%0 Journal Article %1 muller_livivo_2017 %A Müller, Bernd %A Poley, Christoph %A Pössel, Jana %A Hagelstein, Alexandra %A Gübitz, Thomas %D 2017 %J Datenbank-Spektrum %K suchmaschinen %P 1--6 %R 10.1007/s13222-016-0245-2 %T LIVIVO : the vertical search engine for life sciences %U http://link.springer.com/article/10.1007/s13222-016-0245-2 %X The explosive growth of literature and data in the life sciences challenges researchers to keep track of current advancements in their disciplines. Novel approaches in the life science like the One Health paradigm require integrated methodologies in order to link and connect heterogeneous information from databases and literature resources. Current publications in the life sciences are increasingly characterized by the employment of trans-disciplinary methodologies comprising molecular and cell biology, genetics, genomic, epigenomic, transcriptional and proteomic high throughput technologies with data from humans, plants, and animals. The literature search engine LIVIVO empowers retrieval functionality by incorporating various literature resources from medicine, health, environment, agriculture and nutrition. LIVIVO is developed in-house by ZB MED – Information Centre for Life Sciences. It provides a user-friendly and usability-tested search interface with a corpus of 55 Million citations derived from 50 databases. Standardized application programming interfaces are available for data export and high throughput retrieval. The search functions allow for semantic retrieval with filtering options based on life science entities. The service oriented architecture of LIVIVO uses four different implementation layers to deliver search services. A Knowledge Environment is developed by ZB MED to deal with the heterogeneity of data as an integrative approach to model, store, and link semantic concepts within literature resources and databases. Future work will focus on the exploitation of life science ontologies and on the employment of NLP technologies in order to improve query expansion, filters in faceted search, and concept based relevancy rankings in LIVIVO.

@article{muller_livivo_2017, abstract = {The explosive growth of literature and data in the life sciences challenges researchers to keep track of current advancements in their disciplines. Novel approaches in the life science like the One Health paradigm require integrated methodologies in order to link and connect heterogeneous information from databases and literature resources. Current publications in the life sciences are increasingly characterized by the employment of trans-disciplinary methodologies comprising molecular and cell biology, genetics, genomic, epigenomic, transcriptional and proteomic high throughput technologies with data from humans, plants, and animals. The literature search engine LIVIVO empowers retrieval functionality by incorporating various literature resources from medicine, health, environment, agriculture and nutrition. LIVIVO is developed in-house by ZB MED – Information Centre for Life Sciences. It provides a user-friendly and usability-tested search interface with a corpus of 55 Million citations derived from 50 databases. Standardized application programming interfaces are available for data export and high throughput retrieval. The search functions allow for semantic retrieval with filtering options based on life science entities. The service oriented architecture of LIVIVO uses four different implementation layers to deliver search services. A Knowledge Environment is developed by ZB MED to deal with the heterogeneity of data as an integrative approach to model, store, and link semantic concepts within literature resources and databases. Future work will focus on the exploitation of life science ontologies and on the employment of NLP technologies in order to improve query expansion, filters in faceted search, and concept based relevancy rankings in LIVIVO.}, added-at = {2018-11-04T17:02:36.000+0100}, author = {Müller, Bernd and Poley, Christoph and Pössel, Jana and Hagelstein, Alexandra and Gübitz, Thomas}, biburl = {https://www.bibsonomy.org/bibtex/235add0b5218e3c8abdc7d2baf0ee7639/lepsky}, doi = {10.1007/s13222-016-0245-2}, interhash = {cb9d0be2ca7506b54ac3822aaecf13e9}, intrahash = {35add0b5218e3c8abdc7d2baf0ee7639}, issn = {1618-2162, 1610-1995}, journal = {Datenbank-Spektrum}, keywords = {suchmaschinen}, language = {en}, month = jan, pages = {1--6}, timestamp = {2018-11-04T17:02:36.000+0100}, title = {{LIVIVO} : the vertical search engine for life sciences}, url = {http://link.springer.com/article/10.1007/s13222-016-0245-2}, urldate = {2017-01-27}, year = 2017 }