto dati originati dal Long Term Ecological Research (LTER) Network degli Stati Uniti d'America (USA). La nostra attenzione ai dati dell'LTER USA e' pensata per sfruttare il potenziale di questa vasta quantita` di open data. Attualmente, il database contiente 305 dataset appartenenti a 25 siti LTER. popler e' disegnato per rendere possibili aggiornamenti au‐tomatici dei dataset esistenti, e per contenere nuovi dataset, siano essi parte o meno del Network LTER. La combinazione del database online e del pacchetto R "popler" e' una risorsa per lavori ecologici che vertono sulla sintesi di dati. La struttura comune di popler sempli_ca le analisi comparative, e la disponibilita' di dati grezzi conferisce essibilita' nell'analisi dei dati. La libreria R popler sfrutta al massimo queste opportunita fornendo all'utilizzatore una accessibile interfaccia al database online. … (more)
- Is Part Of:
- Methods in ecology and evolution. Volume 11:Issue 2(2020)
- Journal:
- Methods in ecology and evolution
- Issue:
- Volume 11:Issue 2(2020)
- Issue Display:
- Volume 11, Issue 2 (2020)
- Year:
- 2020
- Volume:
- 11
- Issue:
- 2
- Issue Sort Value:
- 2020-0011-0002-0000
- Page Start:
- 258
- Page End:
- 264
- Publication Date:
- 2019-11-20
- Subjects:
- comparative analysis -- data synthesis -- database structure -- online database -- open long‐term population data -- PostgreSQL -- r package -- US Long Term Ecological Research Network data
Ecology -- Periodicals
Evolution -- Periodicals
577 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)2041-210X ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/2041-210X.13319 ↗
- Languages:
- English
- ISSNs:
- 2041-210X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12687.xml