{"id":557697,"date":"2018-12-18T15:26:24","date_gmt":"2018-12-18T23:26:24","guid":{"rendered":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/?post_type=msr-event&p=557697"},"modified":"2025-08-06T11:56:42","modified_gmt":"2025-08-06T18:56:42","slug":"northwest-database-society-nwds-annual-meeting-2019","status":"publish","type":"msr-event","link":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/event\/northwest-database-society-nwds-annual-meeting-2019\/","title":{"rendered":"Northwest Database Society (NWDS) Annual Meeting 2019"},"content":{"rendered":"\n\n

Microsoft Research
\n14820 NE 36th St., Bldg. 99
\nRedmond, WA 98052Opens in a new tab<\/span><\/p>\n

The Northwest Database Society Annual Meeting brings together researchers and practitioners from the greater Pacific Northwest for a day of technical talks and networking on the broad topic of data management systems.<\/p>\n

It will be a full-day event. There will be two keynotes, several sessions of shorter presentations by members of our community, a poster session, and significant break time for unstructured discussion. There will be breakfast, lunch, coffee breaks, and a post-conference reception, courtesy of Microsoft Research.<\/p>\n

If you plan to attend the event, then please register here (opens in new tab)<\/span><\/a>. Although there is no registration fee, you must register to attend.<\/p>\n

Keynote 1: <\/strong>“Explainable Artificial Intelligence in Precision Medicine,” Su-In Lee (UW CSE)<\/h4>\n

Modern machine learning models can accurately predict patient progress and outcomes, however, they are not interpretable in the sense that they do not explain why selected features make sense or why a particular prediction result was made. I will talk about my group’s efforts to address these challenges by developing interpretable machine learning techniques for a wide range of applications, including treating cancer based on a patient’s own molecular profile, finding therapeutic targets for Alzheimer’s, predicting chronic kidney disease, preventing complications during surgery, enabling pre-hospital predictions for trauma patients, and improving our understanding of pan-cancer biology and genome biology. Among these, I will mainly focus on our work MERGE, which uses machine learning to enable targeted treatment of acute myeloid leukemia, published in Nature Communications<\/em> last year, and our explainable artificial intelligence system, Prescience, for preventing hypoxemia in patients under anesthesia, recently featured on the cover of the most recent issue of Nature Biomedical Engineering<\/em>.<\/p>\n

Bio:\u00a0Prof. Su-In Lee (opens in new tab)<\/span><\/a> is an Associate Professor in the Paul G. Allen School of Computer Science & Engineering<\/a>, and an Adjunct Associate Professor in the Genome Sciences Department<\/a>, the Department of Electrical <\/a>Engineering<\/a> and the Department of Biomedical Informatics and Medical Education<\/a> at the University of Washington. She completed her PhD in 2009 at Stanford University<\/a> with Prof. Daphne Koller<\/a> in the Stanford Artificial Intelligence Laboratory<\/a>.\u00a0 Before joining the UW in 2010, she was a visiting professor in the Computational Biology Department<\/a> at Carnegie Mellon University<\/a>. She has received the National Science Foundation CAREER Award and been named an American Cancer Society Research Scholar.\u00a0 She has received a number of generous grants from the National Institutes of Health<\/a> (NIH), National Science Foundation<\/a> (NSF), and American Cancer Society<\/a> (ACS).<\/p>\n

Keynote 2:<\/strong> “Overlaying Distributed Database Applications over Blockchains,” Donald Kossmann & Arvind Arasu (Microsoft Research)<\/h4>\n

There has been a great deal of hype around Blockchains. The Blockchain is a set of technologies to protect the integrity of transactions in an open and scalable way. This talk argues that the core feature of Blockchains, the notion of a digital witness, is extremely useful, but that Blockchain technologies are packaged in the wrong way, thereby reinventing the wheel of databases and distributed transactions. Instead, Blockchain technologies can be integrated into existing data management systems using the existing abstractions such as SQL, stored procedures, and key-value stores. As an example, the talk shows how Blockchain and more traditional database techniques can be used in concert to manage \u201cDecentralized IDs\u201d in an open and scalable way that allows users to control the creation and usage of IDs.<\/p>\n

Bio: Donald Kossmann<\/a> is Distinguished Scientist and Director of Microsoft Research Redmond<\/a>. He works on data management in the cloud, with the goal of making data in the cloud cheaper, more valuable, and more secure. Before Microsoft, he was a professor in the Systems Group of the Department of Computer Science at ETH Zurich for 13 years, doing research and teaching all flavors of data management systems. He was chair of ACM\u00a0SIGMOD from 2013 to 2017 and served on the Board of Trustees of the VLDB Endowment from 2005 to 2011. He co-founded four companies: i-TV-T AG (1998),\u00a0XQRL Inc. (2002), 28msec Inc. (2006), and Teralytics AG (2010).<\/p>\n

Arvind Arasu<\/a> is a Senior Researcher in the Database<\/a> group at Microsoft Research<\/a>. He is currently working on database encryption in the Cipherbase project, whose goal is to enable query processing while keeping data confidential. He previously worked on data streams, information extraction, and data cleaning<\/a>.<\/p>\n

Agenda<\/strong><\/h3>\n

8-9am Breakfast: Cured meat, cheese, croissants, sliced fruit, fruit juice, and coffee & tea.<\/p>\n

Session #1:<\/strong> Video and slides<\/a><\/p>\n

9-10am Su-In Lee (University of Washington): Explainable Artificial Intelligence in Precision Medicine<\/p>\n

10:00 – 10:30 Break<\/p>\n

Session #2: <\/strong>Video and slides<\/a><\/p>\n

10:30 – 10:45 Badrish Chandramouli (Microsoft):\u00a0Open-Source Technologies for Streaming and State Management<\/p>\n

10:45 – 11:00 Jiannan Wang (Simon Fraser University): Democratize Data Preparation for AI<\/p>\n

11:00 – 11:15 Diana Popova (University of Victoria): CutTheTail<\/p>\n

11:15 – 11:30 Batya Kenig (University of Washington): Integrity Constraints Revisited: From Exact to Approximate Implication<\/p>\n

11:30 – 11:45 Gang Luo (University of Washington): Automating Machine Learning Model Building with Big Clinical Data<\/p>\n

11:45 – 12:00 Cong Yan (University of Washington):\u00a0Generating Application-Specific In-Memory Databases<\/p>\n

12:00 – 1:15 Lunch and posters (slides only)<\/p>\n

1:15 – 1:30\u00a0Kamal Gupta (AWS): Amazon Aurora (opens in new tab)<\/span><\/a> (slides only)<\/span><\/p>\n

Session #3:<\/strong> Video and slides<\/a><\/p>\n

1:30 – 1:45 Bailu Ding (Microsoft):\u00a0Improving Optimistic Concurrency Control Through Transaction Batching and Operation Reordering<\/p>\n

1:45 – 2:00 Alekh Jindal (Microsoft):\u00a0Towards a Learning Optimizer for Shared Clouds<\/p>\n

2:00 – 2:15\u00a0Amir Hormati (Google): BigQuery Machine Learning: Advanced Insights in SQL<\/p>\n

2:15 – 2:30 Mosha Pasumansky (Google): BigQuery, an Exabyte-Scale Analytical Storage System<\/p>\n

2:30 – 3:00\u00a0Break: nuts, fruit, coffee, tea, soft drinks<\/p>\n

Session #4:<\/strong> Video and slides<\/a><\/p>\n

3:00 – 3:15\u00a0Vishakha Gupta (ApertureData) & Luis Remis (Intel Labs): A Visual Data Management System<\/p>\n

3:15 – 3:30 Torsten Grabs (Snowflake): The Snowflake Engine<\/p>\n

3:30 – 4:30\u00a0 Donald Kossmann & Arvind Arasu (Microsoft): Overlaying Distributed Database Applications over Blockchains<\/p>\n

Previous Meetings<\/strong><\/h5>\n

This is the second meeting of the series. The first meeting was at University of Washington on January 5, 2018, described here (opens in new tab)<\/span><\/a>.<\/p>\n

Contact Information<\/strong><\/h5>\n

Phil Bernstein<\/a><\/p>\n

Johannes Gehrke <\/a>Opens in a new tab<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Microsoft Research 14820 NE 36th St., Bldg. 99 Redmond, WA 98052Opens in a new tab The Northwest Database Society Annual Meeting brings together researchers and practitioners from the greater Pacific Northwest for a day of technical talks and networking on the broad topic of data management systems. It will be a full-day event. There will […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_startdate":"2019-02-08","msr_enddate":"2019-02-08","msr_location":"Redmond, WA","msr_expirationdate":"","msr_event_recording_link":"","msr_event_link":"https:\/\/www.microsoftevents.com\/profile\/form\/index.cfm?PKformID=0x5744841abcd","msr_event_link_redirect":false,"msr_event_time":"","msr_hide_region":false,"msr_private_event":false,"msr_hide_image_in_river":0,"footnotes":""},"research-area":[13563],"msr-region":[197900],"msr-event-type":[197944],"msr-video-type":[],"msr-locale":[268875],"msr-program-audience":[],"msr-post-option":[],"msr-impact-theme":[],"class_list":["post-557697","msr-event","type-msr-event","status-publish","hentry","msr-research-area-data-platform-analytics","msr-region-north-america","msr-event-type-hosted-by-microsoft","msr-locale-en_us"],"msr_about":"\n\n

Microsoft Research
\n14820 NE 36th St., Bldg. 99
\nRedmond, WA 98052Opens in a new tab<\/span><\/p>\n

The Northwest Database Society Annual Meeting brings together researchers and practitioners from the greater Pacific Northwest for a day of technical talks and networking on the broad topic of data management systems.<\/p>\n

It will be a full-day event. There will be two keynotes, several sessions of shorter presentations by members of our community, a poster session, and significant break time for unstructured discussion. There will be breakfast, lunch, coffee breaks, and a post-conference reception, courtesy of Microsoft Research.<\/p>\n

If you plan to attend the event, then please register here<\/a>. Although there is no registration fee, you must register to attend.<\/p>\n

Keynote 1: <\/strong>“Explainable Artificial Intelligence in Precision Medicine,” Su-In Lee (UW CSE)<\/h4>\n

Modern machine learning models can accurately predict patient progress and outcomes, however, they are not interpretable in the sense that they do not explain why selected features make sense or why a particular prediction result was made. I will talk about my group’s efforts to address these challenges by developing interpretable machine learning techniques for a wide range of applications, including treating cancer based on a patient’s own molecular profile, finding therapeutic targets for Alzheimer’s, predicting chronic kidney disease, preventing complications during surgery, enabling pre-hospital predictions for trauma patients, and improving our understanding of pan-cancer biology and genome biology. Among these, I will mainly focus on our work MERGE, which uses machine learning to enable targeted treatment of acute myeloid leukemia, published in Nature Communications<\/em> last year, and our explainable artificial intelligence system, Prescience, for preventing hypoxemia in patients under anesthesia, recently featured on the cover of the most recent issue of Nature Biomedical Engineering<\/em>.<\/p>\n

Bio:\u00a0Prof. Su-In Lee<\/a> is an Associate Professor in the Paul G. Allen School of Computer Science & Engineering<\/a>, and an Adjunct Associate Professor in the Genome Sciences Department<\/a>, the Department of Electrical <\/a>Engineering<\/a> and the Department of Biomedical Informatics and Medical Education<\/a> at the University of Washington. She completed her PhD in 2009 at Stanford University<\/a> with Prof. Daphne Koller<\/a> in the Stanford Artificial Intelligence Laboratory<\/a>.\u00a0 Before joining the UW in 2010, she was a visiting professor in the Computational Biology Department<\/a> at Carnegie Mellon University<\/a>. She has received the National Science Foundation CAREER Award and been named an American Cancer Society Research Scholar.\u00a0 She has received a number of generous grants from the National Institutes of Health<\/a> (NIH), National Science Foundation<\/a> (NSF), and American Cancer Society<\/a> (ACS).<\/p>\n

Keynote 2:<\/strong> “Overlaying Distributed Database Applications over Blockchains,” Donald Kossmann & Arvind Arasu (Microsoft Research)<\/h4>\n

There has been a great deal of hype around Blockchains. The Blockchain is a set of technologies to protect the integrity of transactions in an open and scalable way. This talk argues that the core feature of Blockchains, the notion of a digital witness, is extremely useful, but that Blockchain technologies are packaged in the wrong way, thereby reinventing the wheel of databases and distributed transactions. Instead, Blockchain technologies can be integrated into existing data management systems using the existing abstractions such as SQL, stored procedures, and key-value stores. As an example, the talk shows how Blockchain and more traditional database techniques can be used in concert to manage \u201cDecentralized IDs\u201d in an open and scalable way that allows users to control the creation and usage of IDs.<\/p>\n

Bio: Donald Kossmann<\/a> is Distinguished Scientist and Director of Microsoft Research Redmond<\/a>. He works on data management in the cloud, with the goal of making data in the cloud cheaper, more valuable, and more secure. Before Microsoft, he was a professor in the Systems Group of the Department of Computer Science at ETH Zurich for 13 years, doing research and teaching all flavors of data management systems. He was chair of ACM\u00a0SIGMOD from 2013 to 2017 and served on the Board of Trustees of the VLDB Endowment from 2005 to 2011. He co-founded four companies: i-TV-T AG (1998),\u00a0XQRL Inc. (2002), 28msec Inc. (2006), and Teralytics AG (2010).<\/p>\n

Arvind Arasu<\/a> is a Senior Researcher in the Database<\/a> group at Microsoft Research<\/a>. He is currently working on database encryption in the Cipherbase project, whose goal is to enable query processing while keeping data confidential. He previously worked on data streams, information extraction, and data cleaning<\/a>.<\/p>\n

Agenda<\/strong><\/h3>\n

8-9am Breakfast: Cured meat, cheese, croissants, sliced fruit, fruit juice, and coffee & tea.<\/p>\n

Session #1:<\/strong> Video and slides<\/a><\/p>\n

9-10am Su-In Lee (University of Washington): Explainable Artificial Intelligence in Precision Medicine<\/p>\n

10:00 – 10:30 Break<\/p>\n

Session #2: <\/strong>Video and slides<\/a><\/p>\n

10:30 – 10:45 Badrish Chandramouli (Microsoft):\u00a0Open-Source Technologies for Streaming and State Management<\/p>\n

10:45 – 11:00 Jiannan Wang (Simon Fraser University): Democratize Data Preparation for AI<\/p>\n

11:00 – 11:15 Diana Popova (University of Victoria): CutTheTail<\/p>\n

11:15 – 11:30 Batya Kenig (University of Washington): Integrity Constraints Revisited: From Exact to Approximate Implication<\/p>\n

11:30 – 11:45 Gang Luo (University of Washington): Automating Machine Learning Model Building with Big Clinical Data<\/p>\n

11:45 – 12:00 Cong Yan (University of Washington):\u00a0Generating Application-Specific In-Memory Databases<\/p>\n

12:00 – 1:15 Lunch and posters (slides only)<\/p>\n

1:15 – 1:30\u00a0Kamal Gupta (AWS): Amazon Aurora<\/a> (slides only)<\/span><\/p>\n

Session #3:<\/strong> Video and slides<\/a><\/p>\n

1:30 – 1:45 Bailu Ding (Microsoft):\u00a0Improving Optimistic Concurrency Control Through Transaction Batching and Operation Reordering<\/p>\n

1:45 – 2:00 Alekh Jindal (Microsoft):\u00a0Towards a Learning Optimizer for Shared Clouds<\/p>\n

2:00 – 2:15\u00a0Amir Hormati (Google): BigQuery Machine Learning: Advanced Insights in SQL<\/p>\n

2:15 – 2:30 Mosha Pasumansky (Google): BigQuery, an Exabyte-Scale Analytical Storage System<\/p>\n

2:30 – 3:00\u00a0Break: nuts, fruit, coffee, tea, soft drinks<\/p>\n

Session #4:<\/strong> Video and slides<\/a><\/p>\n

3:00 – 3:15\u00a0Vishakha Gupta (ApertureData) & Luis Remis (Intel Labs): A Visual Data Management System<\/p>\n

3:15 – 3:30 Torsten Grabs (Snowflake): The Snowflake Engine<\/p>\n

3:30 – 4:30\u00a0 Donald Kossmann & Arvind Arasu (Microsoft): Overlaying Distributed Database Applications over Blockchains<\/p>\n

Previous Meetings<\/strong><\/h5>\n

This is the second meeting of the series. The first meeting was at University of Washington on January 5, 2018, described here<\/a>.<\/p>\n

Contact Information<\/strong><\/h5>\n

Phil Bernstein<\/a><\/p>\n

Johannes Gehrke <\/a>Opens in a new tab<\/span><\/p>\n","tab-content":[{"id":0,"name":"About","content":"The Northwest Database Society Annual Meeting brings together researchers and practitioners from the greater Pacific Northwest for a day of technical talks and networking on the broad topic of data management systems.\r\n\r\nIt will be a full-day event. There will be two keynotes, several sessions of shorter presentations by members of our community, a poster session, and significant break time for unstructured discussion. There will be breakfast, lunch, coffee breaks, and a post-conference reception, courtesy of Microsoft Research.\r\n\r\nIf you plan to attend the event, then please register here<\/a>. Although there is no registration fee, you must register to attend.\r\n

Keynote 1: <\/strong>\"Explainable Artificial Intelligence in Precision Medicine,\" Su-In Lee (UW CSE)<\/h4>\r\nModern machine learning models can accurately predict patient progress and outcomes, however, they are not interpretable in the sense that they do not explain why selected features make sense or why a particular prediction result was made. I will talk about my group's efforts to address these challenges by developing interpretable machine learning techniques for a wide range of applications, including treating cancer based on a patient's own molecular profile, finding therapeutic targets for Alzheimer's, predicting chronic kidney disease, preventing complications during surgery, enabling pre-hospital predictions for trauma patients, and improving our understanding of pan-cancer biology and genome biology. Among these, I will mainly focus on our work MERGE, which uses machine learning to enable targeted treatment of acute myeloid leukemia, published in Nature Communications<\/em> last year, and our explainable artificial intelligence system, Prescience, for preventing hypoxemia in patients under anesthesia, recently featured on the cover of the most recent issue of Nature Biomedical Engineering<\/em>.\r\n\r\nBio:\u00a0Prof. Su-In Lee<\/a> is an Associate Professor in the Paul G. Allen School of Computer Science & Engineering<\/a>, and an Adjunct Associate Professor in the Genome Sciences Department<\/a>, the Department of Electrical <\/a>Engineering<\/a> and the Department of Biomedical Informatics and Medical Education<\/a> at the University of Washington. She completed her PhD in 2009 at Stanford University<\/a> with Prof. Daphne Koller<\/a> in the Stanford Artificial Intelligence Laboratory<\/a>.\u00a0 Before joining the UW in 2010, she was a visiting professor in the Computational Biology Department<\/a> at Carnegie Mellon University<\/a>. She has received the National Science Foundation CAREER Award and been named an American Cancer Society Research Scholar.\u00a0 She has received a number of generous grants from the National Institutes of Health<\/a> (NIH), National Science Foundation<\/a> (NSF), and American Cancer Society<\/a> (ACS).\r\n

Keynote 2:<\/strong> \"Overlaying Distributed Database Applications over Blockchains,\" Donald Kossmann & Arvind Arasu (Microsoft Research)<\/h4>\r\nThere has been a great deal of hype around Blockchains. The Blockchain is a set of technologies to protect the integrity of transactions in an open and scalable way. This talk argues that the core feature of Blockchains, the notion of a digital witness, is extremely useful, but that Blockchain technologies are packaged in the wrong way, thereby reinventing the wheel of databases and distributed transactions. Instead, Blockchain technologies can be integrated into existing data management systems using the existing abstractions such as SQL, stored procedures, and key-value stores. As an example, the talk shows how Blockchain and more traditional database techniques can be used in concert to manage \u201cDecentralized IDs\u201d in an open and scalable way that allows users to control the creation and usage of IDs.\r\n\r\nBio: Donald Kossmann<\/a> is Distinguished Scientist and Director of Microsoft Research Redmond<\/a>. He works on data management in the cloud, with the goal of making data in the cloud cheaper, more valuable, and more secure. Before Microsoft, he was a professor in the Systems Group of the Department of Computer Science at ETH Zurich for 13 years, doing research and teaching all flavors of data management systems. He was chair of ACM\u00a0SIGMOD from 2013 to 2017 and served on the Board of Trustees of the VLDB Endowment from 2005 to 2011. He co-founded four companies: i-TV-T AG (1998),\u00a0XQRL Inc. (2002), 28msec Inc. (2006), and Teralytics AG (2010).\r\n\r\nArvind Arasu<\/a> is a Senior Researcher in the Database<\/a> group at Microsoft Research<\/a>. He is currently working on database encryption in the Cipherbase project, whose goal is to enable query processing while keeping data confidential. He previously worked on data streams, information extraction, and data cleaning<\/a>.\r\n

Agenda<\/strong><\/h3>\r\n8-9am Breakfast: Cured meat, cheese, croissants, sliced fruit, fruit juice, and coffee & tea.\r\n\r\nSession #1:<\/strong> Video and slides<\/a>\r\n\r\n9-10am Su-In Lee (University of Washington): Explainable Artificial Intelligence in Precision Medicine\r\n\r\n10:00 - 10:30 Break\r\n\r\nSession #2: <\/strong>Video and slides<\/a>\r\n\r\n10:30 - 10:45 Badrish Chandramouli (Microsoft):\u00a0Open-Source Technologies for Streaming and State Management\r\n\r\n10:45 - 11:00 Jiannan Wang (Simon Fraser University): Democratize Data Preparation for AI\r\n\r\n11:00 - 11:15 Diana Popova (University of Victoria): CutTheTail\r\n\r\n11:15 - 11:30 Batya Kenig (University of Washington): Integrity Constraints Revisited: From Exact to Approximate Implication\r\n\r\n11:30 - 11:45 Gang Luo (University of Washington): Automating Machine Learning Model Building with Big Clinical Data\r\n\r\n11:45 - 12:00 Cong Yan (University of Washington):\u00a0Generating Application-Specific In-Memory Databases\r\n\r\n12:00 - 1:15 Lunch and posters (slides only)\r\n\r\n1:15 - 1:30\u00a0Kamal Gupta (AWS): Amazon Aurora<\/a> (slides only)<\/span>\r\n\r\nSession #3:<\/strong> Video and slides<\/a>\r\n\r\n1:30 - 1:45 Bailu Ding (Microsoft):\u00a0Improving Optimistic Concurrency Control Through Transaction Batching and Operation Reordering\r\n\r\n1:45 - 2:00 Alekh Jindal (Microsoft):\u00a0Towards a Learning Optimizer for Shared Clouds\r\n\r\n2:00 - 2:15\u00a0Amir Hormati (Google): BigQuery Machine Learning: Advanced Insights in SQL\r\n\r\n2:15 - 2:30 Mosha Pasumansky (Google): BigQuery, an Exabyte-Scale Analytical Storage System\r\n\r\n2:30 - 3:00\u00a0Break: nuts, fruit, coffee, tea, soft drinks\r\n\r\nSession #4:<\/strong> Video and slides<\/a>\r\n\r\n3:00 - 3:15\u00a0Vishakha Gupta (ApertureData) & Luis Remis (Intel Labs): A Visual Data Management System\r\n\r\n3:15 - 3:30 Torsten Grabs (Snowflake): The Snowflake Engine\r\n\r\n3:30 - 4:30\u00a0 Donald Kossmann & Arvind Arasu (Microsoft): Overlaying Distributed Database Applications over Blockchains\r\n
Previous Meetings<\/strong><\/h5>\r\nThis is the second meeting of the series. The first meeting was at University of Washington on January 5, 2018, described here<\/a>.\r\n
Contact Information<\/strong><\/h5>\r\nPhil Bernstein<\/a>\r\n\r\nJohannes Gehrke <\/a>"}],"msr_startdate":"2019-02-08","msr_enddate":"2019-02-08","msr_event_time":"","msr_location":"Redmond, WA","msr_event_link":"https:\/\/www.microsoftevents.com\/profile\/form\/index.cfm?PKformID=0x5744841abcd","msr_event_recording_link":"","msr_startdate_formatted":"February 8, 2019","msr_register_text":"Watch now","msr_cta_link":"https:\/\/www.microsoftevents.com\/profile\/form\/index.cfm?PKformID=0x5744841abcd","msr_cta_text":"Watch now","msr_cta_bi_name":"Event Register","featured_image_thumbnail":null,"event_excerpt":"The Northwest Database Society Annual Meeting brings together researchers and practitioners from the greater Pacific Northwest for a day of technical talks and networking on the broad topic of data management systems. It will be a full-day event. There will be two keynotes, several sessions of shorter presentations by members of our community, a poster session, and significant break time for unstructured discussion. There will be breakfast, lunch, coffee breaks, and a post-conference reception, courtesy…","msr_research_lab":[199565],"related-researchers":[],"msr_impact_theme":[],"related-academic-programs":[],"related-groups":[],"related-projects":[],"related-opportunities":[],"related-publications":[],"related-videos":[],"related-posts":[],"_links":{"self":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/557697","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-event"}],"about":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-event"}],"version-history":[{"count":6,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/557697\/revisions"}],"predecessor-version":[{"id":1147062,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/557697\/revisions\/1147062"}],"wp:attachment":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/media?parent=557697"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=557697"},{"taxonomy":"msr-region","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-region?post=557697"},{"taxonomy":"msr-event-type","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-event-type?post=557697"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=557697"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=557697"},{"taxonomy":"msr-program-audience","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-program-audience?post=557697"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=557697"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=557697"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}