Future development within iEcology will be enhanced by rapidly developing technologies such as:
Taking a picture of a desert horned viper (Cerastes cerastes) during a herpetology tour (Photo: Uri Roll)
Apps and games - Apps on mobile devices are ubiquitous, and often within a person’s reach. Using these to support augmented reality could also provide an interface to generate more detailed data with real-time diagnostics. In addition, apps which 'gamify' nature can motivate public to interact with their environment, and thus provide more data on species and the environment. Overall, apps and games have the potential to transform how humans interact with nature (both positive and negative) and cause a fundamental shift in the quantity and quality of iEcology data.
Automated content analysis – the application of algorithms for analyzing visual, textual, and audio content from digital sources. These methods have allowed for e.g. automatic identification, counting, and description of species and individuals from images and videos and the extraction from text of information on species and their interactions. Further developments will allow combining visual, textual, and audio analysis of large volumes of iEcology data. All these methods should be used carefully and considering ethical concerns.
Bioacoustics and ecoacoustics – the recording and analysis of sounds produced by biological entities and entire environments. Increase in sonic and video recording and publicized soundscapes could provide an untapped source of data for iEcology.
Blockchain – cryptographically linked and growing data lists. Further development of dedicated iEcology blockchains or plug-ins will allow the creation of immutable complex data of various formats that will be permanently recorded into a decentralized platform at the moment of their creation. This would increase security, traceability, decrease errors associated with multiple data entries, and allow imprinting of the technical details of data generator.
Internet of things – a network of computers, machines, and other objects that share information and interact. This will greatly increase the amount of data pertaining to humans and their actions.
Open source hardware – physical objects with design specifications that allow them to be widely studied, modified, created, and distributed. As more knowledge and expertise on construction of various sensors are produced and shared, larger volumes of high-quality and more specialized data could be produced.
Web scraping – the fetching and extraction of relevant information from web content, mostly done automatically. Further developments in these technologies will enable better and quicker access to larger volumes of iEcology data, and potentially continuous monitoring of patterns and trends.
Automated content analysis – the application of algorithms for analyzing visual, textual, and audio content from digital sources. These methods have allowed for e.g. automatic identification, counting, and description of species and individuals from images and videos and the extraction from text of information on species and their interactions. Further developments will allow combining visual, textual, and audio analysis of large volumes of iEcology data. All these methods should be used carefully and considering ethical concerns.
Bioacoustics and ecoacoustics – the recording and analysis of sounds produced by biological entities and entire environments. Increase in sonic and video recording and publicized soundscapes could provide an untapped source of data for iEcology.
Blockchain – cryptographically linked and growing data lists. Further development of dedicated iEcology blockchains or plug-ins will allow the creation of immutable complex data of various formats that will be permanently recorded into a decentralized platform at the moment of their creation. This would increase security, traceability, decrease errors associated with multiple data entries, and allow imprinting of the technical details of data generator.
Internet of things – a network of computers, machines, and other objects that share information and interact. This will greatly increase the amount of data pertaining to humans and their actions.
Open source hardware – physical objects with design specifications that allow them to be widely studied, modified, created, and distributed. As more knowledge and expertise on construction of various sensors are produced and shared, larger volumes of high-quality and more specialized data could be produced.
Web scraping – the fetching and extraction of relevant information from web content, mostly done automatically. Further developments in these technologies will enable better and quicker access to larger volumes of iEcology data, and potentially continuous monitoring of patterns and trends.
