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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/myrandaGoesToSpace/semantic-search-datasets/blob/main/semantic_search.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Semantic Search on NOAA NCEI Data\n",
        "Myranda Uselton Shirk, NOAA NCEI Data Scientist"
      ],
      "metadata": {
        "id": "iav65aXFV0uP"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Introduction\n",
        "The National Oceanic and Atmospheric Administration's (NOAA's) National Centers for Environmental Information (NCEI) hosts one of the world's largest environmental data archives and is the US leading authority on environmental information. One large part of NCEI's role in environmental science is providing access to this data through advances in data discoverability. This notebook showcases a new method for constructing a semantic natural language search engine over NCEI data abstracts and serves as a proof of concept for any organization that wishes to provide a natural language search engine for its clients. "
      ],
      "metadata": {
        "id": "SfLHUmnbWBmz"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Methods\n",
        "\n",
        "### The Transformer Model\n",
        "[HuggingFace](www.huggingface.co) is an online community dedicated to creating and sharing state-of-the-art transformer models within the data science community. Transformer machine learning models, first proposed by Google in 2017, are natural language processing models that outperform all other models to date. The key to these models is an attribute known as attention, which allows for models to embed and understand context in written language. The model used in this notebook is the Sentence Transformer model, which computes semantic similarity for question answering and inference problems. \n"
      ],
      "metadata": {
        "id": "JJvnDmpiXJXL"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Model Application\n",
        "Because the Sentence Transformer computes semantic similarity for question answering, it is reasonable to assume that this method could be applied for semantic search over a corpus of data. In this case, a user query will be computed for similarity against semantic embeddings of NCEI dataset abstracts."
      ],
      "metadata": {
        "id": "tNptcY18YHn0"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### The Data\n",
        "The data in this notebook are sourced from NCEI's metadata portal, Geoportal, and include dataset identifiers, titles, and abstracts. The data are gathered using Catalogue Service for the Web (CSW) protocol and organized for use in Python using the Beautiful Soup library. "
      ],
      "metadata": {
        "id": "ukvM4r94YATb"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Application"
      ],
      "metadata": {
        "id": "9jG-h-dtaLR0"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Install libraries not included in Google CoLab - Sentence Transformers and BS4 (Beautiful Soup)"
      ],
      "metadata": {
        "id": "kQyhaB8vaP7K"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cMkwwzoDM4oB",
        "outputId": "7c77e709-3f44-413b-990b-11be86f529c7"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting sentence-transformers\n",
            "  Downloading sentence-transformers-2.2.2.tar.gz (85 kB)\n",
            "\u001b[K     |████████████████████████████████| 85 kB 772 kB/s \n",
            "\u001b[?25hCollecting transformers<5.0.0,>=4.6.0\n",
            "  Downloading transformers-4.24.0-py3-none-any.whl (5.5 MB)\n",
            "\u001b[K     |████████████████████████████████| 5.5 MB 27.6 MB/s \n",
            "\u001b[?25hRequirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from sentence-transformers) (4.64.1)\n",
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            "Collecting sentencepiece\n",
            "  Downloading sentencepiece-0.1.97-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.3 MB 13.2 MB/s \n",
            "\u001b[?25hCollecting huggingface-hub>=0.4.0\n",
            "  Downloading huggingface_hub-0.10.1-py3-none-any.whl (163 kB)\n",
            "\u001b[K     |████████████████████████████████| 163 kB 44.7 MB/s \n",
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            "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1\n",
            "  Downloading tokenizers-0.13.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.6 MB)\n",
            "\u001b[K     |████████████████████████████████| 7.6 MB 32.0 MB/s \n",
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            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from scikit-learn->sentence-transformers) (3.1.0)\n",
            "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.7/dist-packages (from torchvision->sentence-transformers) (7.1.2)\n",
            "Building wheels for collected packages: sentence-transformers\n",
            "  Building wheel for sentence-transformers (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sentence-transformers: filename=sentence_transformers-2.2.2-py3-none-any.whl size=125938 sha256=91c78a9708c740211d983dbd396ce519baa0e587fe8a25b40686e2721bb1b5f9\n",
            "  Stored in directory: /root/.cache/pip/wheels/bf/06/fb/d59c1e5bd1dac7f6cf61ec0036cc3a10ab8fecaa6b2c3d3ee9\n",
            "Successfully built sentence-transformers\n",
            "Installing collected packages: tokenizers, huggingface-hub, transformers, sentencepiece, sentence-transformers\n",
            "Successfully installed huggingface-hub-0.10.1 sentence-transformers-2.2.2 sentencepiece-0.1.97 tokenizers-0.13.2 transformers-4.24.0\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: bs4 in /usr/local/lib/python3.7/dist-packages (0.0.1)\n",
            "Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.7/dist-packages (from bs4) (4.6.3)\n"
          ]
        }
      ],
      "source": [
        "!pip install -U sentence-transformers\n",
        "!pip install bs4"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Load the relevant packages."
      ],
      "metadata": {
        "id": "ZLxym9goaXb0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sentence_transformers import SentenceTransformer, util\n",
        "from bs4 import BeautifulSoup"
      ],
      "metadata": {
        "id": "K6AuxpNuNJB2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Below is the example code found on the Sentence Transformer HuggingFace page on using their model."
      ],
      "metadata": {
        "id": "st7-O_GmabP0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "'''\n",
        "# Example - semantic search\n",
        "\n",
        "query = \"How many people live in London?\"\n",
        "docs = [\"Around 9 Million people live in London\", \"London is known for its financial district\"]\n",
        "\n",
        "#Load the model\n",
        "model = SentenceTransformer('sentence-transformers/multi-qa-MiniLM-L6-cos-v1')\n",
        "\n",
        "#Encode query and documents\n",
        "query_emb = model.encode(query)\n",
        "doc_emb = model.encode(docs)\n",
        "\n",
        "#Compute dot score between query and all document embeddings\n",
        "scores = util.dot_score(query_emb, doc_emb)[0].cpu().tolist()\n",
        "\n",
        "#Combine docs & scores\n",
        "doc_score_pairs = list(zip(docs, scores))\n",
        "\n",
        "#Sort by decreasing score\n",
        "doc_score_pairs = sorted(doc_score_pairs, key=lambda x: x[1], reverse=True)\n",
        "\n",
        "\n",
        "#Output passages & scores\n",
        "for doc, score in doc_score_pairs:\n",
        "    print(score, doc)\n",
        "  \n",
        "'''"
      ],
      "metadata": {
        "id": "RBJmXkeCNNG1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "outputId": "1a7a1165-2239-4a16-b676-b4846203ed4f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'\\n# Example - semantic search\\n\\nquery = \"How many people live in London?\"\\ndocs = [\"Around 9 Million people live in London\", \"London is known for its financial district\"]\\n\\n#Load the model\\nmodel = SentenceTransformer(\\'sentence-transformers/multi-qa-MiniLM-L6-cos-v1\\')\\n\\n#Encode query and documents\\nquery_emb = model.encode(query)\\ndoc_emb = model.encode(docs)\\n\\n#Compute dot score between query and all document embeddings\\nscores = util.dot_score(query_emb, doc_emb)[0].cpu().tolist()\\n\\n#Combine docs & scores\\ndoc_score_pairs = list(zip(docs, scores))\\n\\n#Sort by decreasing score\\ndoc_score_pairs = sorted(doc_score_pairs, key=lambda x: x[1], reverse=True)\\n\\n\\n#Output passages & scores\\nfor doc, score in doc_score_pairs:\\n    print(score, doc)\\n  \\n'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Write functions for obtaining abstract, title, and identifier from Geoportal CSW request."
      ],
      "metadata": {
        "id": "92A2PFf4aiL6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import requests\n",
        "\n",
        "def find_abstracts(soup):\n",
        "  #df = pd.DataFrame(columns = [\"identifier\", \"abstract\"])\n",
        "  id_list = []\n",
        "  abs_list = []\n",
        "  title_list = []\n",
        "\n",
        "  for record in soup.find_all(\"csw:record\"):\n",
        "    id = record.find(\"dc:identifier\")\n",
        "    abs = record.find(\"dct:abstract\")\n",
        "    title = record.find(\"dc:title\")\n",
        "\n",
        "    # append id and abs to df\n",
        "    #df = df.append([id.text, abs.text])\n",
        "    id_list.append(id.text)\n",
        "    title_list.append(title.text)\n",
        "\n",
        "    if abs != None:\n",
        "      abs_list.append(abs.text)\n",
        "    else:\n",
        "      abs_list.append(\"NA\")\n",
        "\n",
        "  return id_list, title_list, abs_list\n",
        "\n",
        "# Get the abstracts from Geoportal\n",
        "URL = \"https://www.ncei.noaa.gov/metadata/geoportal/opensearch?f=csw&from=0&size=5000&sort=title.sort\"\n",
        "\n",
        "page = requests.get(URL)\n",
        "soup = BeautifulSoup(page.text, \"lxml\")\n",
        "\n",
        "id_list, title_list, abs_list = find_abstracts(soup)\n",
        "df = pd.DataFrame(list(zip(id_list,title_list, abs_list)), columns = [\"identifier\", \"title\", \"abstract\"])\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "uKBtYAG4UF1P",
        "outputId": "3c49050b-77b2-496a-f461-288619cf6e68"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                               identifier  \\\n",
              "0                   gov.noaa.nodc:0000662   \n",
              "1                   gov.noaa.nodc:5400007   \n",
              "2     gov.noaa.ncei:SeaSurfaceTemperature   \n",
              "3                    gov.noaa.ncdc:C00386   \n",
              "4                    gov.noaa.ncdc:C00387   \n",
              "...                                   ...   \n",
              "4995    gov.noaa.ngdc.mgg.wcd:NA093_EM302   \n",
              "4996    gov.noaa.ngdc.mgg.wcd:NA094_EM302   \n",
              "4997    gov.noaa.ngdc.mgg.wcd:NA095_EM302   \n",
              "4998    gov.noaa.ngdc.mgg.wcd:NA096_EM302   \n",
              "4999    gov.noaa.ngdc.mgg.wcd:NA097_EM302   \n",
              "\n",
              "                                                  title  \\\n",
              "0                              (NCEI Accession 0000662)   \n",
              "1                              (NCEI Accession 5400007)   \n",
              "2                              .Sea Surface Temperature   \n",
              "3     1-Minute Page 1 Surface Weather Observations f...   \n",
              "4     1-Minute Page 2 Surface Weather Observations f...   \n",
              "...                                                 ...   \n",
              "4995  EM302 Water Column Sonar Data Collected During...   \n",
              "4996  EM302 Water Column Sonar Data Collected During...   \n",
              "4997  EM302 Water Column Sonar Data Collected During...   \n",
              "4998  EM302 Water Column Sonar Data Collected During...   \n",
              "4999  EM302 Water Column Sonar Data Collected During...   \n",
              "\n",
              "                                               abstract  \n",
              "0                                                    NA  \n",
              "1                                                    NA  \n",
              "2     Derived from processed satellite observations....  \n",
              "3     This dataset includes one-minute observations ...  \n",
              "4     This dataset includes one-minute observations ...  \n",
              "...                                                 ...  \n",
              "4995                      Nautilus Cruise NA093 (EM302)  \n",
              "4996                      Nautilus Cruise NA094 (EM302)  \n",
              "4997                      Nautilus Cruise NA095 (EM302)  \n",
              "4998                      Nautilus Cruise NA096 (EM302)  \n",
              "4999                      Nautilus Cruise NA097 (EM302)  \n",
              "\n",
              "[5000 rows x 3 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ea2843f1-b960-42eb-a731-02ea072d0528\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>identifier</th>\n",
              "      <th>title</th>\n",
              "      <th>abstract</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>gov.noaa.nodc:0000662</td>\n",
              "      <td>(NCEI Accession 0000662)</td>\n",
              "      <td>NA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>gov.noaa.nodc:5400007</td>\n",
              "      <td>(NCEI Accession 5400007)</td>\n",
              "      <td>NA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>gov.noaa.ncei:SeaSurfaceTemperature</td>\n",
              "      <td>.Sea Surface Temperature</td>\n",
              "      <td>Derived from processed satellite observations....</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>gov.noaa.ncdc:C00386</td>\n",
              "      <td>1-Minute Page 1 Surface Weather Observations f...</td>\n",
              "      <td>This dataset includes one-minute observations ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>gov.noaa.ncdc:C00387</td>\n",
              "      <td>1-Minute Page 2 Surface Weather Observations f...</td>\n",
              "      <td>This dataset includes one-minute observations ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4995</th>\n",
              "      <td>gov.noaa.ngdc.mgg.wcd:NA093_EM302</td>\n",
              "      <td>EM302 Water Column Sonar Data Collected During...</td>\n",
              "      <td>Nautilus Cruise NA093 (EM302)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4996</th>\n",
              "      <td>gov.noaa.ngdc.mgg.wcd:NA094_EM302</td>\n",
              "      <td>EM302 Water Column Sonar Data Collected During...</td>\n",
              "      <td>Nautilus Cruise NA094 (EM302)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4997</th>\n",
              "      <td>gov.noaa.ngdc.mgg.wcd:NA095_EM302</td>\n",
              "      <td>EM302 Water Column Sonar Data Collected During...</td>\n",
              "      <td>Nautilus Cruise NA095 (EM302)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4998</th>\n",
              "      <td>gov.noaa.ngdc.mgg.wcd:NA096_EM302</td>\n",
              "      <td>EM302 Water Column Sonar Data Collected During...</td>\n",
              "      <td>Nautilus Cruise NA096 (EM302)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4999</th>\n",
              "      <td>gov.noaa.ngdc.mgg.wcd:NA097_EM302</td>\n",
              "      <td>EM302 Water Column Sonar Data Collected During...</td>\n",
              "      <td>Nautilus Cruise NA097 (EM302)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5000 rows × 3 columns</p>\n",
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          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Make the abstracts the docs\n",
        "docs_df = df[df[\"abstract\"] != \"NA\"]\n",
        "docs = list(docs_df[\"abstract\"])\n",
        "titles = list(docs_df[\"title\"])"
      ],
      "metadata": {
        "id": "65HOmLouzL-i"
      },
      "execution_count": null,
      "outputs": []
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    {
      "cell_type": "markdown",
      "source": [
        "Load the Sentence Transformers model and embed the dataset abstracts."
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      "metadata": {
        "id": "rWy_FjePapMw"
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    },
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      "cell_type": "code",
      "source": [
        "#Load the model\n",
        "model = SentenceTransformer('sentence-transformers/multi-qa-MiniLM-L6-cos-v1')\n",
        "\n",
        "doc_emb = model.encode(docs)\n"
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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Save the abstract embeddings in a file. This allows the search engine manager to only compute the embeddings for the data corpus once."
      ],
      "metadata": {
        "id": "KjV5yAVhauUA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "np.save(\"doc_emb\", doc_emb)"
      ],
      "metadata": {
        "id": "vAoR_2OsSwiY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "doc_emb_saved = np.load(\"doc_emb.npy\")\n",
        "doc_emb_saved"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jDBoQv4gUHHd",
        "outputId": "4e5039a5-78b0-4a7b-d896-5c99d42e460e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 6.94027185e-05,  3.76847200e-02,  1.30539024e-02, ...,\n",
              "         3.56099494e-02, -1.13519669e-01, -1.43111013e-02],\n",
              "       [ 4.22849096e-02, -3.21854278e-02, -3.11591253e-02, ...,\n",
              "         4.74197939e-02, -1.07490636e-01, -3.00586899e-03],\n",
              "       [-6.01339852e-03, -2.23910846e-02, -4.13601585e-02, ...,\n",
              "         5.25129661e-02, -1.01892620e-01, -3.97650823e-02],\n",
              "       ...,\n",
              "       [-5.70231751e-02,  8.11418425e-03,  3.22012976e-02, ...,\n",
              "         1.98791665e-03, -2.65017198e-03,  5.94463907e-02],\n",
              "       [-5.81365339e-02,  1.32378815e-02,  2.05236133e-02, ...,\n",
              "         6.04736293e-03, -2.20852275e-03,  5.79196922e-02],\n",
              "       [-5.61661944e-02,  1.02252932e-02,  1.95322707e-02, ...,\n",
              "        -1.23474875e-03, -7.81550724e-03,  6.14073277e-02]], dtype=float32)"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Ask the user to enter a query, then compute its similarity against the previously embedded abstracts."
      ],
      "metadata": {
        "id": "ZS9Gw9nFa4yv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Query\n",
        "query = input(\"Enter your query: \")\n",
        "\n",
        "#Encode query and documents\n",
        "query_emb = model.encode(query)\n",
        "\n",
        "# predict on a search query for data\n",
        "\n",
        "\n",
        "#Compute dot score between query and all document embeddings\n",
        "scores = util.dot_score(query_emb, doc_emb_saved)[0].cpu().tolist()\n",
        "\n",
        "#Combine docs & scores\n",
        "doc_score_pairs = list(zip(docs, scores, titles))\n",
        "\n",
        "#Sort by decreasing score\n",
        "doc_score_pairs = sorted(doc_score_pairs, key=lambda x: x[1], reverse=True)\n",
        "\n",
        "\n",
        "#Output passages & scores\n",
        "for doc, score, title in doc_score_pairs[:10]:\n",
        "    print(\"Score: %f\" %score)\n",
        "    print(\"Title: %s\" %title)\n",
        "    print(\"Abstract: %s\" %doc)\n",
        "    print('\\n')"
      ],
      "metadata": {
        "id": "f0_yph9dP6HW",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bfc7d68a-ee7a-4538-f57f-89a688b4d3e3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Enter your query: coral health in Atlantic ocean\n",
            "Score: 0.607544\n",
            "Title: EK60 Water Column Sonar Data Collected During HB1402\n",
            "Abstract: Deep Water Coral (HB1402, EK60). The cruise will survey and collect samples of deep-sea corals and related marine life in the canyons in the northern Gulf of Maine in U.S. and Canadian waters. The U.S. and Canadian scientists (National Systematics Laboratory at NOAA’s Northeast Fisheries Science Center; Dalhousie University in Halifax, Nova Scotia) will work aboard the NOAA Ship Henry B. Bigelow. They will use a remotedly operated vehicle (ROV) owned by Canada. Called the Remotely Operated Platform for Ocean Science-- ROPOS for short -- the vehicle can record images and sample water, sediments, and marine life using sampling gear operated from the ship by ROPOS pilots. The sites to be sampled range from 200 to 3000 meters deep, or roughly 650 to 10,000 feet deep. The ROPOS generally works in the Pacific Ocean, and this cruise marks the first time the vehicle has been used for coral research in U.S.Atlantic waters.\n",
            "\n",
            "\n",
            "Score: 0.607359\n",
            "Title: EM122 Water Column Sonar Data Collected During AT26-14\n",
            "Abstract: AT26-14 Acid Horizon: Physiological and Genetic Responses of Deep-water Corals to Ocean Acidification (EM122)\n",
            "\n",
            "\n",
            "Score: 0.597548\n",
            "Title: Digital Video taken during the 3-person submersible Clelia dive 621 of the NOAA Office of Ocean Exploration's Islands in the Stream 2001 cruise, 2001-09-05 (NCEI Accession 0039428)\n",
            "Abstract: Islands in the Stream is a three-month scientific expedition to marine protected areas and other habitats being considered for protection from offshore of Belize in Central America to North Carolina’s continental shelf. \"Islands” are the coral reefs and hard-bottom (also called “hard substrate”) biological communities found along the course of a massive “stream” of ocean currents connecting the Caribbean Sea, the Gulf of Mexico, and the western Atlantic off North America. This expedition emphasizes habitat characterization and an understanding of these islands' \"connection\" as parts of an interrelated ecosystem. Though separated by large expanses of ocean water, the fishes, corals, and invertebrates common to these islands may demonstrate that the health and vitality of “downstream” islands are linked closely to those located “upstream.\"\n",
            "\n",
            "From August to October, scientists explored the deep reef and hard-bottom communities of the South Atlantic Bight, from the east coast of Florida through the North Carolina Shelf. Leg One of this mission, lasting from August 29 to September 7, visited the Oculina Bank, situated 30 km (18 mi) east of the northern Florida coast. Oculina Bank was the first deep-water site in federal waters off the U.S. Eastern Seaboard to be closed to fishing. Once, this area was covered with dense thickets of the ivory tree coral, Oculina varicosa, which provided excellent habitat for reef fish, such as grouper and wreckfish, and feeding grounds for migratory pelagic (deep-sea) species. However, fishing activities destroyed approximately two-thirds of the bank. A fragile and slow-growing coral, deep-water Oculina only grows about one-half inch per year. These and other damaged coral reefs will take many years, even decades, to recover. To aid in the recovery process, a significant portion of the area was closed to fishing in 1994. NOAA has since funded efforts to assess the banks and to attempt to restore the damaged areas. In July 2000, the National Marine Fisheries Service approved plans to expand the protected area, with the goal of saving the remaining ivory tree coral. Much of the protected area is deeper than 100 m (328 ft), rugged, and can only be studied using advanced undersea technologies. The mission will use the HBOI submersible Clelia and an ROV to study the recovery of the reserve. In addition to habitat characterization work, visual observations of artificial-reef restoration structures deployed on the banks beginning in 1995 will help to determine species' rates of recruitment. Scientists will also test a hydrophone array to determine its utility for monitoring grouper spawning.\n",
            "\n",
            "\n",
            "Score: 0.592596\n",
            "Title: Continental Slope Coral Banks of the Southeastern United States: Exploring the Distribution, Ecology, and Biology of Deep Coral Habitats and Associated Fauna 2005\n",
            "Abstract: Deep coral habitats are more extensive and important than previously known, and at the same time they are being threatened. These high profile features may concentrate exploitable resources and enhance local productivity in ways similar to seamounts, but this has not yet been explored. Even though hypotheses have been posed on how coral banks form, data are lacking. Live coral ages and growth rates are poorly known in this area, and ages of coral mounds or dead coral stands are also limited or equivocal. The degree to which there is an obligate deep coral fauna is unclear. While the genetic structure of Lophelia in the northeastern Atlantic is being described, such studies are just beginning in the western Atlantic. It is for these reasons that locating, describing, and mapping deep corals and conducting basic biological studies in these habitats are priorities for our research. On our previous cruises, we have documented deep coral and outer shelf reef habitats and associated biota. However, these missions have only begun to quantify this extensive habitat off the southeastern US (SEUS). Our studies have also yielded many new records of biota, new ecological data, new data on habitat distributions/structures, and data on water column trophic connectivity. This cruise continues and expands our explorations of these unique and relatively unknown deep-water habitats.\n",
            "\n",
            "\n",
            "Score: 0.589673\n",
            "Title: Digital video, still imagery and dive narratives from the NOAA Office of Ocean Exploration's South Atlantic Bight 2001 cruises from 2001-08-29 to 2001-09-07\n",
            "Abstract: This collection contains digital video imagery, digital still imagery, and dive narratives from the NOAA Office of Ocean Exploration's South Atlantic Bight cruises, part of the Islands in the Stream 2001 expedition.\n",
            "\n",
            "Islands in the Stream 2001 is a three-month scientific expedition to marine protected areas and other habitats being considered for protection from offshore of Belize in Central America to North Carolina's continental shelf. \"Islands” are the coral reefs and hard-bottom (also called \"hard substrate\") biological communities found along the course of a massive \"stream\" of ocean currents connecting the Caribbean Sea, the Gulf of Mexico, and the western Atlantic off North America. This expedition emphasizes habitat characterization and an understanding of these islands' \"connection\" as parts of an interrelated ecosystem. Though separated by large expanses of ocean water, the fishes, corals, and invertebrates common to these islands may demonstrate that the health and vitality of \"downstream\" islands are linked closely to those located \"upstream.\"\n",
            "\n",
            "From August to October 2001, scientists explored the deep reef and hard-bottom communities of the South Atlantic Bight, from the east coast of Florida through the North Carolina Shelf. Leg One of this mission, lasting from August 29 to September 7, visited the Oculina Bank, situated 30 km (18 mi) east of the northern Florida coast. Oculina Bank was the first deep-water site in federal waters off the U.S. Eastern Seaboard to be closed to fishing. Once, this area was covered with dense thickets of the ivory tree coral, Oculina varicosa, which provided excellent habitat for reef fish, such as grouper and wreckfish, and feeding grounds for migratory pelagic (deep-sea) species. However, fishing activities destroyed approximately two-thirds of the bank. A fragile and slow-growing coral, deep-water Oculina only grows about one-half inch per year. These and other damaged coral reefs will take many years, even decades, to recover. To aid in the recovery process, a significant portion of the area was closed to fishing in 1994. NOAA has since funded efforts to assess the banks and to attempt to restore the damaged areas. In July 2000, the National Marine Fisheries Service approved plans to expand the protected area, with the goal of saving the remaining ivory tree coral. Much of the protected area is deeper than 100 m (328 ft), rugged, and can only be studied using advanced undersea technologies. The mission will use the HBOI submersible Clelia and an ROV to study the recovery of the reserve. In addition to habitat characterization work, visual observations of artificial-reef restoration structures deployed on the banks beginning in 1995 will help to determine species' rates of recruitment. Scientists will also test a hydrophone array to determine its utility for monitoring grouper spawning.\n",
            "\n",
            "\n",
            "Score: 0.575535\n",
            "Title: Dissolved inorganic carbon, total alkalinity, pH on Total Scale, nutrients and other variables collected from profile and discrete sample observations using CTD, Niskin bottle and other instruments during the R/V Hugh R. Sharp cruise S11802 (EXPOCODE 33H520181102) in the North Atlantic Ocean, Gulf of Maine, Georges Bank, and Mid-Atlantic Bight from 2018-11-02 to 2018-11-12 (NCEI Accession 0189039)\n",
            "Abstract: This dataset contains dissolved inorganic carbon, total alkalinity, pH on total scale, nutrients and other variables measured from profile discrete observations during the R/V Hugh R. Sharp cruise S11802 (EXPOCODE 33H520181102) in the North Atlantic Ocean, Gulf of Maine, Georges Bank, and Mid-Atlantic Bight from 2018-11-02 to 2018-11-12. Increasing amounts of atmospheric carbon dioxide from human industrial activities are causing changes in global ocean carbon chemistry ultimately resulting in a reduction in pH, a process termed ocean acidification. Studies have demonstrated adverse effects on calcifying organisms, particularly some invertebrates, corals, sea urchins, pteropods, and coccolithophores, but also on species of commercial interest such as oysters or crabs. In support of the coastal monitoring and research objectives of the NOAA Ocean Acidification Program (OAP), the Ecosystem Monitoring Cruises (ECOMON) are utilized to collect water samples to measure water column inorganic carbon and hydrographic parameters including nutrients. Samples are collected at three depths (surface, mid-depth and near bottom) at select stations on a quarterly basis in the northeastern Atlantic continental shelf region of the United States. Water samples are sent to and analyzed by scientists at the Atlantic Oceanographic and Meteorological Laboratory (AOML) for dissolved inorganic carbon, pH and total alkalinity concentrations. Additional samples are analyzed for nutrient concentrations at the University of Maine. These data are used to monitor short-long term coastal ocean acidification trends.\n",
            "\n",
            "\n",
            "Score: 0.573351\n",
            "Title: Dissolved inorganic carbon (DIC), total alkalinity, pH on total scale, nutrients and other variables collected from profile and discrete samples observations during NOAA Ship Pisces cruise PC2106 (EXPOCODE 334B20211015) in the North Atlantic Ocean, Gulf of Maine, Georges Bank, Mid-Atlantic Bight from 2021-10-15 to 2021-10-25 (NCEI Accession 0249517)\n",
            "Abstract: This dataset contains dissolved inorganic carbon, total alkalinity, pH on total scale, nutrients and other variables measured from profile discrete observations during NOAA Ship Pisces cruise PC2106 (EXPOCODE 334B20211015) in the North Atlantic Ocean, Gulf of Maine, Georges Bank, Mid-Atlantic Bight from 2021-10-15 to 2021-10-25. Increasing amounts of atmospheric carbon dioxide from human industrial activities are causing changes in global ocean carbon chemistry ultimately resulting in a reduction in pH, a process termed ocean acidification. Studies have demonstrated adverse effects on calcifying organisms, particularly some invertebrates, corals, sea urchins, pteropods, and coccolithophores, but also on species of commercial interest such as oysters or crabs. In support of the coastal monitoring and research objectives of the NOAA Ocean Acidification Program (OAP), the Ecosystem Monitoring Cruises (ECOMON) are utilized to collect water samples to measure water column inorganic carbon and hydrographic parameters including nutrients. Samples are collected at three depths (surface, mid-depth and near bottom) at select stations on a quarterly basis in the northeastern Atlantic continental shelf region off the United States. Water samples are sent to and analyzed by scientists at the Atlantic Oceanographic and Meteorological Laboratory (AOML) for dissolved inorganic carbon, pH and total alkalinity concentrations. Additional samples are analyzed for nutrient concentrations at the University of Maine. These data are used to monitor short-long term coastal ocean acidification trends.\n",
            "\n",
            "\n",
            "Score: 0.568581\n",
            "Title: Dissolved inorganic carbon (DIC), total alkalinity, pH on total scale, nutrients and other variables collected from profile and discrete samples observations during NOAA Ship Pisces cruise PC2104 (EXPOCODE 334B20210805) in the North Atlantic Ocean, Gulf of Maine, Georges Bank, Mid-Atlantic Bight from 2021-08-06 to 2021-08-18 (NCEI Accession 0249432)\n",
            "Abstract: This dataset contains dissolved inorganic carbon, total alkalinity, pH on total scale, nutrients and other variables measured from profile discrete observations during NOAA Ship Pisces cruise PC2104 (EXPOCODE 334B20210805) in the North Atlantic Ocean, Gulf of Maine, Georges Bank, Mid-Atlantic Bight from 2021-08-06 to 2021-08-18. Increasing amounts of atmospheric carbon dioxide from human industrial activities are causing changes in global ocean carbon chemistry ultimately resulting in a reduction in pH, a process termed ocean acidification. Studies have demonstrated adverse effects on calcifying organisms, particularly some invertebrates, corals, sea urchins, pteropods, and coccolithophores, but also on species of commercial interest such as oysters or crabs. In support of the coastal monitoring and research objectives of the NOAA Ocean Acidification Program (OAP), the Ecosystem Monitoring Cruises (ECOMON) are utilized to collect water samples to measure water column inorganic carbon and hydrographic parameters including nutrients. Samples are collected at three depths (surface, mid-depth and near bottom) at select stations on a quarterly basis in the northeastern Atlantic continental shelf region off the United States. Water samples are sent to and analyzed by scientists at the Atlantic Oceanographic and Meteorological Laboratory (AOML) for dissolved inorganic carbon, pH and total alkalinity concentrations. Additional samples are analyzed for nutrient concentrations at the University of Maine. These data are used to monitor short-long term coastal ocean acidification trends.\n",
            "\n",
            "\n",
            "Score: 0.566784\n",
            "Title: Dissolved inorganic carbon, total alkalinity, water temperature, salinity and other variables collected from surface discrete observations using flow through pump and other instruments during the Ship of Opportunity Reykjafoss cruise Reykjafoss_2010 (EXPOCODE 64RJ20100821), in the North Atlantic ocean from 2010-08-21 to 2010-08-24 (NCEI Accession 0239882)\n",
            "Abstract: This dataset contains surface discrete measurements of dissolved inorganic carbon, total alkalinity, water temperature, salinity and other variables collected from surface discrete observations using flow through pump and other instruments during the Ship of Opportunity Reykjafoss cruise Reykjafoss_2010 (EXPOCODE 64RJ20100821), in the North Atlantic ocean from 2010-08-21 to 2010-08-24. Increasing amounts of atmospheric carbon dioxide from human industrial activities are causing changes in global ocean carbon chemistry. Through the SOOP program we measure air and ocean surface pCO2 and take discrete samples of other carbon parameters. This effort is in support of the coastal monitoring and research objectives of the NOAA Ocean Acidification Program (OAP) and the Climate Program Office.\n",
            "\n",
            "\n",
            "Score: 0.566051\n",
            "Title: Dissolved inorganic carbon, water temperature, salinity, dissolved oxygen, nutrients, and other variables collected from discrete profile observations during the R/V Cape Hatteras cruise CapeHatteras_2006 (EXPOCODE 32KZ20060517), in the North Atlantic ocean from 2006-05-17 to 2006-05-26 (NCEI Accession 0240004)\n",
            "Abstract: This dataset contains surface discrete measurements of dissolved inorganic carbon, water temperature, salinity, dissolved oxygen, nutrients, and other variables collected from discrete profile observations during the R/V Cape Hatteras cruise CapeHatteras_2006 (EXPOCODE 32KZ20060517), in the North Atlantic ocean from 2006-05-17 to 2006-05-26. Increasing amounts of atmospheric carbon dioxide from human industrial activities are causing changes in global ocean carbon chemistry resulting in a reduction in pH, a process termed ocean acidification. In support of the coastal monitoring and research objectives of the NOAA Ocean Acidification Program (OAP), the South Florida Project Cruises (SFP) are utilized to collect water samples to measure water inorganic carbon and hydrographic parameters including nutrients.\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Print the results in a more readable format."
      ],
      "metadata": {
        "id": "XMSVpQt6a_6I"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from IPython.display import HTML, display\n",
        "\n",
        "def set_css():\n",
        "  display(HTML('''\n",
        "  <style>\n",
        "    pre {\n",
        "        white-space: pre-wrap;\n",
        "    }\n",
        "  </style>\n",
        "  '''))\n",
        "get_ipython().events.register('pre_run_cell', set_css)"
      ],
      "metadata": {
        "id": "YiFMLlNzeoyr"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Output passages & scores\n",
        "for doc, score, title in doc_score_pairs[:10]:\n",
        "    print(\"Score: %f\" %score)\n",
        "    print(\"Title: %s\" %title)\n",
        "    print(\"Abstract: %s\" %doc)\n",
        "    print('\\n')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "tFJyWME238nC",
        "outputId": "b9279ac2-321f-4aee-8d44-473ed200d0fa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "  <style>\n",
              "    pre {\n",
              "        white-space: pre-wrap;\n",
              "    }\n",
              "  </style>\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Score: 0.595809\n",
            "Title: Digital Video taken during the 3-person submersible Clelia dive 621 of the NOAA Office of Ocean Exploration's Islands in the Stream 2001 cruise, 2001-09-05 (NCEI Accession 0039428)\n",
            "Abstract: Islands in the Stream is a three-month scientific expedition to marine protected areas and other habitats being considered for protection from offshore of Belize in Central America to North Carolina’s continental shelf. \"Islands” are the coral reefs and hard-bottom (also called “hard substrate”) biological communities found along the course of a massive “stream” of ocean currents connecting the Caribbean Sea, the Gulf of Mexico, and the western Atlantic off North America. This expedition emphasizes habitat characterization and an understanding of these islands' \"connection\" as parts of an interrelated ecosystem. Though separated by large expanses of ocean water, the fishes, corals, and invertebrates common to these islands may demonstrate that the health and vitality of “downstream” islands are linked closely to those located “upstream.\"\n",
            "\n",
            "From August to October, scientists explored the deep reef and hard-bottom communities of the South Atlantic Bight, from the east coast of Florida through the North Carolina Shelf. Leg One of this mission, lasting from August 29 to September 7, visited the Oculina Bank, situated 30 km (18 mi) east of the northern Florida coast. Oculina Bank was the first deep-water site in federal waters off the U.S. Eastern Seaboard to be closed to fishing. Once, this area was covered with dense thickets of the ivory tree coral, Oculina varicosa, which provided excellent habitat for reef fish, such as grouper and wreckfish, and feeding grounds for migratory pelagic (deep-sea) species. However, fishing activities destroyed approximately two-thirds of the bank. A fragile and slow-growing coral, deep-water Oculina only grows about one-half inch per year. These and other damaged coral reefs will take many years, even decades, to recover. To aid in the recovery process, a significant portion of the area was closed to fishing in 1994. NOAA has since funded efforts to assess the banks and to attempt to restore the damaged areas. In July 2000, the National Marine Fisheries Service approved plans to expand the protected area, with the goal of saving the remaining ivory tree coral. Much of the protected area is deeper than 100 m (328 ft), rugged, and can only be studied using advanced undersea technologies. The mission will use the HBOI submersible Clelia and an ROV to study the recovery of the reserve. In addition to habitat characterization work, visual observations of artificial-reef restoration structures deployed on the banks beginning in 1995 will help to determine species' rates of recruitment. Scientists will also test a hydrophone array to determine its utility for monitoring grouper spawning.\n",
            "\n",
            "\n",
            "Score: 0.587593\n",
            "Title: Acropora Spatial Survey Data of the Upper Florida Keys National Marine Sanctuary, 2005 - 2007 (NCEI Accession 0046934)\n",
            "Abstract: These data were collected by the NOAA Southeast Fisheries Science Center to document the presence or absence of Acropora spp at shallow reef sites in the Upper Florida Keys (USA).  The presence or absence of acroporid corals was marked by handheld GPS during snorkel or tow surveys of shallow water (<5m) reef habitats in the Upper Florida Keys National Marine Sanctuary.  The data are in GIS shape and layer files with associated attribute files, metadata files, and additional .pdf file outputs of the GIS data layers.\n",
            "\n",
            "\n",
            "Score: 0.584066\n",
            "Title: Digital video, still imagery and dive narratives from the NOAA Office of Ocean Exploration's South Atlantic Bight 2001 cruises from 2001-08-29 to 2001-09-07\n",
            "Abstract: This collection contains digital video imagery, digital still imagery, and dive narratives from the NOAA Office of Ocean Exploration's South Atlantic Bight cruises, part of the Islands in the Stream 2001 expedition.\n",
            "\n",
            "Islands in the Stream 2001 is a three-month scientific expedition to marine protected areas and other habitats being considered for protection from offshore of Belize in Central America to North Carolina's continental shelf. \"Islands” are the coral reefs and hard-bottom (also called \"hard substrate\") biological communities found along the course of a massive \"stream\" of ocean currents connecting the Caribbean Sea, the Gulf of Mexico, and the western Atlantic off North America. This expedition emphasizes habitat characterization and an understanding of these islands' \"connection\" as parts of an interrelated ecosystem. Though separated by large expanses of ocean water, the fishes, corals, and invertebrates common to these islands may demonstrate that the health and vitality of \"downstream\" islands are linked closely to those located \"upstream.\"\n",
            "\n",
            "From August to October 2001, scientists explored the deep reef and hard-bottom communities of the South Atlantic Bight, from the east coast of Florida through the North Carolina Shelf. Leg One of this mission, lasting from August 29 to September 7, visited the Oculina Bank, situated 30 km (18 mi) east of the northern Florida coast. Oculina Bank was the first deep-water site in federal waters off the U.S. Eastern Seaboard to be closed to fishing. Once, this area was covered with dense thickets of the ivory tree coral, Oculina varicosa, which provided excellent habitat for reef fish, such as grouper and wreckfish, and feeding grounds for migratory pelagic (deep-sea) species. However, fishing activities destroyed approximately two-thirds of the bank. A fragile and slow-growing coral, deep-water Oculina only grows about one-half inch per year. These and other damaged coral reefs will take many years, even decades, to recover. To aid in the recovery process, a significant portion of the area was closed to fishing in 1994. NOAA has since funded efforts to assess the banks and to attempt to restore the damaged areas. In July 2000, the National Marine Fisheries Service approved plans to expand the protected area, with the goal of saving the remaining ivory tree coral. Much of the protected area is deeper than 100 m (328 ft), rugged, and can only be studied using advanced undersea technologies. The mission will use the HBOI submersible Clelia and an ROV to study the recovery of the reserve. In addition to habitat characterization work, visual observations of artificial-reef restoration structures deployed on the banks beginning in 1995 will help to determine species' rates of recruitment. Scientists will also test a hydrophone array to determine its utility for monitoring grouper spawning.\n",
            "\n",
            "\n",
            "Score: 0.565915\n",
            "Title: Community Structure of Fish and Macrobenthos at Selected Sites in the Vicinity of Mokapu Ocean Outfall, Oahu, Hawaii, 1998 (NCEI Accession 0000173)\n",
            "Abstract: This report provides the results of the first quantitative survey of the coral reef communities in the vicinity of the Mokapu Ocean Outfall in Kailua Bay, Oahu, Hawaii. This survey, conducted in April and July 1998, focuses on benthic and fish community structure and is designed to detect community changes that may be mediated by the release of treated sewage through the outfall. The Kailua Regional Wastewater Treatment Plant (WWTP), which has been operational since 1977, releases a little more than 13 mgd of secondary treated sewage through a 1.55-km-long discharge pipe at a depth of 32 m. If impacts are occurring to marine communities from a point-source discharge, their effects will be most evident in proximity to the source and less obvious with distance from the source. The sampling strategy used in this study focuses on quantifying the degree of development of marine communities adjacent to and at distances from the discharge source. This strategy should allow delineation of impacts if they are occurring. The results of this first survey indicate that the marine communities in the study area are diverse, with well-developed fish and coral components. This is particularly evident on the Mokapu Ocean Outfall diffuser (Transect T-1) where a high-biomass, diverse fish community occurs. This well-developed fish community is related to the shelter created by the diffuser pipe and basalt armor rock, as well as to the release of organic particles in the treated effluent which serve as a food resource for some fish species. The development of corals as measured in terms of live coverage in the diffuser pipe community is about half that found at the more distant sampling sites. However, a second sampling site (Transect T-2) located parallel to and 15 m away from the diffuser has coral coverage very similar to that found elsewhere in Kailua Bay. These data suggest that if the operation of the Kailua Regional WWTP is having an impact on marine communities, it is very limited in scope and  scale.\n",
            "\n",
            "\n",
            "Score: 0.560247\n",
            "Title: EK60 Water Column Sonar Data Collected During HB1402\n",
            "Abstract: Deep Water Coral (HB1402, EK60). The cruise will survey and collect samples of deep-sea corals and related marine life in the canyons in the northern Gulf of Maine in U.S. and Canadian waters. The U.S. and Canadian scientists (National Systematics Laboratory at NOAA’s Northeast Fisheries Science Center; Dalhousie University in Halifax, Nova Scotia) will work aboard the NOAA Ship Henry B. Bigelow. They will use a remotedly operated vehicle (ROV) owned by Canada. Called the Remotely Operated Platform for Ocean Science-- ROPOS for short -- the vehicle can record images and sample water, sediments, and marine life using sampling gear operated from the ship by ROPOS pilots. The sites to be sampled range from 200 to 3000 meters deep, or roughly 650 to 10,000 feet deep. The ROPOS generally works in the Pacific Ocean, and this cruise marks the first time the vehicle has been used for coral research in U.S.Atlantic waters.\n",
            "\n",
            "\n",
            "Score: 0.559495\n",
            "Title: Community structure of fish and macrobenthos at selected sites fronting Sand Island, Oahu, Hawaii in relation to the Sand Island Deep Ocean Sewage Outfall, 1990 - 1998 (NCEI Accession 0000177)\n",
            "Abstract: This report provides the results of nine years of an annual quantitative monitoring of shallow marine communities inshore of the Sand Island Ocean Outfall, Oahu, Hawaii. This monitoring effort focuses on benthic and fish community structure and is designed to detect changes in these communities. Marine communities offshore of Honolulu have received considerable perturbation over the last 100 years. Dumping of raw sewage in shallow water, which occurred from 1955 to 1977, was halted in 1978; however, point and nonpoint sources of pollution from both urban activities and industry continue. All of these disturbances may serve to obscure any impacts that may be caused by treated effluent discharged from the deep-ocean outfall. The marine communities show a considerable range in development that is probably related to historical impacts. Stations have been located to take advantage of these gradients. Analysis of the nine years of data showed that there has been no statistically significant change in any of the biological parameters measured in this study other than for the mean number of invertebrate species and numbers of individual invertebrates encountered per transect. In these cases the data for 1998 showed significantly greater numbers of species and individuals over other years. These changes are probably the result of higher than usual counts of the Christmas tree worm Spirobranchus giganteus corniculatus as well as just more invertebrate species present at most stations. All other measures of the communities in this study (i.e., percent coral cover, number of coral species, number of fish species, total number of fishes counted, and the biomass of fishes present at each station) showed no significant changes through the period of this study. Hurricane Iniki, which occurred in September 1992, impacted marine communities along the south shore of Oahu. Coral communities received considerable damage, especially at the westernmost study station. Recovery in these communities is evident from the six years of data collected since the storm. Thus far, this study has not detected a quantifiable negative impact from the operation of the Sand Island Ocean Outfall.\n",
            "\n",
            "\n",
            "Score: 0.558580\n",
            "Title: EM122 Water Column Sonar Data Collected During AT26-14\n",
            "Abstract: AT26-14 Acid Horizon: Physiological and Genetic Responses of Deep-water Corals to Ocean Acidification (EM122)\n",
            "\n",
            "\n",
            "Score: 0.548057\n",
            "Title: Digital video data and temperature, salinity and other physical data taken during the NOAA Office of Ocean Exploration's Florida Coast Deep Corals 2005 cruise from 2005-11-07 to 2005-11-21\n",
            "Abstract: These video data as well as temperature, salinity and other physical data were collected during the Florida Coast Deep Corals mission of 2005. The data gathered during this expedition provided a strong foundation of information on the deep-water coral ecosystems off the Florida coast. The expedition was sponsored by the NOAA Office of Ocean Exploration.\n",
            "\n",
            "With the continuing global depletion of coastal fisheries, commercial fishing vessels are moving into deeper water and exploiting fish and crustacean species that are frequently associated with complex coral structures. Deep-sea coral ecosystems (DSCE) exist at numerous locations around the coast of Florida. These coral communities provide habitat for relatively unknown but highly diverse assemblages of fish and invertebrates, many of which are undoubtedly undescribed species. There is therefore an urgent need to identify these coral habitats, map their distribution and abundance, and document any potentially valuable fishery species associated with them. Resource managers can use this information to develop conservation policy and scientists can use it as a foundation for hypothesis driven ecological and physiological research. Since deepwater reefs are not visible to the general public, dissemination of information through the media and the education system is vital in order to create empathy for their protection. The overarching objective of this proposal is to increase the current understanding of deep-water coral habitats along Florida's coasts. Unlike shallow water tropical reefs, deep-water reefs are not well known.\n",
            "\n",
            "\n",
            "Score: 0.544877\n",
            "Title: A survey of selected coral and fish assemblages near the Waianae Ocean Outfall, Oahu, Hawaii, 1990-1999 (NCEI Accession 0000794)\n",
            "Abstract: During 1990-1999, coral growth and fish abundance were monitored at stations located at and in the vicinity of the Waianae Ocean Outfall. Comparisons of results with fish surveys showed no significant differences in the species composition or relative abundances of fish populations at Station W-2 (the sunken ship Mahi), which is located 1.2 km south of the diffuser. Fish abundance and species richness increased at Station W- 3, which is located at the diffuser, from 1990 to 1995, decreased in 1996, and increased again in 1997 through 1999. At Station WW, an inshore station located 0.8 km from shore, fish were abundant and speciose on the armor rock covering the pipeline. The fish species seen inshore are comparable to fish species seen in similar (boulder) natural biotopes around Hawaii. There were no significant differences in total mean coral cover at selected quadrats from 1994 to 1999 at Station W-2. However, there was a significant increase (approximately 8%) in total mean coral cover at this station from 1991 to 1999. At the diffuser, corals were seen growing on the diffuser pipe and on the riser discharge ports. In 1986, when the diffuser began operation at a discharge rate of 1.5 mgd (0.07 m3/s), no corals were seen at this location. At inshore station WW, corals off the pipeline were sparsely distributed but were numerous and thriving on the armor rock over the pipeline. In 1998 the inshore transect (Alpha), off the armor rock, was covered (30%) with the alga Dictyopteris plagiogramma; however, in 1999 it disappeared. This seaweed was also abundant at this location in 1995, 1996, and 1997. The water was clear at all stations surveyed (13 to 20 m horizontal visibility), and the surrounding sediments were clean and white. No significant deleterious effect due to outfall operation and discharge were seen on the biological community at the stations surveyed. The increase in fish diversity and abundance at the diffuser since 1997 may be due to natural fluctuations in abundance or to environmental conditions suitable to the fish populations living there.\n",
            "\n",
            "\n",
            "Score: 0.543404\n",
            "Title: Carbonate data collected from R/V Hildebrand in the SEFCRI region of the Florida Reef Tract from 2014-05-27 to 2015-09-02 (NCEI Accession 0157022)\n",
            "Abstract: This data set includes seawater chemistry that was collected in coral reef habitats located within the SEFCRI region as well as inlets and outfalls that release nutrient rich and/or sediment laden freshwater to the coastal waters South Florida. Freshwater runoff and riverine inputs are known to be enriched in dissolved inorganic carbon, and diluted lower saline waters are known to have elevated pCO2 (e.g., Manzello et al. 2013) which is why those areas in addition to the reef sites were included in our analyses. This data along with other data collected in the field were used to inform the overall project looking at the sensitivity of the SEFCRI region to OA.\n",
            "\n",
            "We measured ambient seasonal variability across inshore/offshore reef habitats to predict the response of the CaCO3 budget of coral reefs in the SEFCRI region to ocean acidification. This data set includes all of the seawater samples that were collected and analyzed to identify the carbonate chemistry in this region.\n",
            "\n",
            "\n"
          ]
        }
      ]
    }
  ]
}